The active safety systems used in automotive field are largely exploiting lane detection technique for warning the vehicle drivers to correct any unintended road departure and to reach fully autonomous vehicles. Due to its ability, to be programmed, to perform complex mathematical functions and its characterization of high speed processing, Field Programmable Gate Array (FPGA) could cope with the requirement of lane detection implementation and application. In the present work, lane detection is implemented using FPGA for day vision. This necessitates utilization of image processing techniques like filtering, edge detection and thresholding. The lane detection is performed by firstly capturing the image from a video camera and converted to gray scale. Then, a noise filtering process for gray image is performed using Gaussian and average filter. Methods from first and second order edge detection techniques have been selected for the purpose of lane edge detection. The effect of manually changing the threshold level on image enhancement has been examined. The results showed that raising threshold level would better enhance the image. The type of FPGA device used in the present work is Altera DE2. Firstly, the version DE2 Cyclone II start with (11xxxxxx-xxxx) together with Genx camera has been used. This camera supports both formats NTSC and PAL, while the above version of FPGA backups only NTSC format. The software of lane detection is designed and coded using Verilog language.
The document describes a novel FPGA implementation of an image scaling processor using bilinear interpolation. The proposed method uses sharpening and clamp filters as pre-filters to the bilinear interpolator in order to improve image quality during scaling. The bilinear interpolation algorithm was chosen due to its lower complexity compared to other methods. The design was implemented in Verilog and synthesized for an FPGA, achieving a maximum frequency of 215.64MHz for 64x64 grayscale images. The hardware resources required were moderately lower than other algorithms.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A vlsi architecture for efficient removal of noises and enhancement of imagesIAEME Publication
This document summarizes a proposed VLSI architecture for removing noise and enhancing images. The architecture uses a decision tree-based approach with three modules: an isolation module to identify noisy pixels, a fringe module to determine if pixels are on edges, and a similarity module to further analyze pixels. Noisy pixels are replaced with reconstructed values from an edge-preserving filter. Histogram equalization is then applied to improve image quality. The proposed architecture is implemented on FPGA and evaluated on different types of noises using metrics like PSNR and MSE.
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document describes a real-time vehicle license plate identification system (RTVLPIS) developed using image processing techniques in MATLAB. The system takes an image of a vehicle, extracts the license plate region using edge detection and segmentation, isolates the characters, and performs optical character recognition to identify the license plate numbers. The key steps involve image acquisition, thresholding, edge detection, noise elimination, segmentation, and character recognition. The system has applications in areas like parking management, border control, toll collection and traffic monitoring.
THE REDUCTION IN COMPUTATION TIME IN THE COLOR IMAGE DECOMPOSITION WITH THE B...IJCSEIT Journal
This paper presents two different approaches in color image decomposition domain with Bidimensional
Empirical Mode Decomposition (BEMD). The first approach applies the BEMD on each channel
separately and the second is based on interpolation of each channel in the sifting process. The comparison
of two approaches shows the same performance of each approach in terms of visual quality, but they do not
provide the same results in execution time which presents the most important criteron in real time
applications. It was shown that the second BEMD approach based on interpolation of each channel in the
sifting process, gives a gain in the point of view the execution time.
Final Thesis Presentation Licenseplaterecognitionincomplexscenesdswazalwar
Dhawal S Wazalwar presented his master's thesis on a license plate recognition system at Illinois Institute of Technology. The system uses image processing techniques like edge detection, morphological operations, and thresholding to detect license plates. It then segments characters and extracts features for recognition using a neural network classifier. Experimental results on over 1500 images showed average plate detection of 98.1% and character recognition of 97.05%. Further improvements could enhance performance for low contrast or non-standard plates.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The document describes a novel FPGA implementation of an image scaling processor using bilinear interpolation. The proposed method uses sharpening and clamp filters as pre-filters to the bilinear interpolator in order to improve image quality during scaling. The bilinear interpolation algorithm was chosen due to its lower complexity compared to other methods. The design was implemented in Verilog and synthesized for an FPGA, achieving a maximum frequency of 215.64MHz for 64x64 grayscale images. The hardware resources required were moderately lower than other algorithms.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
A vlsi architecture for efficient removal of noises and enhancement of imagesIAEME Publication
This document summarizes a proposed VLSI architecture for removing noise and enhancing images. The architecture uses a decision tree-based approach with three modules: an isolation module to identify noisy pixels, a fringe module to determine if pixels are on edges, and a similarity module to further analyze pixels. Noisy pixels are replaced with reconstructed values from an edge-preserving filter. Histogram equalization is then applied to improve image quality. The proposed architecture is implemented on FPGA and evaluated on different types of noises using metrics like PSNR and MSE.
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document describes a real-time vehicle license plate identification system (RTVLPIS) developed using image processing techniques in MATLAB. The system takes an image of a vehicle, extracts the license plate region using edge detection and segmentation, isolates the characters, and performs optical character recognition to identify the license plate numbers. The key steps involve image acquisition, thresholding, edge detection, noise elimination, segmentation, and character recognition. The system has applications in areas like parking management, border control, toll collection and traffic monitoring.
THE REDUCTION IN COMPUTATION TIME IN THE COLOR IMAGE DECOMPOSITION WITH THE B...IJCSEIT Journal
This paper presents two different approaches in color image decomposition domain with Bidimensional
Empirical Mode Decomposition (BEMD). The first approach applies the BEMD on each channel
separately and the second is based on interpolation of each channel in the sifting process. The comparison
of two approaches shows the same performance of each approach in terms of visual quality, but they do not
provide the same results in execution time which presents the most important criteron in real time
applications. It was shown that the second BEMD approach based on interpolation of each channel in the
sifting process, gives a gain in the point of view the execution time.
Final Thesis Presentation Licenseplaterecognitionincomplexscenesdswazalwar
Dhawal S Wazalwar presented his master's thesis on a license plate recognition system at Illinois Institute of Technology. The system uses image processing techniques like edge detection, morphological operations, and thresholding to detect license plates. It then segments characters and extracts features for recognition using a neural network classifier. Experimental results on over 1500 images showed average plate detection of 98.1% and character recognition of 97.05%. Further improvements could enhance performance for low contrast or non-standard plates.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Ieee projects 2012 2013 - Digital Image ProcessingK Sundaresh Ka
ieee projects download, base paper for ieee projects, ieee projects list, ieee projects titles, ieee projects for cse, ieee projects on networking,ieee projects 2012, ieee projects 2013, final year project, computer science final year projects, final year projects for information technology, ieee final year projects, final year students projects, students projects in java, students projects download, students projects in java with source code, students projects architecture, free ieee papers
This document summarizes an article from the International Journal of Electronics and Communication Engineering & Technology. The article reviews methods for automatic license plate recognition (ALPR), which involves image acquisition, preprocessing, license plate detection, character segmentation, and character recognition. Common techniques discussed include binarization, connected component labeling, Hough transforms, neural networks, and support vector machines. The goal of the paper is to present a detailed review of the processes and methods used in ALPR systems.
Enhancement of genetic image watermarking robust against cropping attackijfcstjournal
The enhancement of image watermarking algorithm robust against particular attack by using genetic
algorithm is presented here. There is a trade-off between imperceptibility and robustness in image
watermarking. To preserve both of these characteristics in digital image watermarking in a logical value,
the genetic algorithm is used. Some factors were introduced for providing robustness of image
watermarking against cropping attack such as the Centre of Interest Proximity Factor (CIPF), the
Complexity Factor (CF) and the Priority Coefficient (PC).
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
IRJET- Spatial Clustering Method for Satellite Image SegmentationIRJET Journal
This document proposes a spatial clustering method for satellite image segmentation using neuro fuzzy logic c-means (NFLC). NFLC estimates the number of objects/samples in a satellite image based on texture, color, shape, size, and calculates the regions of roads, buildings and vegetation. It implements neighborhood weighting using self-organizing map (SOM) to calculate image clusters iteratively. Experimental results show NFLC obtains high edge accuracy compared to fuzzy local information c-means and can extract valuable information from satellite images without preprocessing.
IRJET- A Review on Face Detection and Expression RecognitionIRJET Journal
This document reviews face detection and expression recognition techniques. It discusses common methods for face detection including knowledge-based, feature-based, template matching and appearance-based. For expression recognition it covers preprocessing, feature extraction using local binary patterns (LBP) and principal component analysis (PCA). LBP represents textures as histograms of local binary patterns. PCA performs dimensionality reduction to extract the most important features. The document also provides examples of implementing a basic face recognition system and compares LBP and PCA methods.
License plate recognition for toll payment applicationeSAT Journals
Abstract Automatic License Plate Recognition (ALPR) is the method for the extraction of vehicle license plate information from images. It can be used on various applications such as Pay-Per -Use roads (Electronic Toll Collection), Parking lots and arterial traffic conditions monitoring. Automatic License Plate Recognition uses infrared cameras to capture images under varied lighting and weather conditions. The objective of this paper is to implement K-Means Clustering Algorithm for License plate extraction & Maximally stable extreme region for license plate segmentation , Template matching method for license plate recognition & also payment in toll plaza and parking lots automatically by detecting the number plates of vehicles which in turn reduce the traffic and consumption of time in toll stations. Keywords: Automatic License Plate Recognition (ALPR), Maximally Stable Extreme Region (MSER), Template matching, and Character Recognition
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
License Plate Recognition using Morphological Operation. Amitava Choudhury
This paper describes an efficient technique of locating and
extracting license plate and recognizing each segmented
character. The proposed model can be subdivided into four
parts- Digitization of image, Edge Detection, Separation of
characters and Template Matching. In this work, we propose a
method which is based on morphological operations where
different Structuring Elements (SE) are used to maximally
eliminate non-plate region and enhance plate region.
Character segmentation is done using Connected Component
Analysis. Correlation based template matching technique is
used for recognition of characters. This system is
implemented using MATLAB7.4.0. The proposed system is
mainly applicable to Indian License Plates.
IRJET- Road Feature Extraction from High Resolution Satellite Images using Ne...IRJET Journal
This document describes a method to detect road damage like potholes using images from satellite or other platforms. It involves:
1. Acquiring high resolution images of roads from satellites or other sources.
2. Pre-processing the images by converting to grayscale and enhancing to remove noise.
3. Using a convolutional neural network (CNN) to extract features from the images by applying filters and pooling layers to detect patterns like potholes.
4. Classifying sections of the road as containing damage or not and notifying authorities automatically through an Android app if damage is found.
The goal is to accurately detect road damage from images to help authorities maintain roads and reduce accidents. The described method uses
Mobile Based Application to Scan the Number Plate and To Verify the Owner Det...inventionjournals
Any License plate recognition system usually passes through three steps of image processing: 1) Extraction of a license plate region; 2) Segmentation of the plate characters; and 3) Recognition of each character. A number of algorithms have been proposed in recent times for efficient disposal of the application. The purpose of this project was to develop a real time application which recognizes number plates from cars at a gate, for example at the entrance of a parking area or a border crossing. The system, based on regular PC with mobile camera, catches video frames which include a visible car number plate and processes them. Once a number plate is detected, its digits are recognized, displayed on the User Interface or checked against a database.The software aspect of the system runs on mobile hardware and can be linked to other applications or databases. It first uses a series of image manipulation techniques to detect, normalize and enhance the Image of the number plate, and then optical character recognition (ocr) to extract the alpha numeric text of number plate. The system are generally deployed in one of two basic approaches: one allows for the entire process to be performed at the lane location in real-time. The other will reveal the driver’s profile by checking in the registered database.
This document proposes a multi-level block truncation code algorithm for RGB image compression to achieve low bit rates and high quality. The algorithm combines bit mapping and quantization by dividing images into blocks, calculating thresholds, quantizing thresholds, and representing blocks with bit maps. It was tested on standard images like flowers, Lena, and baboon. Results showed improved peak signal-to-noise ratio and mean squared error compared to existing methods, demonstrating the effectiveness of the proposed multi-level block truncation code algorithm for image compression.
Traffic sign detection via graph based ranking and segmentationPREMSAI CHEEDELLA
The majority of the existing traffic sign detection system use shape information, but the methods of remain limited in regard to detecting and segmenting traffic signs from a complex background.
Automated License Plate Recognition for Toll Booth ApplicationIJERA Editor
This document describes an automated license plate recognition system that can be used for toll booth applications. It analyzes images of vehicles to detect and recognize their license plates for automated payment of tolls. The system uses image processing techniques like thresholding, edge detection and template matching to locate and extract the license plate from an image. It then recognizes the characters on the plate using a neural network and compares it to databases to obtain vehicle information. The key steps involve preprocessing the image, segmenting the license plate region, extracting and enhancing the characters, and recognizing the plate number. This automated system allows contactless and real-time processing of vehicles for toll payment and has applications in traffic management and security control.
This document summarizes key concepts in digital image processing, including:
1) Image processing transforms digital images for viewing or analysis and includes image-to-image, image-to-information, and information-to-image transformations.
2) Image-to-image transformations like adjustments to tonescale, contrast, and geometry are used to enhance or alter digital images for output or diagnosis.
3) Image-to-information transformations extract data from images through techniques like histograms, compression, and segmentation for analysis.
4) Information-to-image transformations are needed to reconstruct images for output through techniques like decompression and scaling.
Number Plate Recognition of Still Images in Vehicular Parking SystemIRJET Journal
This document discusses a proposed method for number plate recognition in vehicle parking systems using image processing techniques. It begins with an abstract that outlines the increasing need for automated vehicle management systems due to rising vehicle and traffic volumes. It then provides an overview of the key steps in number plate recognition systems - plate detection, character segmentation, and character recognition. The proposed method uses profile projection for segmentation and neural networks for recognition. The document reviews several existing plate detection methods and their limitations. It proposes a new method that uses edge detection and morphological operations to isolate the license plate from an image while removing noise. Finally, it discusses factors to consider for license plate detection and different image segmentation techniques used in existing automatic number plate recognition systems.
FPGA IMPLEMENTATION OF SOFT OUTPUT VITERBI ALGORITHM USING MEMORYLESS HYBRID ...VLSICS Design
The importance of convolutional codes is well established. They are widely used to encode digital data before transmission through noisy or error-prone communication channels to reduce occurrence of errors and memory. This paper presents novel decoding technique, memoryless Hybrid Register Exchange with simulation and FPGA implementation results. It requires single register as compared to Register Exchange Method (REM) & Hybrid Register Exchange Method (HREM); therefore the data trans-fer operations and ultimately the switching activity will get reduced.
IRJET- Image based Approach for Indian Fake Note Detection by Dark Channe...IRJET Journal
This document presents a proposed method for detecting fake Indian currency notes using image processing techniques. The proposed system takes an image of a currency note as input and performs pre-processing including resizing, restoration, and enhancement. It then applies "X-ray vision" using dark channel prior to extract inner and outer edges of patterns in the image. The extracted patterns are labeled and classified using a fuzzy classifier. The system is able to classify images as real or fake currency with 90-95% accuracy. The document reviews related work on currency detection and provides details on the proposed methodology, which includes image acquisition, pre-processing, enhancement, dark channel prior, labeling, and fuzzy classification. Results are presented showing the output of each step.
ROBUST COLOUR IMAGE WATERMARKING SCHEME BASED ON FEATURE POINTS AND IMAGE NOR...csandit
Geometric attacks can desynchronize the location of the watermark and hence cause incorrect
watermark detection. This paper presents a robust colour image watermarking scheme based on
visually significant feature points and image normalization technique. The feature points are
used as synchronization marks between watermark embedding and detection. The watermark is
embedded into the non overlapped normalized circular regions in the luminance component or
the blue component of a color image. The embedding of the watermark is carried out by
modifying the DCT coefficients values in selected blocks. The original unmarked image is not
required for watermark extraction Experimental results show that the proposed scheme
successfully makes the watermark perceptually invisible as well as robust to common signal
processing and geometric attacks.
Stereo matching based on absolute differences for multiple objects detectionTELKOMNIKA JOURNAL
This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detion using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.
PARALLEL GENERATION OF IMAGE LAYERS CONSTRUCTED BY EDGE DETECTION USING MESSA...ijcsit
Edge detection is one of the most fundamental algorithms in digital image processing. Many algorithms have been implemented to construct image layers extracted from the original image based on selecting threshold parameters. Changing theses parameters to get a high quality layer is time consuming. In this paper, we propose two parallel technique, NASHT1 and NASHT2, to generate multiple layers of an input
image automatically to enable the image tester to select the highest quality detected edges. In addition, the
effect of intensive I/O operations and the number of parallel running processes on the performance of the proposed techniques have also been studied.
Ieee projects 2012 2013 - Digital Image ProcessingK Sundaresh Ka
ieee projects download, base paper for ieee projects, ieee projects list, ieee projects titles, ieee projects for cse, ieee projects on networking,ieee projects 2012, ieee projects 2013, final year project, computer science final year projects, final year projects for information technology, ieee final year projects, final year students projects, students projects in java, students projects download, students projects in java with source code, students projects architecture, free ieee papers
This document summarizes an article from the International Journal of Electronics and Communication Engineering & Technology. The article reviews methods for automatic license plate recognition (ALPR), which involves image acquisition, preprocessing, license plate detection, character segmentation, and character recognition. Common techniques discussed include binarization, connected component labeling, Hough transforms, neural networks, and support vector machines. The goal of the paper is to present a detailed review of the processes and methods used in ALPR systems.
Enhancement of genetic image watermarking robust against cropping attackijfcstjournal
The enhancement of image watermarking algorithm robust against particular attack by using genetic
algorithm is presented here. There is a trade-off between imperceptibility and robustness in image
watermarking. To preserve both of these characteristics in digital image watermarking in a logical value,
the genetic algorithm is used. Some factors were introduced for providing robustness of image
watermarking against cropping attack such as the Centre of Interest Proximity Factor (CIPF), the
Complexity Factor (CF) and the Priority Coefficient (PC).
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
IRJET- Spatial Clustering Method for Satellite Image SegmentationIRJET Journal
This document proposes a spatial clustering method for satellite image segmentation using neuro fuzzy logic c-means (NFLC). NFLC estimates the number of objects/samples in a satellite image based on texture, color, shape, size, and calculates the regions of roads, buildings and vegetation. It implements neighborhood weighting using self-organizing map (SOM) to calculate image clusters iteratively. Experimental results show NFLC obtains high edge accuracy compared to fuzzy local information c-means and can extract valuable information from satellite images without preprocessing.
IRJET- A Review on Face Detection and Expression RecognitionIRJET Journal
This document reviews face detection and expression recognition techniques. It discusses common methods for face detection including knowledge-based, feature-based, template matching and appearance-based. For expression recognition it covers preprocessing, feature extraction using local binary patterns (LBP) and principal component analysis (PCA). LBP represents textures as histograms of local binary patterns. PCA performs dimensionality reduction to extract the most important features. The document also provides examples of implementing a basic face recognition system and compares LBP and PCA methods.
License plate recognition for toll payment applicationeSAT Journals
Abstract Automatic License Plate Recognition (ALPR) is the method for the extraction of vehicle license plate information from images. It can be used on various applications such as Pay-Per -Use roads (Electronic Toll Collection), Parking lots and arterial traffic conditions monitoring. Automatic License Plate Recognition uses infrared cameras to capture images under varied lighting and weather conditions. The objective of this paper is to implement K-Means Clustering Algorithm for License plate extraction & Maximally stable extreme region for license plate segmentation , Template matching method for license plate recognition & also payment in toll plaza and parking lots automatically by detecting the number plates of vehicles which in turn reduce the traffic and consumption of time in toll stations. Keywords: Automatic License Plate Recognition (ALPR), Maximally Stable Extreme Region (MSER), Template matching, and Character Recognition
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
License Plate Recognition using Morphological Operation. Amitava Choudhury
This paper describes an efficient technique of locating and
extracting license plate and recognizing each segmented
character. The proposed model can be subdivided into four
parts- Digitization of image, Edge Detection, Separation of
characters and Template Matching. In this work, we propose a
method which is based on morphological operations where
different Structuring Elements (SE) are used to maximally
eliminate non-plate region and enhance plate region.
Character segmentation is done using Connected Component
Analysis. Correlation based template matching technique is
used for recognition of characters. This system is
implemented using MATLAB7.4.0. The proposed system is
mainly applicable to Indian License Plates.
IRJET- Road Feature Extraction from High Resolution Satellite Images using Ne...IRJET Journal
This document describes a method to detect road damage like potholes using images from satellite or other platforms. It involves:
1. Acquiring high resolution images of roads from satellites or other sources.
2. Pre-processing the images by converting to grayscale and enhancing to remove noise.
3. Using a convolutional neural network (CNN) to extract features from the images by applying filters and pooling layers to detect patterns like potholes.
4. Classifying sections of the road as containing damage or not and notifying authorities automatically through an Android app if damage is found.
The goal is to accurately detect road damage from images to help authorities maintain roads and reduce accidents. The described method uses
Mobile Based Application to Scan the Number Plate and To Verify the Owner Det...inventionjournals
Any License plate recognition system usually passes through three steps of image processing: 1) Extraction of a license plate region; 2) Segmentation of the plate characters; and 3) Recognition of each character. A number of algorithms have been proposed in recent times for efficient disposal of the application. The purpose of this project was to develop a real time application which recognizes number plates from cars at a gate, for example at the entrance of a parking area or a border crossing. The system, based on regular PC with mobile camera, catches video frames which include a visible car number plate and processes them. Once a number plate is detected, its digits are recognized, displayed on the User Interface or checked against a database.The software aspect of the system runs on mobile hardware and can be linked to other applications or databases. It first uses a series of image manipulation techniques to detect, normalize and enhance the Image of the number plate, and then optical character recognition (ocr) to extract the alpha numeric text of number plate. The system are generally deployed in one of two basic approaches: one allows for the entire process to be performed at the lane location in real-time. The other will reveal the driver’s profile by checking in the registered database.
This document proposes a multi-level block truncation code algorithm for RGB image compression to achieve low bit rates and high quality. The algorithm combines bit mapping and quantization by dividing images into blocks, calculating thresholds, quantizing thresholds, and representing blocks with bit maps. It was tested on standard images like flowers, Lena, and baboon. Results showed improved peak signal-to-noise ratio and mean squared error compared to existing methods, demonstrating the effectiveness of the proposed multi-level block truncation code algorithm for image compression.
Traffic sign detection via graph based ranking and segmentationPREMSAI CHEEDELLA
The majority of the existing traffic sign detection system use shape information, but the methods of remain limited in regard to detecting and segmenting traffic signs from a complex background.
Automated License Plate Recognition for Toll Booth ApplicationIJERA Editor
This document describes an automated license plate recognition system that can be used for toll booth applications. It analyzes images of vehicles to detect and recognize their license plates for automated payment of tolls. The system uses image processing techniques like thresholding, edge detection and template matching to locate and extract the license plate from an image. It then recognizes the characters on the plate using a neural network and compares it to databases to obtain vehicle information. The key steps involve preprocessing the image, segmenting the license plate region, extracting and enhancing the characters, and recognizing the plate number. This automated system allows contactless and real-time processing of vehicles for toll payment and has applications in traffic management and security control.
This document summarizes key concepts in digital image processing, including:
1) Image processing transforms digital images for viewing or analysis and includes image-to-image, image-to-information, and information-to-image transformations.
2) Image-to-image transformations like adjustments to tonescale, contrast, and geometry are used to enhance or alter digital images for output or diagnosis.
3) Image-to-information transformations extract data from images through techniques like histograms, compression, and segmentation for analysis.
4) Information-to-image transformations are needed to reconstruct images for output through techniques like decompression and scaling.
Number Plate Recognition of Still Images in Vehicular Parking SystemIRJET Journal
This document discusses a proposed method for number plate recognition in vehicle parking systems using image processing techniques. It begins with an abstract that outlines the increasing need for automated vehicle management systems due to rising vehicle and traffic volumes. It then provides an overview of the key steps in number plate recognition systems - plate detection, character segmentation, and character recognition. The proposed method uses profile projection for segmentation and neural networks for recognition. The document reviews several existing plate detection methods and their limitations. It proposes a new method that uses edge detection and morphological operations to isolate the license plate from an image while removing noise. Finally, it discusses factors to consider for license plate detection and different image segmentation techniques used in existing automatic number plate recognition systems.
FPGA IMPLEMENTATION OF SOFT OUTPUT VITERBI ALGORITHM USING MEMORYLESS HYBRID ...VLSICS Design
The importance of convolutional codes is well established. They are widely used to encode digital data before transmission through noisy or error-prone communication channels to reduce occurrence of errors and memory. This paper presents novel decoding technique, memoryless Hybrid Register Exchange with simulation and FPGA implementation results. It requires single register as compared to Register Exchange Method (REM) & Hybrid Register Exchange Method (HREM); therefore the data trans-fer operations and ultimately the switching activity will get reduced.
IRJET- Image based Approach for Indian Fake Note Detection by Dark Channe...IRJET Journal
This document presents a proposed method for detecting fake Indian currency notes using image processing techniques. The proposed system takes an image of a currency note as input and performs pre-processing including resizing, restoration, and enhancement. It then applies "X-ray vision" using dark channel prior to extract inner and outer edges of patterns in the image. The extracted patterns are labeled and classified using a fuzzy classifier. The system is able to classify images as real or fake currency with 90-95% accuracy. The document reviews related work on currency detection and provides details on the proposed methodology, which includes image acquisition, pre-processing, enhancement, dark channel prior, labeling, and fuzzy classification. Results are presented showing the output of each step.
ROBUST COLOUR IMAGE WATERMARKING SCHEME BASED ON FEATURE POINTS AND IMAGE NOR...csandit
Geometric attacks can desynchronize the location of the watermark and hence cause incorrect
watermark detection. This paper presents a robust colour image watermarking scheme based on
visually significant feature points and image normalization technique. The feature points are
used as synchronization marks between watermark embedding and detection. The watermark is
embedded into the non overlapped normalized circular regions in the luminance component or
the blue component of a color image. The embedding of the watermark is carried out by
modifying the DCT coefficients values in selected blocks. The original unmarked image is not
required for watermark extraction Experimental results show that the proposed scheme
successfully makes the watermark perceptually invisible as well as robust to common signal
processing and geometric attacks.
Stereo matching based on absolute differences for multiple objects detectionTELKOMNIKA JOURNAL
This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detion using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.
PARALLEL GENERATION OF IMAGE LAYERS CONSTRUCTED BY EDGE DETECTION USING MESSA...ijcsit
Edge detection is one of the most fundamental algorithms in digital image processing. Many algorithms have been implemented to construct image layers extracted from the original image based on selecting threshold parameters. Changing theses parameters to get a high quality layer is time consuming. In this paper, we propose two parallel technique, NASHT1 and NASHT2, to generate multiple layers of an input
image automatically to enable the image tester to select the highest quality detected edges. In addition, the
effect of intensive I/O operations and the number of parallel running processes on the performance of the proposed techniques have also been studied.
Implementation of Lane Line Detection using HoughTransformation and Gaussian ...IRJET Journal
This document summarizes a research paper that implements lane line detection in images and videos using the Hough transform and Gaussian smoothing. The methodology section outlines the steps taken, which include converting the image to grayscale, applying Gaussian smoothing for noise reduction, using Canny edge detection to extract edges, and applying the Hough transform to detect lane lines. Key algorithms discussed are Gaussian smoothing, Canny edge detection, Hough transformation, grayscale conversion, and defining a region of interest. The implementation section demonstrates applying these techniques to detect lane lines, including masking the image, edge detection, and identifying the lane lines.
AN EFFICIENT M-ARY QIM DATA HIDING ALGORITHM FOR THE APPLICATION TO IMAGE ERR...IJNSA Journal
Methods like edge directed interpolation and projection onto convex sets (POCS) that are widely used for image error concealment to produce better image quality are complex in nature and also time consuming. Moreover, those methods are not suitable for real time error concealment where the decoder may not have sufficient computation power or done in online. In this paper, we propose a data-hiding scheme for error concealment of digital image. Edge direction information of a block is extracted in the encoder and is embedded imperceptibly into the host media using quantization index modulation (QIM), thus reduces work load of the decoder. The system performance in term of fidelity and computational load is improved using M-ary data modulation based on near-orthogonal QIM. The decoder extracts the embedded
features (edge information) and those features are then used for recovery of lost data. Experimental results duly support the effectiveness of the proposed scheme.
Digital image watermarking using dct with high security ofIAEME Publication
1) The document describes a new approach to digital image watermarking using discrete cosine transform (DCT) and image fusion.
2) It embeds a watermark into the middle frequency DCT coefficients of an image for imperceptibility and robustness.
3) To increase security, it then uses image fusion techniques from the MATLAB Wavelet Toolbox to combine the original and watermarked images into a single synthesized image, eliminating the need to transmit the original image separately.
Enhanced Algorithm for Obstacle Detection and Avoidance Using a Hybrid of Pla...IOSR Journals
This document presents an enhanced algorithm for obstacle detection and avoidance using a hybrid of plane-to-plane homography, image segmentation, corner detection, and edge detection techniques. The algorithm aims to improve upon previous methods by eliminating false positives, reducing unreliable corners and broken edges, providing depth perception without planar assumptions, and requiring less processing power. The key components of the algorithm include plane-to-plane homography, image segmentation, Canny edge detection, Harris corner detection, and the RANSAC sampling method for system analysis. Test results on sample images show the algorithm can accurately detect obstacles based on texture differences while reducing noise from ground plane textures.
AUTOMATIC SPEED CONTROLLING OF VEHICLE BASED ON SIGNBOARD DETECTION USING IMA...IRJET Journal
This document proposes an automatic vehicle speed control system based on traffic sign detection using image processing. The system uses a Raspberry Pi camera to capture images of signboards and an image processing module to detect and recognize speed limit signs in various lighting conditions. It then sends the detected speed limit to a speed control module, which reduces the vehicle's speed according to the sign using a BLDC motor controller. The goal is to reduce accidents caused by ignoring speed limit signs by automatically enforcing the speed limit. The system was found to reduce accidents by 30% in testing by controlling the vehicle's speed based on detected signboard speeds.
Deep hypersphere embedding for real-time face recognitionTELKOMNIKA JOURNAL
With the advancement of human-computer interaction capabilities of robots, computer vision surveillance systems involving security yields a large impact in the research industry by helping in digitalization of certain security processes. Recognizing a face in the computer vision involves identification and classification of which faces belongs to the same person by means of comparing face embedding vectors. In an organization that has a large and diverse labelled dataset on a large number of epoch, oftentimes, creates a training difficulties involving incompatibility in different versions of face embedding that leads to poor face recognition accuracy. In this paper, we will design and implement robotic vision security surveillance system incorporating hybrid combination of MTCNN for face detection, and FaceNet as the unified embedding for face recognition and clustering.
IRJET- SEPD Technique for Removal of Salt and Pepper Noise in Digital ImagesIRJET Journal
This document describes a technique called SEPD (Simple Edge-Preserved Denoising) for removing salt and pepper noise from digital images. SEPD uses a 3x3 pixel window to detect and filter impulse noise while preserving edges. It works by detecting minimum and maximum pixel values (extreme values) in the window, and then uses any directional edges present to estimate the value of the central pixel if it contains impulse noise. The proposed SEPD technique was implemented in VLSI with low computational complexity and memory requirements, making it suitable for real-time embedded applications. Experimental results showed the SEPD technique achieved better image quality than previous methods while using less hardware resources.
A Hardware Model to Measure Motion Estimation with Bit Plane Matching AlgorithmTELKOMNIKA JOURNAL
The multistep approach involving combination of techniques is referred as motion estimation.
The proposed approach is an adaptive control system to measure the motion from starting point to limit of
search. The motion patterns are used to analyze and avoid stationary regions of image. The algorithm
proposed is robust efficient and the calculations justify its advantages. The motivation of the work is to
maximize the encoding speed and visual quality with the help of motion vector algorithm. In this work a
hardware model is developed in which a frame of pictures are captured and sent via serial port to the system.
MATLAB simulation tool is used to detect the motion among the picture frame. Once any motion is detected
that signal is sent to the hardware which will give the appropriate sign accordingly. This system is developed
on two platforms (hardware as well software) to estimate and measure the motion vectors
Improving of Fingerprint Segmentation Images Based on K-MEANS and DBSCAN Clus...IJECEIAES
Nowadays, the fingerprint identification system is the most exploited sector of biometric. Fingerprint image segmentation is considered one of its first processing stage. Thus, this stage affects typically the feature extraction and matching process which leads to fingerprint recognition system with high accuracy. In this paper, three major steps are proposed. First, Soble and TopHat filtering method have been used to improve the quality of the fingerprint images. Then, for each local block in fingerprint image, an accurate separation of the foreground and background region is obtained by K-means clustering for combining 5-dimensional characteristics vector (variance, difference of mean, gradient coherence, ridge direction and energy spectrum). Additionally, in our approach, the local variance thresholding is used to reduce computing time for segmentation. Finally, we are combined to our system DBSCAN clustering which has been performed in order to overcome the drawbacks of K-means classification in fingerprint images segmentation. The proposed algorithm is tested on four different databases. Experimental results demonstrate that our approach is significantly efficacy against some recently published techniques in terms of separation between the ridge and non-ridge region.
This document summarizes a thesis presentation on an autonomous robotic system for nondestructive evaluation of asphalt pavement using deep learning. The system uses a robot equipped with vision sensors and an impact echo sensor. Deep learning models are used to detect cracks from images and classify crack severity from impact echo signals. The robot can autonomously collect data, perform real-time crack detection using onboard processing, and present severity maps quantifying the cracks. The system provides a low-cost way to inspect roads and quantify cracking issues. Future work could improve low-light crack detection, evaluate subsurface conditions, and integrate additional sensors to cover more area faster.
IRJET- Geological Boundary Detection for Satellite Images using AI TechniqueIRJET Journal
This document summarizes a research paper that proposes a method for detecting geological boundaries in satellite images using artificial intelligence techniques. The method involves pre-processing images, generating histograms to analyze pixel values, performing 2D convolution on image planes, applying a particle swarm optimization algorithm to identify boundaries, and testing the approach on pre-flood and post-flood satellite images of Kerala, India. The results show differences in detected geological boundaries between the two images, allowing changes from flooding to be identified. The method provides a way to automatically analyze satellite imagery and extract geological boundary information.
Offline signatures matching using haar wavelet subbandsTELKOMNIKA JOURNAL
The complexity of multimedia contents is significantly increasing in the current world. This leads to an exigent demand for developing highly effective systems tosatisfy human needs. Until today, handwritten signature considered an important means that is used in banks and businesses to evidence identity, so there are many works triedto develop a method for recognition purpose. This paper introduced an efficient technique for offline signature recognition depending on extracting the local feature by utilizing the haar wavelet subbands and energy. Three different setsof features are utilized by partitioning the signature image into non overlapping blocks where different block sizes are used. CEDAR signature database is used asa dataset for testing purpose. The results achieved by this technique indicate a high performance in signature recognition.
IRJET - Change Detection in Satellite Images using Convolutional Neural N...IRJET Journal
The document describes a method for detecting changes in satellite images using convolutional neural networks. It discusses how existing methods have limitations in terms of accuracy and speed. The proposed method uses preprocessing techniques like median filtering and non-local means filtering. It then applies convolutional neural networks to extracted compressed image features and classify detected changes. The method forms a difference image without explicitly training on change images, making it unsupervised. Testing achieved 91.63% accuracy in change detection, showing the effectiveness of the proposed convolutional neural network approach.
The document presents a new efficient color image compression technique that aims to improve the quality of decompressed images while achieving higher compression ratios. It does this by compressing important edge parts of the image differently than non-edge background parts. Specifically, it applies low-quality lossy compression to non-edge parts and high-quality lossy compression to edge parts. The technique uses edge detection, adaptive thresholding based on local variance and mean, and discrete cosine transform followed by quantization and entropy encoding. Experimental results on various images show it achieves better compression ratios, lower bit rates, and higher peak signal to noise ratios compared to non-adaptive methods.
Real Time Implementation of Ede Detection Technique for Angiogram Images on FPGAIRJET Journal
This document presents a new edge detection algorithm for angiogram images and its implementation on an FPGA. It begins with an introduction to angiography and importance of edge detection in analyzing angiogram images. It then describes the proposed algorithm which includes histogram equalization for enhancement followed by a modified Canny edge detection approach. The key steps of the modified Canny approach are also outlined. Experimental results on angiogram images demonstrate that the proposed FPGA implementation takes only 0.562ms for execution while maintaining accuracy. In conclusion, the algorithm is able to efficiently detect blood vessel edges in angiogram images making it useful for analyzing vascular diseases.
FPGA Implementation of 2-D DCT & DWT Engines for Vision Based Tracking of Dyn...IJERA Editor
Real time motion estimation for tracking is a challenging task. Several techniques can transform an image into frequency domain, such as DCT, DFT and wavelet transform. Direct implementation of 2-D DCT takes N^4 multiplications for an N x N image which is impractical. The proposed architecture for implementation of 2-D DCT uses look up tables. They are used to store pre-computed vector products that completely eliminate the multiplier. This makes the architecture highly time efficient, and the routing delay and power consumption is also reduced significantly. Another approach, 2-D discrete wavelet transform based motion estimation (DWT-ME) provides substantial improvements in quality and area. The proposed architecture uses Haar wavelet transform for motion estimation. In this paper, we present the comparison of the performance of discrete cosine transform, discrete wavelet transform for implementation in motion estimation.
Lane Detection and Traffic Sign Recognition using OpenCV and Deep Learning fo...IRJET Journal
This document discusses lane detection and traffic sign recognition methods for autonomous vehicles. It proposes using OpenCV and deep learning techniques for lane detection and a CNN model for traffic sign recognition. For lane detection, it describes using frame masking, image thresholding, and Hough line transformation on camera images to detect lane markings. For traffic sign recognition, it discusses pre-processing images, developing a CNN architecture called EdLeNet based on LeNet, and achieving over 98% accuracy on a test set for sign classification. The goal is to incorporate these computer vision methods into driver assistance systems to help enable safer autonomous driving.
The document describes a system for recognizing fake currency notes using image processing techniques. It discusses how advances in color printing have made it easier to counterfeit currency notes. The proposed system uses image acquisition, preprocessing, grayscale conversion, edge detection, image segmentation, and feature extraction to analyze images of currency notes and compare them to a dataset of original notes to determine if they are fake or real. The key features extracted for analysis include the security thread, serial number, latent image, watermark, and identification mark. The system is designed to be simple, fast, and accurately detect counterfeits.
Similar to Lane detection system for day vision using altera DE2 (20)
Amazon products reviews classification based on machine learning, deep learni...TELKOMNIKA JOURNAL
In recent times, the trend of online shopping through e-commerce stores and websites has grown to a huge extent. Whenever a product is purchased on an e-commerce platform, people leave their reviews about the product. These reviews are very helpful for the store owners and the product’s manufacturers for the betterment of their work process as well as product quality. An automated system is proposed in this work that operates on two datasets D1 and D2 obtained from Amazon. After certain preprocessing steps, N-gram and word embedding-based features are extracted using term frequency-inverse document frequency (TF-IDF), bag of words (BoW) and global vectors (GloVe), and Word2vec, respectively. Four machine learning (ML) models support vector machines (SVM), logistic regression (RF), logistic regression (LR), multinomial Naïve Bayes (MNB), two deep learning (DL) models convolutional neural network (CNN), long-short term memory (LSTM), and standalone bidirectional encoder representations (BERT) are used to classify reviews as either positive or negative. The results obtained by the standard ML, DL models and BERT are evaluated using certain performance evaluation measures. BERT turns out to be the best-performing model in the case of D1 with an accuracy of 90% on features derived by word embedding models while the CNN provides the best accuracy of 97% upon word embedding features in the case of D2. The proposed model shows better overall performance on D2 as compared to D1.
Design, simulation, and analysis of microstrip patch antenna for wireless app...TELKOMNIKA JOURNAL
In this study, a microstrip patch antenna that works at 3.6 GHz was built and tested to see how well it works. In this work, Rogers RT/Duroid 5880 has been used as the substrate material, with a dielectric permittivity of 2.2 and a thickness of 0.3451 mm; it serves as the base for the examined antenna. The computer simulation technology (CST) studio suite is utilized to show the recommended antenna design. The goal of this study was to get a more extensive transmission capacity, a lower voltage standing wave ratio (VSWR), and a lower return loss, but the main goal was to get a higher gain, directivity, and efficiency. After simulation, the return loss, gain, directivity, bandwidth, and efficiency of the supplied antenna are found to be -17.626 dB, 9.671 dBi, 9.924 dBi, 0.2 GHz, and 97.45%, respectively. Besides, the recreation uncovered that the transfer speed side-lobe level at phi was much better than those of the earlier works, at -28.8 dB, respectively. Thus, it makes a solid contender for remote innovation and more robust communication.
Design and simulation an optimal enhanced PI controller for congestion avoida...TELKOMNIKA JOURNAL
This document describes using a snake optimization algorithm to tune the gains of an enhanced proportional-integral controller for congestion avoidance in a TCP/AQM system. The controller aims to maintain a stable and desired queue size without noise or transmission problems. A linearized model of the TCP/AQM system is presented. An enhanced PI controller combining nonlinear gain and original PI gains is proposed. The snake optimization algorithm is then used to tune the parameters of the enhanced PI controller to achieve optimal system performance and response. Simulation results are discussed showing the proposed controller provides a stable and robust behavior for congestion control.
Improving the detection of intrusion in vehicular ad-hoc networks with modifi...TELKOMNIKA JOURNAL
Vehicular ad-hoc networks (VANETs) are wireless-equipped vehicles that form networks along the road. The security of this network has been a major challenge. The identity-based cryptosystem (IBC) previously used to secure the networks suffers from membership authentication security features. This paper focuses on improving the detection of intruders in VANETs with a modified identity-based cryptosystem (MIBC). The MIBC is developed using a non-singular elliptic curve with Lagrange interpolation. The public key of vehicles and roadside units on the network are derived from number plates and location identification numbers, respectively. Pseudo-identities are used to mask the real identity of users to preserve their privacy. The membership authentication mechanism ensures that only valid and authenticated members of the network are allowed to join the network. The performance of the MIBC is evaluated using intrusion detection ratio (IDR) and computation time (CT) and then validated with the existing IBC. The result obtained shows that the MIBC recorded an IDR of 99.3% against 94.3% obtained for the existing identity-based cryptosystem (EIBC) for 140 unregistered vehicles attempting to intrude on the network. The MIBC shows lower CT values of 1.17 ms against 1.70 ms for EIBC. The MIBC can be used to improve the security of VANETs.
Conceptual model of internet banking adoption with perceived risk and trust f...TELKOMNIKA JOURNAL
Understanding the primary factors of internet banking (IB) acceptance is critical for both banks and users; nevertheless, our knowledge of the role of users’ perceived risk and trust in IB adoption is limited. As a result, we develop a conceptual model by incorporating perceived risk and trust into the technology acceptance model (TAM) theory toward the IB. The proper research emphasized that the most essential component in explaining IB adoption behavior is behavioral intention to use IB adoption. TAM is helpful for figuring out how elements that affect IB adoption are connected to one another. According to previous literature on IB and the use of such technology in Iraq, one has to choose a theoretical foundation that may justify the acceptance of IB from the customer’s perspective. The conceptual model was therefore constructed using the TAM as a foundation. Furthermore, perceived risk and trust were added to the TAM dimensions as external factors. The key objective of this work was to extend the TAM to construct a conceptual model for IB adoption and to get sufficient theoretical support from the existing literature for the essential elements and their relationships in order to unearth new insights about factors responsible for IB adoption.
Efficient combined fuzzy logic and LMS algorithm for smart antennaTELKOMNIKA JOURNAL
The smart antennas are broadly used in wireless communication. The least mean square (LMS) algorithm is a procedure that is concerned in controlling the smart antenna pattern to accommodate specified requirements such as steering the beam toward the desired signal, in addition to placing the deep nulls in the direction of unwanted signals. The conventional LMS (C-LMS) has some drawbacks like slow convergence speed besides high steady state fluctuation error. To overcome these shortcomings, the present paper adopts an adaptive fuzzy control step size least mean square (FC-LMS) algorithm to adjust its step size. Computer simulation outcomes illustrate that the given model has fast convergence rate as well as low mean square error steady state.
Design and implementation of a LoRa-based system for warning of forest fireTELKOMNIKA JOURNAL
This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos.The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.
Wavelet-based sensing technique in cognitive radio networkTELKOMNIKA JOURNAL
Cognitive radio is a smart radio that can change its transmitter parameter based on interaction with the environment in which it operates. The demand for frequency spectrum is growing due to a big data issue as many Internet of Things (IoT) devices are in the network. Based on previous research, most frequency spectrum was used, but some spectrums were not used, called spectrum hole. Energy detection is one of the spectrum sensing methods that has been frequently used since it is easy to use and does not require license users to have any prior signal understanding. But this technique is incapable of detecting at low signal-to-noise ratio (SNR) levels. Therefore, the wavelet-based sensing is proposed to overcome this issue and detect spectrum holes. The main objective of this work is to evaluate the performance of wavelet-based sensing and compare it with the energy detection technique. The findings show that the percentage of detection in wavelet-based sensing is 83% higher than energy detection performance. This result indicates that the wavelet-based sensing has higher precision in detection and the interference towards primary user can be decreased.
A novel compact dual-band bandstop filter with enhanced rejection bandsTELKOMNIKA JOURNAL
In this paper, we present the design of a new wide dual-band bandstop filter (DBBSF) using nonuniform transmission lines. The method used to design this filter is to replace conventional uniform transmission lines with nonuniform lines governed by a truncated Fourier series. Based on how impedances are profiled in the proposed DBBSF structure, the fractional bandwidths of the two 10 dB-down rejection bands are widened to 39.72% and 52.63%, respectively, and the physical size has been reduced compared to that of the filter with the uniform transmission lines. The results of the electromagnetic (EM) simulation support the obtained analytical response and show an improved frequency behavior.
Deep learning approach to DDoS attack with imbalanced data at the application...TELKOMNIKA JOURNAL
A distributed denial of service (DDoS) attack is where one or more computers attack or target a server computer, by flooding internet traffic to the server. As a result, the server cannot be accessed by legitimate users. A result of this attack causes enormous losses for a company because it can reduce the level of user trust, and reduce the company’s reputation to lose customers due to downtime. One of the services at the application layer that can be accessed by users is a web-based lightweight directory access protocol (LDAP) service that can provide safe and easy services to access directory applications. We used a deep learning approach to detect DDoS attacks on the CICDDoS 2019 dataset on a complex computer network at the application layer to get fast and accurate results for dealing with unbalanced data. Based on the results obtained, it is observed that DDoS attack detection using a deep learning approach on imbalanced data performs better when implemented using synthetic minority oversampling technique (SMOTE) method for binary classes. On the other hand, the proposed deep learning approach performs better for detecting DDoS attacks in multiclass when implemented using the adaptive synthetic (ADASYN) method.
The appearance of uncertainties and disturbances often effects the characteristics of either linear or nonlinear systems. Plus, the stabilization process may be deteriorated thus incurring a catastrophic effect to the system performance. As such, this manuscript addresses the concept of matching condition for the systems that are suffering from miss-match uncertainties and exogeneous disturbances. The perturbation towards the system at hand is assumed to be known and unbounded. To reach this outcome, uncertainties and their classifications are reviewed thoroughly. The structural matching condition is proposed and tabulated in the proposition 1. Two types of mathematical expressions are presented to distinguish the system with matched uncertainty and the system with miss-matched uncertainty. Lastly, two-dimensional numerical expressions are provided to practice the proposed proposition. The outcome shows that matching condition has the ability to change the system to a design-friendly model for asymptotic stabilization.
Implementation of FinFET technology based low power 4×4 Wallace tree multipli...TELKOMNIKA JOURNAL
Many systems, including digital signal processors, finite impulse response (FIR) filters, application-specific integrated circuits, and microprocessors, use multipliers. The demand for low power multipliers is gradually rising day by day in the current technological trend. In this study, we describe a 4×4 Wallace multiplier based on a carry select adder (CSA) that uses less power and has a better power delay product than existing multipliers. HSPICE tool at 16 nm technology is used to simulate the results. In comparison to the traditional CSA-based multiplier, which has a power consumption of 1.7 µW and power delay product (PDP) of 57.3 fJ, the results demonstrate that the Wallace multiplier design employing CSA with first zero finding logic (FZF) logic has the lowest power consumption of 1.4 µW and PDP of 27.5 fJ.
Evaluation of the weighted-overlap add model with massive MIMO in a 5G systemTELKOMNIKA JOURNAL
The flaw in 5G orthogonal frequency division multiplexing (OFDM) becomes apparent in high-speed situations. Because the doppler effect causes frequency shifts, the orthogonality of OFDM subcarriers is broken, lowering both their bit error rate (BER) and throughput output. As part of this research, we use a novel design that combines massive multiple input multiple output (MIMO) and weighted overlap and add (WOLA) to improve the performance of 5G systems. To determine which design is superior, throughput and BER are calculated for both the proposed design and OFDM. The results of the improved system show a massive improvement in performance ver the conventional system and significant improvements with massive MIMO, including the best throughput and BER. When compared to conventional systems, the improved system has a throughput that is around 22% higher and the best performance in terms of BER, but it still has around 25% less error than OFDM.
Reflector antenna design in different frequencies using frequency selective s...TELKOMNIKA JOURNAL
In this study, it is aimed to obtain two different asymmetric radiation patterns obtained from antennas in the shape of the cross-section of a parabolic reflector (fan blade type antennas) and antennas with cosecant-square radiation characteristics at two different frequencies from a single antenna. For this purpose, firstly, a fan blade type antenna design will be made, and then the reflective surface of this antenna will be completed to the shape of the reflective surface of the antenna with the cosecant-square radiation characteristic with the frequency selective surface designed to provide the characteristics suitable for the purpose. The frequency selective surface designed and it provides the perfect transmission as possible at 4 GHz operating frequency, while it will act as a band-quenching filter for electromagnetic waves at 5 GHz operating frequency and will be a reflective surface. Thanks to this frequency selective surface to be used as a reflective surface in the antenna, a fan blade type radiation characteristic at 4 GHz operating frequency will be obtained, while a cosecant-square radiation characteristic at 5 GHz operating frequency will be obtained.
Reagentless iron detection in water based on unclad fiber optical sensorTELKOMNIKA JOURNAL
A simple and low-cost fiber based optical sensor for iron detection is demonstrated in this paper. The sensor head consist of an unclad optical fiber with the unclad length of 1 cm and it has a straight structure. Results obtained shows a linear relationship between the output light intensity and iron concentration, illustrating the functionality of this iron optical sensor. Based on the experimental results, the sensitivity and linearity are achieved at 0.0328/ppm and 0.9824 respectively at the wavelength of 690 nm. With the same wavelength, other performance parameters are also studied. Resolution and limit of detection (LOD) are found to be 0.3049 ppm and 0.0755 ppm correspondingly. This iron sensor is advantageous in that it does not require any reagent for detection, enabling it to be simpler and cost-effective in the implementation of the iron sensing.
Impact of CuS counter electrode calcination temperature on quantum dot sensit...TELKOMNIKA JOURNAL
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
In place of the commercial Pt electrode used in quantum sensitized solar cells, the low-cost CuS cathode is created using electrophoresis. High resolution scanning electron microscopy and X-ray diffraction were used to analyze the structure and morphology of structural cubic samples with diameters ranging from 40 nm to 200 nm. The conversion efficiency of solar cells is significantly impacted by the calcination temperatures of cathodes at 100 °C, 120 °C, 150 °C, and 180 °C under vacuum. The fluorine doped tin oxide (FTO)/CuS cathode electrode reached a maximum efficiency of 3.89% when it was calcined at 120 °C. Compared to other temperature combinations, CuS nanoparticles crystallize at 120 °C, which lowers resistance while increasing electron lifetime.
A progressive learning for structural tolerance online sequential extreme lea...TELKOMNIKA JOURNAL
This article discusses the progressive learning for structural tolerance online sequential extreme learning machine (PSTOS-ELM). PSTOS-ELM can save robust accuracy while updating the new data and the new class data on the online training situation. The robustness accuracy arises from using the householder block exact QR decomposition recursive least squares (HBQRD-RLS) of the PSTOS-ELM. This method is suitable for applications that have data streaming and often have new class data. Our experiment compares the PSTOS-ELM accuracy and accuracy robustness while data is updating with the batch-extreme learning machine (ELM) and structural tolerance online sequential extreme learning machine (STOS-ELM) that both must retrain the data in a new class data case. The experimental results show that PSTOS-ELM has accuracy and robustness comparable to ELM and STOS-ELM while also can update new class data immediately.
Electroencephalography-based brain-computer interface using neural networksTELKOMNIKA JOURNAL
This study aimed to develop a brain-computer interface that can control an electric wheelchair using electroencephalography (EEG) signals. First, we used the Mind Wave Mobile 2 device to capture raw EEG signals from the surface of the scalp. The signals were transformed into the frequency domain using fast Fourier transform (FFT) and filtered to monitor changes in attention and relaxation. Next, we performed time and frequency domain analyses to identify features for five eye gestures: opened, closed, blink per second, double blink, and lookup. The base state was the opened-eyes gesture, and we compared the features of the remaining four action gestures to the base state to identify potential gestures. We then built a multilayer neural network to classify these features into five signals that control the wheelchair’s movement. Finally, we designed an experimental wheelchair system to test the effectiveness of the proposed approach. The results demonstrate that the EEG classification was highly accurate and computationally efficient. Moreover, the average performance of the brain-controlled wheelchair system was over 75% across different individuals, which suggests the feasibility of this approach.
Adaptive segmentation algorithm based on level set model in medical imagingTELKOMNIKA JOURNAL
For image segmentation, level set models are frequently employed. It offer best solution to overcome the main limitations of deformable parametric models. However, the challenge when applying those models in medical images stills deal with removing blurs in image edges which directly affects the edge indicator function, leads to not adaptively segmenting images and causes a wrong analysis of pathologies wich prevents to conclude a correct diagnosis. To overcome such issues, an effective process is suggested by simultaneously modelling and solving systems’ two-dimensional partial differential equations (PDE). The first PDE equation allows restoration using Euler’s equation similar to an anisotropic smoothing based on a regularized Perona and Malik filter that eliminates noise while preserving edge information in accordance with detected contours in the second equation that segments the image based on the first equation solutions. This approach allows developing a new algorithm which overcome the studied model drawbacks. Results of the proposed method give clear segments that can be applied to any application. Experiments on many medical images in particular blurry images with high information losses, demonstrate that the developed approach produces superior segmentation results in terms of quantity and quality compared to other models already presented in previeous works.
Automatic channel selection using shuffled frog leaping algorithm for EEG bas...TELKOMNIKA JOURNAL
Drug addiction is a complex neurobiological disorder that necessitates comprehensive treatment of both the body and mind. It is categorized as a brain disorder due to its impact on the brain. Various methods such as electroencephalography (EEG), functional magnetic resonance imaging (FMRI), and magnetoencephalography (MEG) can capture brain activities and structures. EEG signals provide valuable insights into neurological disorders, including drug addiction. Accurate classification of drug addiction from EEG signals relies on appropriate features and channel selection. Choosing the right EEG channels is essential to reduce computational costs and mitigate the risk of overfitting associated with using all available channels. To address the challenge of optimal channel selection in addiction detection from EEG signals, this work employs the shuffled frog leaping algorithm (SFLA). SFLA facilitates the selection of appropriate channels, leading to improved accuracy. Wavelet features extracted from the selected input channel signals are then analyzed using various machine learning classifiers to detect addiction. Experimental results indicate that after selecting features from the appropriate channels, classification accuracy significantly increased across all classifiers. Particularly, the multi-layer perceptron (MLP) classifier combined with SFLA demonstrated a remarkable accuracy improvement of 15.78% while reducing time complexity.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
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2. Edge Detection Process
In the present work, the considered edge detection process comprises three stages;
Noise filtering, edge detection techniques and thresholding. In what follows, a detail explanation
will be presented [6].
2.1. Noise Filtering
Digital images are exposed to different types of noise. Noise occurs due to errors in the
acquisition process of the image and its adverse effect is that the image pixel values do not
represent the true intensities of the real scene. Various sources may cause noise in images.
Noise may come from high temperature or transmission such as electronic circuit noise. Another
source of noise is referred as quantization error which results from quantizing the pixels of
sensed image into discrete levels. The noise can be introduced through brightening shadows or
through color-balance processing [7, 8]. Many types of filters are considered in the image
processing literature for removing the noise from an image; such as median filter, mean filter,
high pass filter, average filter, Gaussian filter, inverse filter and Wiener filtering. In the present
work, two famous filters have been only employed for real time edge detection; namely average
and Gaussian filters [9].
2.1.1. Averaging Operator
Noise reduction is the main advantageous effect of averaging. On the other hand, the
averaging could cause blurring which results in reducing the details in an image. Moreover, it is
a low-pass filter; as it permits retention of low spatial frequencies and suppression of high
frequency components. Larger template, say 3×3 or 5×5, helps to get rid more noise (high
frequencies), however it leads to reduce the level of details [8], [10]. The template weighting
functions of averaging operator are unity (or 1/9 such as to guarantee that the outcome of
averaging nine white pixels is white) as indicated in Figure 1.
Figure 1. 5×5 averaging operator template [3]
2.1.2. Gaussian Averaging Operator
The Gaussian averaging operator is one of the best smoothing technique for noise
removal of the image. The Gaussian relationship sets up the values of Gaussian operator
template. As shown in (1), the formula describes the Gaussian function at coordinates (𝑥, 𝑦) and
it is controlled by the variance 𝜎2
𝐺(𝑥, 𝑦, 𝜎) =
1
2𝜋 𝜎2 𝑒
−
𝑥2+𝑦2
2𝜎2
(1)
To find the coefficients for Gaussian template using (1) which is then convolved with the
image. The 3 × 3 convolution template for Gaussian with standard deviation σ = 1 is given
in (2) [9], [11].
G=[
1 2 1
2 4 2
1 2 1
] (2)
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2.2. Edge Detection Techniques
The techniques of edge detection are based on mathematical methods which are
capable of recognizing and detecting points in a digital image at which the brightness of the
image is sharply changed. These critical points are typically arranged into groups of curved line
segments called edges which are represented as binary image. The main objectives of edge
detection are [9], [12]:
a. Producing line-based drawings of scenes derived from their images.
b. Extracting the important features from image edges such as corners, lines and curves. The
algorithms of computer vision (e.g., recognition) are mostly utilized from such features.
c. Intensity changes at different image locations are physically caused by various events such
as [8], [13];
d. discontinuity in surface orientation and/or surface color and texture (surface boundary),
e. discontinuity in depth and/or surface color and texture (object boundary),
f. geometric and non-geometric events,
g. direct reflection of light, such as a mirror (specularity),
h. inter-reflections and shadows (from the same object or other objects).
The edge detection techniques comprise two groups; first order and second order.
Examples of the first group are Robert, Sobel, Priwitt, kirsch and Robinson technique [14].
Sobel is the most famous algorithm. Robinson technique is characterized by having many
masks; as two of these masks are similar to those of Sobel technique. In the present work,
Sobel and Robinson have been selected as representatives of first order group. On the other
hand, the second order group includes mainly Laplacian, Laplacian of gaussain and
Marr–Hildreth algorithm [15]. The first two techniques are chosen to implement real time edge
detection.
2.2.1. First Order Edge Detection
In image processing application, the calculation of the first derivative of a signal is
approximated by finite differences as indicated in (3):
𝑓′(𝑥) = lim 𝑑→0
𝑓(𝑥+𝑑)−𝑓(𝑥)
𝑑
(3)
if d=1, then the discrete derivative version is written as
𝑓′(𝑥) ≅ 𝑓(𝑥 + 𝑑) − 𝑓(𝑥) (4)
the local minima or maxima of first derivative are utilized to detect the points lying on an edge as
illustrated in Figure 2 [8], [16].
Figure 2. Edge detection derivatives [5]
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a. Sobel Edge Detection Technique
The Sobel operator is based on central difference; however, it assigns higher weight
value to the central pixels when averaging. The following equation gives 3×3 convolution of
Sobel operators.
𝐺𝑥 = [
1 2 1
0 0 0
−1 −2 −1
] and 𝐺 𝑦 = [
1 0 −1
2 0 −2
1 0 −1
] (5)
The two masks are individually applied on the input image to give gradient component
in horizontal orientation Gx and other gradient component in vertical orientation Gy [3], [17]. The
magnitude gradient of is usually computed using (6):
𝐺 [𝑓(𝑥, 𝑦)] = |𝐺𝑥| + |𝐺 𝑦| (6)
the gradient direction can be represented as:
𝜃(𝑥, 𝑦) = 𝑡𝑎𝑛−1
(𝐺 𝑦 𝐺𝑥⁄ ) (7)
b. Robinson Edge Detection Technique
The masks of Robinson edge detection masks are called compass masks since they
are defined by rotating a single mask to eight main compass orientations: north, west, south,
east, north-west, north-east, south-west, and south-east. The masks are depicted in Equation
below:
𝑅0
= [
1 0 1
−2 0 2
−1 0 1
]
𝑅1
= [
0 1 2
−1 0 1
−2 −1 0
]
𝑅2 =
[
1 2 1
0 0 0
−1 −2 −1
],
𝑅3 [
2 1 0
1 0 −1
0 −1 −2
]
(8)
𝑅4
= [
1 0 −1
2 0 −2
1 0 −1
]
𝑅5 = [
0 −1 −2
1 0 −1
2 1 0
]
𝑅6
= [
−1 −2 −1
0 0 0
1 2 1
]
𝑅7
= [
−2 −1 0
−1 0 1
0 1 2
]
The maximum value resulting from the convolution of each of the masks with the image
is defined as the edge magnitude. The edge detection is found by the mask that produces the
maximum magnitude. It is worth to note that the masks R2 and R4 are identical to the Sobel
masks. Extraction of explicit information about edge in any direction can be found by rotating
any of the edge detection masks in a manner like compass masks [4], [18].
2.2.2. Second-order Edge Detection
Points which lie on an edge can be detected by detecting the zero-crossing of the
second derivative as shown in Figure 2. The second derivative is approximated by finite
differences as depicted in (9) [19]:
𝑓′′(𝑥) = lim 𝑑→0
𝑓′(𝑥+𝑑)−𝑓′(𝑥)
𝑑
≅ 𝑓′
(𝑥 + 1) − 𝑓′
(𝑥)
= 𝑓(𝑥 + 2) − 𝑓(𝑥 + 1) − [𝑓(𝑥 + 1) − 𝑓(𝑥)]
= 𝑓(𝑥 + 2) − 2𝑓(𝑥 + 1) + 𝑓(𝑥) (9)
where 𝑑 = 1
a. Laplacian Edge Detection
The Laplacian definition of an image defined by f(x, y) is a second order derivative given
by (10):
𝛻2
𝑓(𝑥, 𝑦) =
𝜕2 𝑓
𝜕𝑥2 +
𝜕2 𝑓
𝜕𝑦2 (10)
The approximation version of above equation in digital image is given to 4 and
8-connectivities as indicated (11) and (12), respectively [11], [20]:
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4-connectivity: [
0 −1 0
−1 4 −1
0 −1 0
]
∇2
𝑓 = 4 𝑧5 − (𝑧2 + 𝑧4 + 𝑧6 + 𝑧8) (11)
8-connectivity: [
−1 −1 −1
−1 8 −1
−1 −1 −1
]
∇2
𝑓 = 8 𝑧5 − (𝑧1 + 𝑧2 + 𝑧3 + 𝑧4 + 𝑧6 + 𝑧7 + 𝑧8 + 𝑧9) (12)
where zi is the value of i-th position of matrix element; i.e., for 3 × 3 mask, the following mask
can be represented in terms of zi [9], [21].
[
𝑧1 𝑧2 𝑧3
𝑧4 𝑧5 𝑧6
𝑧7 𝑧8 𝑧9
]
b. Techniq Laplacian of Gaussian (LoG) Operator
Laplacian operator is noise susceptible. To decrease the noise sensitivity, Laplacian of
Gaussian (LoG) operator can be used instead. LoG is a two-step algorithm; it firstly performs
the Gaussian smoothing followed by Laplacian operation. Low susceptibility of this method to
noise is due to noise reduction caused by Gaussian function and probability of detection of false
edges is considerably minimized by resultant Laplacian mask. The LoG function for convolution
is defined as follows [14], [22]:
𝐿𝑂𝐺 (𝑥, 𝑦) =
1
𝜋 𝜎4 [1 −
𝑥2+𝑦2
2𝜎2 ] 𝑒
−
𝑥2+𝑦2
2𝜎2
(13)
Figure 3 (a) shows the three-dimension plot of LoG function which looks like a Mexican
hat. The above equation tells that a wider convolution mask is required for higher value of σ. It is
easy to find out that the first zero-crossing of the LoG function occurs at √2σ
n
. Two-dimensional
cross section of the zero-crossing of the Mexican hat is illustrated in Figure 3 (b) [17], [23]. In
(14) utilizes 5 × 5 convolution mask to carry out LoG edge detector.
(a) (b)
Figure 3. Laplacian of Gaussian technique (a) plot of LoG function in 3D (b) zero crossing
[
0
0
1
0
0
0
1
2
1
0
1
2
−16
2
1
0
1
2
1
0
0
0
1
0
0]
(14)
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2.3. Thresholding (Gray Scale Thresholding)
Thresholding is a popular technique used for segmentation of monochrome image. The
image intensity defined by f(x, y) comprises light object and dark background. A threshold level
T is designated to extract the objects from background and the thresholded image g(x, y) can be
described using (15). The (15) is only suitable when the image has 2 dominant gray level
ranges [3], [24], [25].
𝑔(𝑥, 𝑦) = {
1 𝑖𝑓 𝑓 (𝑥, 𝑦) > 𝑇
0 𝑖𝑓 𝑓 (𝑥, 𝑦) ≤ 𝑇
(15)
3. Video Signal Formatting for Lane Detection
In what follows, video signal formatting will be elaborated for lane detection. The data
read directly from camera and acquired by composite cable is available in the ITU656 format as
illustrated in Figure 4 [3]. These data have to be firstly converted into standard format YUV
4:2:2, which is commonly referred to as YCbCr. This format, YCbCr, is a color display format
and it is composed of three components; the luma component (Y), blue-difference component
(Cb) and red-difference chroma component (Cr). This format is a way of encrypting RGB data
and it does not represent an actual color space of its own [4].
Figure 4. Hardware setup
As soon as the data is changed to this format, the system will sample down the signal
from 720 to 640 horizontal pixels. Then the converted data is fed into an SDRAM FIFO which
works as a frame buffer. Another conversion process is performed for the output of the FIFO,
which transform the data from the format YUV 4:2:2 to the format YUV 4:4:4. At last, newly
formatted YCbCr data is once more converted to the standard 10-bit RGB format.
The RGB data is directly fed into VGA controller to be next displayed on standard VGA
monitor. However, instead of going directly to the VGA controller, the RGB data are admitted to
go through other modules; filtering and edge detection modules [13]. The above discussion is
illustrated in Figure 5 and the functionality description of different modules in this figure is
summarized in Table 1. The extension (.v) indicates that the Verilog is the programming
Languages that has written the code.
Table 1. Summary of Modules
Module name Description
DE2_TV.v This file contains the top-level module.
TD_Detect.v Detect a valid video input.
ITU_656_Decoder.v Convert the video from ITU-656 format to YUV 4:2:2 formats.
DIV.v
Used by previous module to reduce the horizontal resolution from 720 to 640 lines
per frame.
Sdram_Control_4port.v A buffer used for combining the odd and even field of a frame.
YUV422_to_444.v Convert the video from 4:2:2 to format 4:4:4 formats.
YCbCr2RGB.v Convert the video word from 8 to 10 bits to match the video output DAC.
VGA_Ctrl.v Controls the output to the LCD monitor.
Line_Buffer.v One line delay buffer used for de-interlacing the image.
I2C_AV_Config.v Module controlling the video decoder.
Average.v Modules of average filter.
Gaussain.v Modules of gaussain filter.
Sobel.v Sobel module.
Robinson.v Robinson module.
LoG.v Laplacian of gaussain module.
Laplacian.v Laplacian modules.
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It is interesting for edge detection to vary the threshold level to display different amounts
of detail on the VGA screen. There are eighteen switches resident on the DE2 board. Table 2
illustrates how they can be utilized for resetting, switching filter and for manually adjusting
threshold level of edge detection.
Figure 5. Block diagram of a lane detection
Table 2. Control Edge Detections in DE2 Cyclone II
Input key/switch Action
Key 0 Reset
Switch 0 Toggle between gray scale image and edge detected image.
Switch 1 Turn on filtering.
Switch 2 to Switch 17 Adjust edge detection threshold.
4. Result
In this section the lane edge detction will be performed based on the the used version of
DE2 board and the camera, the results can be devided into either day or night lane detection.
As mentioned earlier, the camera Genx (GDV 720 ultra) has two standards; PAL and NTSC,
meanwhile Altera DE2 starting with (11xx...) supports only NTSC standard. Also, this type of
camera does not support night vision; and hence, the day vision is only considered in the
present scenario. Original and gray scale images are displayed in Figure 6 and Figure 7,
respectively.
Figure 6. Original color image Figure 7. Gray scale image
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4.1. Filtering
To reduce the noise; the gray scale image is then fed to two filters, gaussain and
avarage filters. Figure 8 and Figure 9 shows the images resulting from avarage and gaussain
filters, respectively. It is clear from these figures that the average filter has better filtering
charcteristics than Gaussian filter. Therefore, the latter filter will be excluded and average filter
will be mainly relied on for filtering purposes in all next simulations. In what follows, the filtered
image, based on average filter, is allowed to be edge detected. Two types of edge detection
techniques has been suggested; first and second order techniques.
Figure 8. Gaussian filter with standard
deviation (σ = 1)
Figure 9. Average filter
4.2. First-order Edge Detection
For the first order type, two techniques has been selected, Sobel and Robinson; while
for the other type, Laplacian and Laplacian of Gaussian (LoG) has been chosen. Figure 10 and
Figure 11 shows the images coming out from Sobel and Robinson techniques, respectively.
One can easily see that more details would appear in image resulting from Robinson than that
resulting from Sobel method. This may be attributed to eight mask operator which supports
Robinson technique and four mask operator which support the other method.
Figure 10. Sobel edge detection Figure 11. Robinson edge detection
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4.3. Second-order Edge Detection
Next, the second order type has been considered. The edge detected images from
Laplacian and LoG is illustrated in Figure 12 and Figure 13, respectively. It is well-known that
this second order type could not give better results since they are based on detection of edge
location from its zero-crossing property and hence such type of edge detction techniques would
be sensetive to noise. However, it is clear from these figures that LoG gives better edge
detection features than its counterpart. The conclusion drawn from the above argument is that
Sobel edge detection technique could give the best edge detection characteristics and it
outperforms the others.
Figure 12. Lapacian edge detection Figure 13. LoG edge detection
4.4. Thresholding
It is interesting to examine the effectiveness of the considered techniques against the
change of threshold level. Three levels have been taken into account; low, medium and high.
These three levels has been practically set-up and designated using the switches implanted on
DE2 board; such that the level selection is performed manually. Table 3 shows the bands of
considered levels for both Sobel and Robinson. It is worthy to notify that the level band and
value changes according to edge detection technique, environment, type of camera, board
version and even on orientation angle of camera. For the present scenario, the low, medium
and high level values for Sobel edge detection technique are designated as
Table 3. Mechanism of Adjusting the Threshold of Edge Detection
Type edge detection Low level switches
Medium level
switches
High level switches
Sobel SW [2] to SW [3] SW [4] to SW [5] SW [6] to SW [7]
Robinson SW [2] to SW [5] SW [6] to SW [8] SW [9] to SW [10]
"SW [3]", "SW [5]" and "SW [7]", respectively. On the other hand, the low, medium and
high-level values for Robinson edge detection technique are designated as "SW [5]", "SW [8]"
and "SW [10]", respectively. The switch SW [0] is preserved for admitting either edge detection
or gray scale image and the switch SW [1] is dedicated for switching the filtering process.
Figures 14-25 show the images after detection with both first order techniques and with different
three threshold levels.
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Figure 20. Laplacian technique Figure 21. LoG technique
(low level) (medium level)
Figure 22. Laplacian technique Figure 23. LoG technique
(medium level) (medium level)
Figure 24. Laplacian technique Figure 25. LoG technique
(high level) (high level)
The conclusion drawn from this observation is that increasing the threshold level would
better enhance the edge detected image. The reason behind this enhancement is that raising
the threshold level would discard the weak features of the image with low intensity. Table 4
displays the flow summary report that appeared after Quartus II 32-bit version 11.1 succeeding
in compilation.
It is clear that Laplacian technique wins the minimum numbers of logic elements.
However, one may deduce from the table that the number of logic elements depends on number
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of masks, their size and the strategy of edge detection computing; where the Sobel technique
has 2 masks with 3 × 3 size, Robinson has 8 masks with 3 × 3 size, Laplacian has 1 mask with
3 × 3 size and LoG has 1 mask with 5 × 5 size. As such, LoG has maximum number of logic
elements due to having maximum number of masks with large mask size which in turn reserve
higher number of line buffers. It is worthy to notify that the total number of logic elements
fabricated inside FPGA under study is 33,216 total logic elements and Sobel technique,
e.g., occupy 9% of the total logic elements. It is interesting to investigate the change of table
summary after thresholding process. Table 5 lists the information about number of logic
elements, combination functions and dedicated logic registers for all considered edge detection
techniques. However, due to deleting and adding instructions at the thresholding process, there
is a slight change in the number of logic elements depending on the number of these elements
required modified instructions.
Table 4. Summary of Resources for DE2 Start with-11
Edge detection methods
Total logic
elements
Total combinational
functions
Dedicated logic
registers
Sobel edge detection 1989 1611 1209
Robinson edge detection 2656 2252 1161
Laplacian edge detection 1947 1583 1221
LoG edge detection 3860 3408 1367
Table 5. Summary of Resources after Thresholding Process
Edge detection methods
Total logic
elements
Total combinational
functions
Dedicated logic
registers
Sobel edge detection 1983 1609 1163
Robinson edge detection 2617 2262 1161
Laplacian edge detection 1974 1628 1209
LoG edge detection 3833 3380 1281
5. Conclusions
Based on the observations of the results, one may draw the following main conclusions.
For the sake of clarity, the conclusion points can be classified according to lane detection and
lane tracking scenarios. Two filters have been suggested for lane detection part; average filter
and Gaussian filter. The results of present work have shown that the average filter has much
better filtering characteristics than Gaussian one and for all considered situations. For our case,
raising the threshold level successfully enhanced the image resulting from most edge detection
techniques. This indicates that all unimportant image features, clutter and noise reside at low
level intensity. The results have shown that Sobel edge detector has the best edge detection
characteristics among the others. Also, the threshold level raising has better enhancement for
the image based on Sobel technique than that resulting from other techniques. For current work,
second order edge detection techniques failed for performing edge detection in most scenarios
and for different threshold level.The number of logic elements occupied by lane detection
process relies on the number of masks and mask size for specified edge detection algorithm. In
terms of minimum number of logic elements, Laplacian technique comes the first, while Sobel
has the second order. Due to failure of Laplacian detector in most situations, Sobel become the
first candidate edge detector.
References
[1] Roberts, Brook, et al. A Dataset for Lane Instance Segmentation in Urban Environments. arXiv
preprint arXiv:1807.01347 (2018).
[2] Cao, Jiale, Yanwei Pang, Xuelong Li. Learning multilayer channel features for pedestrian detection.
IEEE transactions on image processing. 2017; 26(7): 3210-3220.
[3] Mohammed Abdulraheem Fadhel. Design and Implementation of a Lane Detection and Tracking
System Using FPGA, M.Sc. Thesis, University of Technology, Baghdad, Iraq, 2015.
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