International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
2-Dimensional Wavelet pre-processing to extract IC-Pin information for disarr...IOSR Journals
Abstract: Due to higher processing power to cost ratio, it is now possible to replace the manual detection methods used in the IC (Integrated Circuit) industry by Image-processing based automated methods, to detect a broken pin of an IC connected on a PCB during manufacturing, which will make the process faster, easier and cheaper. In this paper an accurate and fast automatic detection method is used where the top view camera shots of PCBs are processed using advanced methods of 2-dimensional discrete wavelet pre-processing before applying edge-detection. Comparison with conventional edge detection methods such as Sobel, Prewitt and Canny edge detection without 2-D DWT is also performed. Keywords :2-dimensional wavelets, Edge detection, Machine vision, Image processing, Canny.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Denoising and Edge Detection Using SobelmethodIJMER
The main aim of our study is to detect edges in the image without any noise , In many of the images edges carry important information of the image, this paper presents a method which consists of sobel operator and discrete wavelet de-noising to do edge detection on images which include white Gaussian noises. There were so many methods for the edge detection, sobel is the one of the method, by using this sobel operator or median filtering, salt and pepper noise cannot be removed properly, so firstly we use complex wavelet to remove noise and sobel operator is used to do edge detection on the image. Through the pictures obtained by the experiment, we can observe that compared to other methods, the method has more obvious effect on edge detection.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Enhanced Optimization of Edge Detection for High Resolution Images Using Veri...ijcisjournal
dge Detection plays a crucial role in Image Processing and Segmentation where a set of algorithms aims
to identify various portions of a digital image at which a sharpened image is observed in the output or
more formally has discontinuities. The contour of Edge Detection also helps in Object Detection and
Recognition. Image edges can be detected by using two attributes such as Gradient and Laplacian. In our
Paper, we proposed a system which utilizes Canny and Sobel Operators for Edge Detection which is a
Gradient First order derivative function for edge detection by using Verilog Hardware Description
Language and in turn compared with the results of the previous paper in Matlab. The process of edge
detection in Verilog significantly reduces the processing time and filters out unneeded information, while
preserving the important structural properties of an image. This edge detection can be used to detect
vehicles in Traffic Jam, Medical imaging system for analysing MRI, x-rays by using Xilinx ISE Design
Suite 14.2.
Abstract Edge detection is a fundamental tool used in most image processing applications. We proposed a simple, fast and efficient technique to detect the edge for the identifying, locating sharp discontinuities in an image and boundary of an image. In this paper, we found that proposed method called LookUp Table performs well, which requires least computational time as compared to conventional Edge Detection techniques. And also in this paper we presented a comparative performance of various conventional Edge Detection Techniques. Keywords: Edge detectors, Lookup table.
2-Dimensional Wavelet pre-processing to extract IC-Pin information for disarr...IOSR Journals
Abstract: Due to higher processing power to cost ratio, it is now possible to replace the manual detection methods used in the IC (Integrated Circuit) industry by Image-processing based automated methods, to detect a broken pin of an IC connected on a PCB during manufacturing, which will make the process faster, easier and cheaper. In this paper an accurate and fast automatic detection method is used where the top view camera shots of PCBs are processed using advanced methods of 2-dimensional discrete wavelet pre-processing before applying edge-detection. Comparison with conventional edge detection methods such as Sobel, Prewitt and Canny edge detection without 2-D DWT is also performed. Keywords :2-dimensional wavelets, Edge detection, Machine vision, Image processing, Canny.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Denoising and Edge Detection Using SobelmethodIJMER
The main aim of our study is to detect edges in the image without any noise , In many of the images edges carry important information of the image, this paper presents a method which consists of sobel operator and discrete wavelet de-noising to do edge detection on images which include white Gaussian noises. There were so many methods for the edge detection, sobel is the one of the method, by using this sobel operator or median filtering, salt and pepper noise cannot be removed properly, so firstly we use complex wavelet to remove noise and sobel operator is used to do edge detection on the image. Through the pictures obtained by the experiment, we can observe that compared to other methods, the method has more obvious effect on edge detection.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Enhanced Optimization of Edge Detection for High Resolution Images Using Veri...ijcisjournal
dge Detection plays a crucial role in Image Processing and Segmentation where a set of algorithms aims
to identify various portions of a digital image at which a sharpened image is observed in the output or
more formally has discontinuities. The contour of Edge Detection also helps in Object Detection and
Recognition. Image edges can be detected by using two attributes such as Gradient and Laplacian. In our
Paper, we proposed a system which utilizes Canny and Sobel Operators for Edge Detection which is a
Gradient First order derivative function for edge detection by using Verilog Hardware Description
Language and in turn compared with the results of the previous paper in Matlab. The process of edge
detection in Verilog significantly reduces the processing time and filters out unneeded information, while
preserving the important structural properties of an image. This edge detection can be used to detect
vehicles in Traffic Jam, Medical imaging system for analysing MRI, x-rays by using Xilinx ISE Design
Suite 14.2.
Abstract Edge detection is a fundamental tool used in most image processing applications. We proposed a simple, fast and efficient technique to detect the edge for the identifying, locating sharp discontinuities in an image and boundary of an image. In this paper, we found that proposed method called LookUp Table performs well, which requires least computational time as compared to conventional Edge Detection techniques. And also in this paper we presented a comparative performance of various conventional Edge Detection Techniques. Keywords: Edge detectors, Lookup table.
This document discusses a hand gesture recognition system for underprivileged individuals. It begins by outlining the key steps in hand gesture recognition systems: image capture, pre-processing, segmentation, feature extraction and gesture recognition. It then goes into more detail on specific techniques for each step, such as thresholding and edge detection for segmentation. The document also covers applications like access control, sign language translation and future areas like biometric authentication. In conclusion, it proposes that hand gesture recognition can help disabled individuals communicate through accessible human-computer interaction.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Journals
This document summarizes an article that presents a method for implementing image segmentation using edge detection based on the Sobel edge operator on an FPGA. It describes how the Sobel operator works by calculating horizontal and vertical gradients to detect edges. The document outlines the steps to segment an image using Sobel edge detection, including applying horizontal and vertical masks, calculating the gradient, and thresholding. It also provides the architecture for the FPGA implementation, including modules for pixel generation, Sobel enhancement, edge detection, and binary segmentation. The results show edge detection outputs from MATLAB and simulation waveforms, demonstrating the FPGA-based method can perform edge-based image segmentation.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Publishing House
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.
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...IOSR Journals
This document describes a design of a Gabor filter for noise reduction in images of betel vine leaves to aid in disease segmentation. A Gabor filter is designed using Verilog HDL and implemented on a CADENCE platform. The filter takes pixel inputs from images that have undergone preprocessing like Sobel edge detection and segmentation. It convolves the pixels with stored filter coefficients to reduce noise and segment the diseased areas. The proposed Gabor filter achieves noiseless segmentation with increased speed and reduced delays compared to existing methods. It utilizes fewer resources with minimal warnings. The system could be enhanced further with 2D/3D processing and neural network training.
Edge detection of herbal plants is a set of mathematical methods which aim at identifying points in a digital image at which the image brightness changes sharply and has discontinuities. They are defined as the set of curved line segments termed edges. Effective edge detection for microscopic image of herbal plant is proposed through this paper which compares the edge detected images and then performs further segmentation. Comparison between Sobel operator, Prewitt, Canny and Robert cross operators is performed. Our method after efficient edge detection performs Gabor filter and K-means clustering to procure a better image. It is then subjected to further segmentation. Experimental methods in our proposed algorithm show that our method achieves a better edge detection as compared to other edge detector operators. Our proposed algorithm provides the maximum PSNR value of 43.684 amongst the other commercial edge detection operators.
A NOVEL APPROACH FOR SEGMENTATION OF SECTOR SCAN SONAR IMAGES USING ADAPTIVE ...ijistjournal
The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. If the background of an image is uneven, the fixed thresholding technique is not suitable to segment an image using adaptive thresholding method. In this paper a new Adaptive thresholding method is proposed to reduce the speckle noise, preserving the structural features and textural information of Sector Scan SONAR (Sound Navigation and Ranging) images. Due to the massive proliferation of SONAR images, the proposed method is very appealing in under water environment applications. In fact it is a pre- treatment required in any SONAR images analysis system. The results obtained from the proposed method were compared quantitatively and qualitatively with the results obtained from the other speckle reduction techniques and demonstrate its higher performance for speckle reduction in the SONAR images.
A survey on efficient no reference blur estimation methodseSAT Journals
Abstract Blur estimation in image processing has come to be of great importance in assessing the quality of images. This work presents a survey of no-reference blur estimation methods. A no-reference method is particularly useful, when the input image used for blur estimation does not have an available corresponding reference image. This paper provides a comparison of the methodologies of four no-reference blur estimation methods. The first method applies a scale adaptive technique of blur estimation to get better accuracy in the results. The second blur metric involves finding the energy using second order derivatives of an image using derivative pair of quadrature filters. The third blur metric is based on the kurtosis measurement in the discrete dyadic wavelet transform (DDWT) of the images. The fourth method of blur estimation is obtained by finding the ratio of sum of the edge widths of all the detected edges to the total number of edges. The results provided are useful in comparing the methods based on metrics like Spearman correlation coefficient. The results are obtained by evaluation on images from the Laboratory for Image and Video Engineering (LIVE) database. The various methods are evaluated on the images by adding varying content of noise. The performance is evaluated for 3 different categories namely Gaussian blur, motion blur and also JPEG2000 compressed images. Blur estimation finds its application in quality assessment, image fusion and auto-focusing in images. The sharpness of an image can also be found from the blur metric as sharpness is inversely proportional to blur. Sharpness metrics can also be combined with other metrics to measure overall quality of the image. Keywords: Blur estimation, blur, no-reference
This document summarizes and compares four no-reference blur estimation methods: (1) a scale adaptive wavelet transform method, (2) a method using energy of quadrature filters, (3) a kurtosis measurement method using discrete dyadic wavelet transform, and (4) a method measuring average edge width. The methods are evaluated on blurred, noisy, and compressed images from a database. Results show the quadrature filter method performs best except for compressed images, where a perceptual method works best. The scale adaptive and kurtosis methods degrade more with noise while the quadrature filter method is more robust.
This document summarizes various image segmentation techniques including region-based, edge-based, thresholding, feature-based clustering, and model-based segmentation. It provides details on each technique, including advantages and disadvantages. Region-based segmentation groups similar pixels into regions while edge-based segmentation detects boundaries between regions. Thresholding uses threshold values from histograms to segment images. Feature-based clustering groups pixels based on characteristics like intensity. Model-based segmentation uses probabilistic models like Markov random fields. The document concludes that the best technique depends on the application and image type, though thresholding is simplest computationally.
The document describes a modified Otsu method for edge detection using genetic algorithms. It begins with an introduction and literature review of existing edge detection techniques like Roberts, Sobel, and Prewitt operators as well as Otsu thresholding. The proposed technique uses genetic algorithms to determine an optimal threshold for edge detection. It initializes a population of threshold values as chromosomes, calculates their fitness based on class variance, and applies genetic operators like selection, crossover and mutation to arrive at the optimal threshold. Experimental results showed the modified Otsu method performed better than the original Otsu technique.
In this paper a novel edge detection method has been proposed which outperform Otsu method [1]. The proposed detection algorithm has been devised using the concept of genetic algorithm in spatial domain. The key of edge detection is the choice of threshold; which determines the results of edge detection. GA has been used to determine an optimal threshold over the image. Results are compared with existing Otsu technique which shows better performances
Automatic Detection of Radius of Bone FractureIRJET Journal
This document presents a proposed algorithm for automatically detecting the radius of bone fractures in x-ray images. The algorithm involves several steps: image preprocessing using filters to reduce noise, segmentation using FCM clustering to separate bone regions, feature extraction using Hough transform to identify lines and circles, and detecting the radius of fractures based on the extracted features. The algorithm was tested on 20 x-ray images and achieved about 90% accuracy in detecting fracture radii. The proposed method provides an efficient and accurate approach for fracture detection compared to other methods. Future work may focus on enhancing the algorithm to handle multiple fractures and different image modalities like CT and MRI.
Performance Evaluation of Image Edge Detection Techniques CSCJournals
The success of an image recognition procedure is related to the quality of the edges marked. The
aim of this research is to investigate and evaluate edge detection techniques when applied to
noisy images at different scales. Sobel, Prewitt, and Canny edge detection algorithms are
evaluated using artificially generated images and comparison criteria: edge quality (EQ) and map
quality (MQ). The results demonstrated that the use of these criteria can be utilized as an aid for
further analysis and arbitration to find the best edge detector for a given image.
3 ijaems nov-2015-6-development of an advanced technique for historical docum...INFOGAIN PUBLICATION
In this paper, technique used for historical document preservation is explored. In this paper a noise estimation technique is applied to know noise standard deviation. We first estimate or detect level of noise present in noisy images by selecting weak textured patches in image on the basis of gradient matrix and its statistical properties, then eliminate that noise through non local means(NLM) denoising technique that will use estimated noise level as filtering parameter for eliminating noise from the image. This technique is based on weighted average of the similar pixels in historical image. Non local means techniques removes noise from images without taking care of noise level ,it is mandatory to take care of noise level for best preserving Historical document images.
Spot Edge Detection in cDNA Microarray Images using Window based Bi-Dimension...idescitation
Ongoing Microarray is an increasingly playing a crucial role applied in the field
of medical and biological operations. The initiator of Microarray technology is M. Schena et
al. [1] and from past few years microarrays have begun to be used in many fields such as
biomedicine, mostly on cancer and Diabetic, and medical diagnoses. A Deoxyribonucleic
Acid (DNA) microarray is a collection of microscopic DNA spots attached to a solid surface,
such as glass, plastic or silicon chip forming an array. Processing of DNA microarray image
analysis includes three tasks: gridding, segmentation and intensity extraction and at the
stage of processing, the irregularities of shape and spot position which leads to generate
significant errors. This article presents a new spot edge detection method using Window
based Bi-dimensional Empirical Mode Decomposition. On separating spots form the
background area and to decreases the probability of errors and gives more accurate
information about the states of spots we are proposing a spot edge detection via WBEMD.
By using this method we can identify the spots with low density, which leads to increasing
the performance of cDNA microarray images.
Comparative Analysis of Common Edge Detection Algorithms using Pre-processing...IJECEIAES
Edge detection is the process of segmenting an image by detecting discontinuities in brightness. Several standard segmentation methods have been widely used for edge detection. However, due to inherent quality of images, these methods prove ineffective if they are applied without any preprocessing. In this paper, an image pre-processing approach has been adopted in order to get certain parameters that are useful to perform better edge detection with the standard edge detection methods. The proposed preprocessing approach involves median filtering to reduce the noise in image and then edge detection technique is carried out. Finally, Standard edge detection methods can be applied to the resultant pre-processing image and its Simulation results are show that our pre-processed approach when used with a standard edge detection method enhances its performance.
Signal Processing, Statistical and Learning Machine Techniques for Edge Detec...idescitation
A review of published articles on edge detection is
given in this paper. It includes some definitions and different
methods of edge detection in different classes. The relation
between different classes is given in this review and also gives
some calculations about their performance and application.
The edge detection methods are the combination of image
differentiation, image smoothing and a post processing for
edge labelling. A filter is used for image smoothing, due to
which noise is reduced, numerical calculation is regularized,
and to improve the accuracy and the reliability, it provide a
parametric representation that works as mathematical
microscope, that will examine it in different scales. To
represent the strength and position of edges and their
orientation, the image differentiation gives information of
intensity transition in the image. To inhibit the false edges,
produce a uniform contour of objects, and associate the
expanded ones, the edge labelling calls for post processing.
Fingerprint Registration Using Zernike Moments : An Approach for a Supervised...CSCJournals
In this work, we deal with contactless fingerprint biometrics. More specifically, we are interested in solving the problem of registration by taking into consideration some constraints such as finger rotation and translation. In the proposed method, the registration requires: (1) a segmentation technique to extract streaks, (2) a skeletonization technique to extract the center line streaks and (3) and landmarks extraction technique. The correspondence between the sets of control points, is obtained by calculating the descriptor vector of Zernike moments on a window of size RxR centered at each point. Comparison of correlation coefficients between the descriptor vectors of Zernike moments helps define the corresponding points. The estimation of parameters of the existing deformation between images is performed using RANSAC algorithm (Random SAmple Consensus) that suppresses wrong matches. Finally, performance evaluation is achieved on a set of fingerprint images where promising results are reported.
Importance of Mean Shift in Remote Sensing SegmentationIOSR Journals
1) Mean shift is a non-parametric clustering technique that can segment remote sensing images into homogeneous regions without prior knowledge of the number of clusters or constraints on cluster shape.
2) The document presents a case study demonstrating mean shift can segment an image containing oil storage tanks into distinct regions faster than level set segmentation.
3) Mean shift is shown to be well-suited for remote sensing image segmentation tasks like forest mapping and land cover classification due to its ability to handle noise, gradients, and texture variations common in real-world images.
IRJET- Digit Identification in Natural ImagesIRJET Journal
The document describes a technique to locate and recognize numbers in natural images. It involves preprocessing the image using Gaussian blur for smoothing, edge detection using Sobel or Canny operators, finding maximally stable extremal regions (MSER) to identify candidate objects, segmenting individual digits using vertical projection or contours, extracting features of each segmented digit, and classifying the digits using a technique like K-nearest neighbors. The technique aims to recognize numbers without requiring extensive training data, thus saving memory and computation time compared to traditional optical character recognition systems. Room for future improvement includes handling complex backgrounds better to make the approach more robust.
This document discusses using electrical resistivity measurements to evaluate properties of expansive soils containing bentonite. Laboratory experiments were conducted mixing bentonite into clayey soil at ratios from 10-100% to produce samples with varying swelling potential. Field electrical resistivity measurements were taken using a four-electrode probe on the soil samples. Linear correlations were determined between electrical resistivity and various soil properties including liquid limit, plastic limit, shrinkage limit, swelling pressure, and maximum dry density at different bentonite ratios. The correlations allow direct estimation of soil properties from electrical resistivity measurements in the field without laboratory testing.
This document discusses a hand gesture recognition system for underprivileged individuals. It begins by outlining the key steps in hand gesture recognition systems: image capture, pre-processing, segmentation, feature extraction and gesture recognition. It then goes into more detail on specific techniques for each step, such as thresholding and edge detection for segmentation. The document also covers applications like access control, sign language translation and future areas like biometric authentication. In conclusion, it proposes that hand gesture recognition can help disabled individuals communicate through accessible human-computer interaction.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Journals
This document summarizes an article that presents a method for implementing image segmentation using edge detection based on the Sobel edge operator on an FPGA. It describes how the Sobel operator works by calculating horizontal and vertical gradients to detect edges. The document outlines the steps to segment an image using Sobel edge detection, including applying horizontal and vertical masks, calculating the gradient, and thresholding. It also provides the architecture for the FPGA implementation, including modules for pixel generation, Sobel enhancement, edge detection, and binary segmentation. The results show edge detection outputs from MATLAB and simulation waveforms, demonstrating the FPGA-based method can perform edge-based image segmentation.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Publishing House
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.
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...IOSR Journals
This document describes a design of a Gabor filter for noise reduction in images of betel vine leaves to aid in disease segmentation. A Gabor filter is designed using Verilog HDL and implemented on a CADENCE platform. The filter takes pixel inputs from images that have undergone preprocessing like Sobel edge detection and segmentation. It convolves the pixels with stored filter coefficients to reduce noise and segment the diseased areas. The proposed Gabor filter achieves noiseless segmentation with increased speed and reduced delays compared to existing methods. It utilizes fewer resources with minimal warnings. The system could be enhanced further with 2D/3D processing and neural network training.
Edge detection of herbal plants is a set of mathematical methods which aim at identifying points in a digital image at which the image brightness changes sharply and has discontinuities. They are defined as the set of curved line segments termed edges. Effective edge detection for microscopic image of herbal plant is proposed through this paper which compares the edge detected images and then performs further segmentation. Comparison between Sobel operator, Prewitt, Canny and Robert cross operators is performed. Our method after efficient edge detection performs Gabor filter and K-means clustering to procure a better image. It is then subjected to further segmentation. Experimental methods in our proposed algorithm show that our method achieves a better edge detection as compared to other edge detector operators. Our proposed algorithm provides the maximum PSNR value of 43.684 amongst the other commercial edge detection operators.
A NOVEL APPROACH FOR SEGMENTATION OF SECTOR SCAN SONAR IMAGES USING ADAPTIVE ...ijistjournal
The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. If the background of an image is uneven, the fixed thresholding technique is not suitable to segment an image using adaptive thresholding method. In this paper a new Adaptive thresholding method is proposed to reduce the speckle noise, preserving the structural features and textural information of Sector Scan SONAR (Sound Navigation and Ranging) images. Due to the massive proliferation of SONAR images, the proposed method is very appealing in under water environment applications. In fact it is a pre- treatment required in any SONAR images analysis system. The results obtained from the proposed method were compared quantitatively and qualitatively with the results obtained from the other speckle reduction techniques and demonstrate its higher performance for speckle reduction in the SONAR images.
A survey on efficient no reference blur estimation methodseSAT Journals
Abstract Blur estimation in image processing has come to be of great importance in assessing the quality of images. This work presents a survey of no-reference blur estimation methods. A no-reference method is particularly useful, when the input image used for blur estimation does not have an available corresponding reference image. This paper provides a comparison of the methodologies of four no-reference blur estimation methods. The first method applies a scale adaptive technique of blur estimation to get better accuracy in the results. The second blur metric involves finding the energy using second order derivatives of an image using derivative pair of quadrature filters. The third blur metric is based on the kurtosis measurement in the discrete dyadic wavelet transform (DDWT) of the images. The fourth method of blur estimation is obtained by finding the ratio of sum of the edge widths of all the detected edges to the total number of edges. The results provided are useful in comparing the methods based on metrics like Spearman correlation coefficient. The results are obtained by evaluation on images from the Laboratory for Image and Video Engineering (LIVE) database. The various methods are evaluated on the images by adding varying content of noise. The performance is evaluated for 3 different categories namely Gaussian blur, motion blur and also JPEG2000 compressed images. Blur estimation finds its application in quality assessment, image fusion and auto-focusing in images. The sharpness of an image can also be found from the blur metric as sharpness is inversely proportional to blur. Sharpness metrics can also be combined with other metrics to measure overall quality of the image. Keywords: Blur estimation, blur, no-reference
This document summarizes and compares four no-reference blur estimation methods: (1) a scale adaptive wavelet transform method, (2) a method using energy of quadrature filters, (3) a kurtosis measurement method using discrete dyadic wavelet transform, and (4) a method measuring average edge width. The methods are evaluated on blurred, noisy, and compressed images from a database. Results show the quadrature filter method performs best except for compressed images, where a perceptual method works best. The scale adaptive and kurtosis methods degrade more with noise while the quadrature filter method is more robust.
This document summarizes various image segmentation techniques including region-based, edge-based, thresholding, feature-based clustering, and model-based segmentation. It provides details on each technique, including advantages and disadvantages. Region-based segmentation groups similar pixels into regions while edge-based segmentation detects boundaries between regions. Thresholding uses threshold values from histograms to segment images. Feature-based clustering groups pixels based on characteristics like intensity. Model-based segmentation uses probabilistic models like Markov random fields. The document concludes that the best technique depends on the application and image type, though thresholding is simplest computationally.
The document describes a modified Otsu method for edge detection using genetic algorithms. It begins with an introduction and literature review of existing edge detection techniques like Roberts, Sobel, and Prewitt operators as well as Otsu thresholding. The proposed technique uses genetic algorithms to determine an optimal threshold for edge detection. It initializes a population of threshold values as chromosomes, calculates their fitness based on class variance, and applies genetic operators like selection, crossover and mutation to arrive at the optimal threshold. Experimental results showed the modified Otsu method performed better than the original Otsu technique.
In this paper a novel edge detection method has been proposed which outperform Otsu method [1]. The proposed detection algorithm has been devised using the concept of genetic algorithm in spatial domain. The key of edge detection is the choice of threshold; which determines the results of edge detection. GA has been used to determine an optimal threshold over the image. Results are compared with existing Otsu technique which shows better performances
Automatic Detection of Radius of Bone FractureIRJET Journal
This document presents a proposed algorithm for automatically detecting the radius of bone fractures in x-ray images. The algorithm involves several steps: image preprocessing using filters to reduce noise, segmentation using FCM clustering to separate bone regions, feature extraction using Hough transform to identify lines and circles, and detecting the radius of fractures based on the extracted features. The algorithm was tested on 20 x-ray images and achieved about 90% accuracy in detecting fracture radii. The proposed method provides an efficient and accurate approach for fracture detection compared to other methods. Future work may focus on enhancing the algorithm to handle multiple fractures and different image modalities like CT and MRI.
Performance Evaluation of Image Edge Detection Techniques CSCJournals
The success of an image recognition procedure is related to the quality of the edges marked. The
aim of this research is to investigate and evaluate edge detection techniques when applied to
noisy images at different scales. Sobel, Prewitt, and Canny edge detection algorithms are
evaluated using artificially generated images and comparison criteria: edge quality (EQ) and map
quality (MQ). The results demonstrated that the use of these criteria can be utilized as an aid for
further analysis and arbitration to find the best edge detector for a given image.
3 ijaems nov-2015-6-development of an advanced technique for historical docum...INFOGAIN PUBLICATION
In this paper, technique used for historical document preservation is explored. In this paper a noise estimation technique is applied to know noise standard deviation. We first estimate or detect level of noise present in noisy images by selecting weak textured patches in image on the basis of gradient matrix and its statistical properties, then eliminate that noise through non local means(NLM) denoising technique that will use estimated noise level as filtering parameter for eliminating noise from the image. This technique is based on weighted average of the similar pixels in historical image. Non local means techniques removes noise from images without taking care of noise level ,it is mandatory to take care of noise level for best preserving Historical document images.
Spot Edge Detection in cDNA Microarray Images using Window based Bi-Dimension...idescitation
Ongoing Microarray is an increasingly playing a crucial role applied in the field
of medical and biological operations. The initiator of Microarray technology is M. Schena et
al. [1] and from past few years microarrays have begun to be used in many fields such as
biomedicine, mostly on cancer and Diabetic, and medical diagnoses. A Deoxyribonucleic
Acid (DNA) microarray is a collection of microscopic DNA spots attached to a solid surface,
such as glass, plastic or silicon chip forming an array. Processing of DNA microarray image
analysis includes three tasks: gridding, segmentation and intensity extraction and at the
stage of processing, the irregularities of shape and spot position which leads to generate
significant errors. This article presents a new spot edge detection method using Window
based Bi-dimensional Empirical Mode Decomposition. On separating spots form the
background area and to decreases the probability of errors and gives more accurate
information about the states of spots we are proposing a spot edge detection via WBEMD.
By using this method we can identify the spots with low density, which leads to increasing
the performance of cDNA microarray images.
Comparative Analysis of Common Edge Detection Algorithms using Pre-processing...IJECEIAES
Edge detection is the process of segmenting an image by detecting discontinuities in brightness. Several standard segmentation methods have been widely used for edge detection. However, due to inherent quality of images, these methods prove ineffective if they are applied without any preprocessing. In this paper, an image pre-processing approach has been adopted in order to get certain parameters that are useful to perform better edge detection with the standard edge detection methods. The proposed preprocessing approach involves median filtering to reduce the noise in image and then edge detection technique is carried out. Finally, Standard edge detection methods can be applied to the resultant pre-processing image and its Simulation results are show that our pre-processed approach when used with a standard edge detection method enhances its performance.
Signal Processing, Statistical and Learning Machine Techniques for Edge Detec...idescitation
A review of published articles on edge detection is
given in this paper. It includes some definitions and different
methods of edge detection in different classes. The relation
between different classes is given in this review and also gives
some calculations about their performance and application.
The edge detection methods are the combination of image
differentiation, image smoothing and a post processing for
edge labelling. A filter is used for image smoothing, due to
which noise is reduced, numerical calculation is regularized,
and to improve the accuracy and the reliability, it provide a
parametric representation that works as mathematical
microscope, that will examine it in different scales. To
represent the strength and position of edges and their
orientation, the image differentiation gives information of
intensity transition in the image. To inhibit the false edges,
produce a uniform contour of objects, and associate the
expanded ones, the edge labelling calls for post processing.
Fingerprint Registration Using Zernike Moments : An Approach for a Supervised...CSCJournals
In this work, we deal with contactless fingerprint biometrics. More specifically, we are interested in solving the problem of registration by taking into consideration some constraints such as finger rotation and translation. In the proposed method, the registration requires: (1) a segmentation technique to extract streaks, (2) a skeletonization technique to extract the center line streaks and (3) and landmarks extraction technique. The correspondence between the sets of control points, is obtained by calculating the descriptor vector of Zernike moments on a window of size RxR centered at each point. Comparison of correlation coefficients between the descriptor vectors of Zernike moments helps define the corresponding points. The estimation of parameters of the existing deformation between images is performed using RANSAC algorithm (Random SAmple Consensus) that suppresses wrong matches. Finally, performance evaluation is achieved on a set of fingerprint images where promising results are reported.
Importance of Mean Shift in Remote Sensing SegmentationIOSR Journals
1) Mean shift is a non-parametric clustering technique that can segment remote sensing images into homogeneous regions without prior knowledge of the number of clusters or constraints on cluster shape.
2) The document presents a case study demonstrating mean shift can segment an image containing oil storage tanks into distinct regions faster than level set segmentation.
3) Mean shift is shown to be well-suited for remote sensing image segmentation tasks like forest mapping and land cover classification due to its ability to handle noise, gradients, and texture variations common in real-world images.
IRJET- Digit Identification in Natural ImagesIRJET Journal
The document describes a technique to locate and recognize numbers in natural images. It involves preprocessing the image using Gaussian blur for smoothing, edge detection using Sobel or Canny operators, finding maximally stable extremal regions (MSER) to identify candidate objects, segmenting individual digits using vertical projection or contours, extracting features of each segmented digit, and classifying the digits using a technique like K-nearest neighbors. The technique aims to recognize numbers without requiring extensive training data, thus saving memory and computation time compared to traditional optical character recognition systems. Room for future improvement includes handling complex backgrounds better to make the approach more robust.
This document discusses using electrical resistivity measurements to evaluate properties of expansive soils containing bentonite. Laboratory experiments were conducted mixing bentonite into clayey soil at ratios from 10-100% to produce samples with varying swelling potential. Field electrical resistivity measurements were taken using a four-electrode probe on the soil samples. Linear correlations were determined between electrical resistivity and various soil properties including liquid limit, plastic limit, shrinkage limit, swelling pressure, and maximum dry density at different bentonite ratios. The correlations allow direct estimation of soil properties from electrical resistivity measurements in the field without laboratory testing.
This document summarizes an experimental study on the performance of an air-cooled condenser for low pressure steam condensation. Key findings include:
- Mass flow rate of condensed steam decreases with decreases in steam pressure and temperature difference.
- While capacity is sometimes limited by ambient conditions, air-cooled condensers are still preferable to traditional steam surface condensers due to water availability and environmental issues.
- Previous studies have examined the effects of ambient conditions like temperature and wind velocity on the performance of air-cooled condensers. Fins and changes to tube geometry have been used to improve performance.
This document contains a set of 43 multiple choice questions that appear to be from a final exam for a finance course. The questions cover a range of topics in corporate finance including organizational forms, capital structure, capital budgeting techniques, the cost of capital, and financial statement analysis.
Trough External Service Management Improve Quality & ProductivityIJMER
The challenges in Small car project, necessitated improvements in quality and productivity,
right from day one of implementation of project. Detailed studies on external management services,
manufacturing process, various departments involved, and procedures followed were done, and
problems in the existing system were identified and solutions were provided. The object of this paper is to
investigate methods of measuring performance. The subject of this paper is the process of implementing
methods to increase productivity. Methods (procedures) of the study. Pattern during the writing of this
work was used by scientist’s articles information about the measurement and implementation of systems
productivity. Since this work was written with the use of different methods and examples, not all of them
before writing the work were known to me, I want to present a certain part to improve the productivity of
some companies in my country.
This document appears to be a study guide for an ACC 349 final exam, listing 42 multiple choice questions covering topics related to managerial and cost accounting. The questions assess understanding of concepts like factory overhead application, manufacturing overhead allocation, job order and process costing systems, activity-based costing, standard costs, budgeting, and cost-volume-profit analysis.
This document summarizes research into improving the mechanical properties of neodymium-iron-boron bonded magnets through the addition of molybdenum disulfide (MoS2). Samples containing 0%, 0.5%, 1%, 1.5%, and 2% MoS2 by weight were produced and tested. Magnetic testing found that saturation magnetization and remanence increased with up to 1% MoS2 due to reduced friction, but decreased at higher amounts. Mechanical testing found density and compression strength increased with MoS2 due to reduced porosity, while hardness decreased slightly. Up to 1% MoS2 improved properties without harming magnetism, showing potential for stronger rare-earth magnets.
This document summarizes research that uses a binary coded genetic algorithm to optimize the design of fin arrays on an internal combustion engine cylinder. The goal is to maximize heat transfer through either rectangular or triangular fin profiles. Mathematical models are developed to calculate the heat transfer based on parameters like fin length, thickness, spacing, and material properties. Constraints related to fin mass and dimensions are also considered. The genetic algorithm operates on a population of potential designs encoded as binary strings. Over generations, the algorithms applies reproduction, crossover and mutation to arrive at optimal fin array designs that maximize heat transfer within the given constraints. Results show that the triangular fin profile provides advantages over the rectangular profile in terms of heat transfer per unit mass.
This document summarizes a study on the sintering mechanism of silica gel nanoparticles during initial heating stages. Thermogravimetric analysis showed weight loss up to 600°C attributed to removal of absorbed water and hydroxyl groups. Diffuse reflectance infrared spectroscopy revealed bonding changes - bridged hydroxyl groups were replaced by free hydroxyl and water molecules with heating. Heating also increased asymmetric stretching splitting, indicating greater long-range Coulombic forces from increased siloxane bonding between particles. The study concludes initial sintering is driven by dehydration and surface hydroxyl condensation forming siloxane bonds between particles.
An Optimal Risk- Aware Mechanism for Countering Routing Attacks in MANETsIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Prospect of bioenergy substitution in tea industries of North East IndiaIJMER
Coal Straw
Thermal energy requirement (GJ/year) 12592 12592
Quantity required (tonnes/year) 3616 2610
Cost of fuel (Rs/tonne) 3500 1370
Total annual cost (Rs. Lakhs) 23.06 15.46
Savings (Rs. Lakhs) - 11.6
1) The document discusses the potential for substituting conventional fuels with bioenergy sources in tea processing industries in Northeast India to reduce costs and dependency on fossil fuels.
2) It analyzes the feasibility of biomass gasification, use of agricultural residues for process heating, and biodiesel production from non-ed
1) During a routine anatomy dissection, researchers observed an unusual branching pattern of the brachial artery in a male cadaver.
2) Specifically, they found that the ulnar artery originated from the lateral side of the brachial artery, rather than in the cubital fossa as is typical.
3) The variant ulnar artery descended on the lateral forearm and crossed to the medial side, following a superficial path along the arm.
Moving is a stressful process, but taking some simple steps can help make it easier. Start by decluttering your home a month in advance to determine what you want to keep, donate, or toss. Then create a detailed moving checklist and timeline to stay organized as you pack up boxes, arrange transportation, change your address, and unpack at your new home. Finally, don't forget to pack essential items separately so you have access to them during the move.
Receiver Module of Smart power monitoring and metering distribution system u...IJMER
In the current situation all the communication is very much important and faster range but
the usage of the power should be less in order to reduce the power and the usage of the sources we are
going for this data transmission through the power lines which is common and much feasible since
power line is used at all homes. In this paper we have concentrated much in the receiver module where
the receiver receives the data through the power lines through which we can know the readings of
amount of usage of power at each homes and also the power theft if it occurs anywhere.by this way we
no need to generate any particular infrastructure for transmitting an d receiving instead we can use the
power line itself.This is the work done in NLC,TAMILNADU india which is very less explained in this
paper.
1. The document discusses factors that affect rail transportation quality and safety, such as removing connections inside tunnels and on bridges to prevent damage, monitoring environmental conditions due to climate change, and controlling railway operations.
2. Key factors include protecting lines from floods and landslides, monitoring trenches and tunnel entrances/exits, coordinating with other organizations during construction, and converting at-grade crossings to grade-separated crossings.
3. The use of experienced workers and technical knowledge from other countries can help enhance safety and quality by addressing these important issues.
1. The document discusses the history and evolution of wireless communication technologies from 1G to 4G. It describes the standards and technologies that defined each generation including AM, FM, GSM, CDMA, WCDMA, LTE and WiMAX.
2. 4G is defined as providing broadband internet access with speeds up to 100 Mbps for mobile users and 1 Gbps for stationary users. Common 4G standards include LTE, WiMAX, HSPA+ and Wi-Fi.
3. 4G networks implement a 5-layer architecture including fixed, personal, hotspot, cellular and distribution layers to deliver high-speed internet access. Requirements for setting up 4G networks include the nature
Trajectory Control With MPC For A Robot Manipülatör Using ANN ModelIJMER
In this study, in a computer the dynamic motion modelling of manipulator and control of
trajectory with an algorithm this has been tested. First after dynamic motion simulation of manipulator
has been made MPC Control. The result in this study we can observe that computed torque method gives
better results than MPC methods. So in trajectory control it is approved of using computed torque
method. In last part of this study the results are estimated forward development are exemined and
suggested. The model predictive control (MPC) technique for an articulated robot with n joints is
introduced in this paper. The proposed MPC control action is conceptually different with the trajectory
robot control methods in that the control action is determined by optimising a performance index over
the time horizon. A neural network (NN) is used in this paper as the predictive model.
Hardware Unit for Edge Detection with Comparative Analysis of Different Edge ...paperpublications3
Abstract: An edge in an image is a contour across which the brightness of the image changes abruptly. In image processing, an edge is often interpreted as one class of singularities. Edge detection is an important task in image processing. It is a main tool in pattern recognition, image segmentation, and scene analysis. An edge detector is basically a high pass filter that can be applied to extract the edge points in an image. This topic has attracted many researchers and many achievements have been made. Many researchers provided different approaches based on mathematical calculations which some of them are either robust or cost effective. A new algorithm will be proposed to detect the edges of image with increased robustness and throughput. Using this algorithm we will reduce the time complexity problem which is faced by previous algorithm. We will also propose hardware unit for proposed algorithm which will reduce the area, power and speed problem. We will compare our proposed algorithm with previous approach. For image quality measurement we will use some scientific parameters those are PSNR, SSIM, FSIM. Implementation of proposed algorithm will be done by Matlab and hardware implementation will be done by using of Verilog on Xilinx 14.1 simulator. Verification will be done on Model sim.
The objective of this paper is to present the hybrid approach for edge detection. Under this technique, edge
detection is performed in two phase. In first phase, Canny Algorithm is applied for image smoothing and in
second phase neural network is to detecting actual edges. Neural network is a wonderful tool for edge
detection. As it is a non-linear network with built-in thresholding capability. Neural Network can be trained
with back propagation technique using few training patterns but the most important and difficult part is to
identify the correct and proper training set.
A Flexible Scheme for Transmission Line Fault Identification Using Image Proc...IJEEE
This paper describes a methodology that aims to find and diagnosing faults in transmission lines exploitation image process technique. The image processing techniques have been widely used to solve problem in process of all areas. In this paper, the methodology conjointly uses a digital image process Wavelet Shrinkage function to fault identification and diagnosis. In other words, the purpose is to extract the faulty image from the source with the separation and the co-ordinates of the transmission lines. The segmentation objective is the image division its set of parts and objects, which distinguishes it among others in the scene, are the key to have an improved result in identification of faults.The experimental results indicate that the proposed method provides promising results and is advantageous both in terms of PSNR and in visual quality.
Image segmentation methods for brain mri imageseSAT Journals
This document compares different edge detection methods for brain MRI images and proposes a new active contour (snake) model approach. It first describes traditional gradient-based methods like Sobel, Prewitt and Canny edge detectors, noting their limitations in medical images. It then introduces active contour models, which use energy functions to capture edges of curved objects sharply. An experiment applies different methods to a brain MRI image and compares their outputs visually and using PSNR, finding the active contour method performs best in segmenting the brain region accurately. The document concludes the active contour approach is well-suited for medical image segmentation tasks.
A NOVEL APPROACH FOR SEGMENTATION OF SECTOR SCAN SONAR IMAGES USING ADAPTIVE ...ijistjournal
The SAR and SAS images are perturbed by a multiplicative noise called speckle, due to the coherent nature of the scattering phenomenon. If the background of an image is uneven, the fixed thresholding technique is not suitable to segment an image using adaptive thresholding method. In this paper a new Adaptive thresholding method is proposed to reduce the speckle noise, preserving the structural features and textural information of Sector Scan SONAR (Sound Navigation and Ranging) images. Due to the massive proliferation of SONAR images, the proposed method is very appealing in under water environment applications. In fact it is a pre- treatment required in any SONAR images analysis system. The results obtained from the proposed method were compared quantitatively and qualitatively with the results obtained from the other speckle reduction techniques and demonstrate its higher performance for speckle reduction in the SONAR images.
AN ENHANCED BLOCK BASED EDGE DETECTION TECHNIQUE USING HYSTERESIS THRESHOLDING sipij
Edge detection is a crucial step in various image processing systems like computer vision , pattern
recognition and feature extraction. The Canny edge detection algorithm even though exhibits high
accuracy, is computationally more complex compared to other edge detection techniques. A block based
distributed edge detection technique is presented in this paper, which adaptively finds the thresholds for
edge detection depending on block type and the distribution of gradients in each block. A novel method of
computation of high threshold has been proposed in this paper. Block-based hysteresis thresholds are
computed using a non uniform gradient magnitude histogram. The algorithm exhibits remarkably high
edge detection accuracy, scalability and significantly reduced computational time. Pratt’s Figure of Merit
quantifies the accuracy of the edge detector, which showed better values than that of original Canny and
distributed Canny edge detector for benchmark dataset. The method detected all visually prominent edges
for diverse block size.
This document summarizes an analysis of iris recognition based on false acceptance rate (FAR) and false rejection rate (FRR) using the Hough transform. It first provides an overview of iris recognition and its typical stages: image acquisition, localization/segmentation, normalization, feature extraction, and pattern matching. It then describes existing methods used in each stage, including the Hough transform and rubber sheet model for localization and normalization. The proposed methodology applies Canny edge detection, Hough transform for boundary detection, normalization with the rubber sheet model, and calculates metrics like mean squared error, root mean squared error, signal-to-noise ratio, and root signal-to-noise ratio to evaluate the accuracy of iris recognition using FAR
Image Blur Detection with 2D Haar Wavelet Transform and Its Effect on Skewed ...Vladimir Kulyukin
This document presents an algorithm for image blur detection using 2D Haar wavelet transforms. The algorithm splits images into tiles and applies the 2D Haar wavelet transform to each tile to detect regions with pronounced changes. Tiles with similar changes are grouped into clusters. Images with large clusters are classified as sharp, while images with small clusters are classified as blurred. The algorithm is integrated with a skewed barcode scanning algorithm to filter out blurred images, improving scanning success rates. Experimental results found it performed comparably or better than two other blur detection algorithms and positively impacted skewed barcode scanning when integrated.
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
This document compares different first order edge detection techniques, including Canny, Sobel, Roberts, and Prewitt. It presents the methodology and steps for edge detection, including smoothing, enhancement, detection and localization. It then describes each technique in detail, providing the algorithms and edge detected images. The conclusion is that the Canny filter produces better results than the other techniques, but parameters can be adjusted for different requirements. Comparing the techniques helps evaluate their ability to detect edges in images.
Algorithm for the Comparison of Different Types of First Order Edge Detection...IOSR Journals
This document compares different first order edge detection techniques, including Canny, Sobel, Roberts, and Prewitt. It presents an algorithm to rigorously evaluate and compare the performance of these techniques. The algorithm is applied to detect edges in a sample image containing multiple objects. Simulation results show that the Canny technique produces the best edges, while the others detect weaker edges. The document concludes by discussing the ability of edge detection to simplify images by identifying boundaries and discontinuities, which is important for tasks like image analysis, pattern recognition, and computer vision.
This paper discusses techniques for digital image processing, including noise reduction, edge detection, and histogram equalization. Noise reduction techniques discussed include mean, Gaussian, and median filters to remove salt and pepper noise and Gaussian noise. Edge detection algorithms like Sobel and Laplacian are introduced to reduce image data while preserving object boundaries. Histogram equalization is used for image enhancement by spreading pixel values across the full intensity range for increased contrast. The goal is recognizing objects in images through these preprocessing steps.
NMS and Thresholding Architecture used for FPGA based Canny Edge Detector for...idescitation
In this paper, an architecture designed for Non-
Maximal Suppression used in Canny edge detection algorithm
is presented in order to reduce memory requirements
significantly. The architecture also achieves decreased latency
and increased throughput with no loss in edge detection. The
new algorithm used has a low-complexity 8-bin non-uniform
gradient magnitude histogram to compute block-based
hysteresis thresholds that are used by the Canny edge detector.
Furthermore, the hardware architecture of the proposed
algorithm is presented in this paper and the architecture is
synthesized on the Xilinx Virtex 5 FPGA. The design
development is done in VHDL and simulated results are
obtained using modelsim 6.3 with Xilinx 12.2.
IRJET- Image Feature Extraction using Hough Transformation PrincipleIRJET Journal
The document describes an image processing technique that uses Hough transformation and contour detection to extract features from images and count objects. It proposes an integrated method to detect circular objects, detach overlapping objects, and count objects of any shape. The method applies Canny edge detection, contour detection, and circular Hough transform to segment overlapping circular objects. It then uses contour detection to count all objects regardless of shape. Experimental results show the method can successfully segment and count overlapping circular and non-circular objects in test images.
Evaluate Combined Sobel-Canny Edge Detector for Image Procssingidescitation
Edge detection is one of the fundamental operation
of the computer vision to locate the sharp intensity changes to
find the edges in an image. The selection of detector depending
on the environment , especially in noisy background.In this
paper, presents a brief theory for the sobel kernel and canny
edge detector.Then propose an algorithm which combined
two detectors, the sobel detector which is widely used in digital
image processing and canny edge detector that is another
classical techniques. The design consists of three stages.Firstly
added salt & pepper noisy to the original free noisy image file
then compute the sobel detector for the file ,then apply canny
detector on the results of the second stage to filter the pixel
that signed out as an edge in the sobel detection by using
Gaussian filter. Test the algorithm by using various file which
contains salt & pepper noise with free noisy image with
different values of sigma to evaluate and specify the
performance, weakness.
ANALYSIS OF INTEREST POINTS OF CURVELET COEFFICIENTS CONTRIBUTIONS OF MICROS...sipij
This paper focuses on improved edge model based on Curvelet coefficients analysis. Curvelet transform is
a powerful tool for multiresolution representation of object with anisotropic edge. Curvelet coefficients
contributions have been analyzed using Scale Invariant Feature Transform (SIFT), commonly used to study
local structure in images. The permutation of Curvelet coefficients from original image and edges image
obtained from gradient operator is used to improve original edges. Experimental results show that this
method brings out details on edges when the decomposition scale increases.
Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. To extract important information from an MRI medical images, an efficient image segmentation or edge detection is required. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes or discontinuities occur. However, in practices, it is found rather difficult to design an edge detector that is capable of finding all the true edges in an image as there is always noise, and the subjectivity of sensitiveness in detecting the edges. Many traditional algorithms have been proposed to detect the edge, such as Canny, Sobel, Prewitt, Roberts, Zerocross, and Laplacian of Gaussian (LoG). Moreover, many researches have shown the potential of using Artificial Neural Network (ANN) for edge detection. Although many algorithms have been conducted on edge detection for medical images, however higher computational cost and subjective image quality could be further improved. Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. First, we developed features based on horizontal, vertical, and diagonal difference. Then, Canny edge detector will be used as the training output. Finally, optimized parameters will be obtained, including number of hidden layers and output threshold. The edge detection image will be analysed its quality subjectively and computational. Results showed that the proposed algorithm provided better image quality while it has faster processing time around three times time compared to other traditional algorithms, such as Sobel and Canny edge detector.
ALGORITHM AND TECHNIQUE ON VARIOUS EDGE DETECTION: A SURVEYsipij
An edge may be defined as a set of connected pixels that forms a boundary between two disjoints regions.
Edge detection is basically, a method of segmenting an image into regions of discontinuity. Edge detection
plays an important role in digital image processing and practical aspects of our life. .In this paper we
studied various edge detection techniques as Prewitt, Robert, Sobel, Marr Hildrith and Canny operators.
On comparing them we can see that canny edge detector performs better than all other edge detectors on
various aspects such as it is adaptive in nature, performs better for noisy image, gives sharp edges , low
probability of detecting false edges etc
International Journal of Engineering Research and Development (IJERD)IJERD Editor
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This document summarizes 10 important AI research papers. It begins with a brief introduction on artificial intelligence and what the papers aim to provide information on. It then lists the 10 papers with their titles:
1. A Computational Approach to Edge Detection
2. A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence
3. A Threshold Selection Method from Gray-Level Histograms
4. Deep Residual Learning for Image Recognition
5. Distinctive Image Features from Scale-Invariant Keypoints
6. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
7. Large-scale Video Classification with Convolutional Neural Networks
8. Probabilistic Reason
Similar to Mislaid character analysis using 2-dimensional discrete wavelet transform for edge refinement (20)
A Study on Translucent Concrete Product and Its Properties by Using Optical F...IJMER
- Translucent concrete is a concrete based material with light-transferring properties,
obtained due to embedded light optical elements like Optical fibers used in concrete. Light is conducted
through the concrete from one end to the other. This results into a certain light pattern on the other
surface, depending on the fiber structure. Optical fibers transmit light so effectively that there is
virtually no loss of light conducted through the fibers. This paper deals with the modeling of such
translucent or transparent concrete blocks and panel and their usage and also the advantages it brings
in the field. The main purpose is to use sunlight as a light source to reduce the power consumption of
illumination and to use the optical fiber to sense the stress of structures and also use this concrete as an
architectural purpose of the building
Developing Cost Effective Automation for Cotton Seed DelintingIJMER
A low cost automation system for removal of lint from cottonseed is to be designed and
developed. The setup consists of stainless steel drum with stirrer in which cottonseeds having lint is mixed
with concentrated sulphuric acid. So lint will get burn. This lint free cottonseed treated with lime water to
neutralize acidic nature. After water washing this cottonseeds are used for agriculter purpose
Study & Testing Of Bio-Composite Material Based On Munja FibreIJMER
The incorporation of natural fibres such as munja fiber composites has gained
increasing applications both in many areas of Engineering and Technology. The aim of this study is to
evaluate mechanical properties such as flexural and tensile properties of reinforced epoxy composites.
This is mainly due to their applicable benefits as they are light weight and offer low cost compared to
synthetic fibre composites. Munja fibres recently have been a substitute material in many weight-critical
applications in areas such as aerospace, automotive and other high demanding industrial sectors. In
this study, natural munja fibre composites and munja/fibreglass hybrid composites were fabricated by a
combination of hand lay-up and cold-press methods. A new variety in munja fibre is the present work
the main aim of the work is to extract the neat fibre and is characterized for its flexural characteristics.
The composites are fabricated by reinforcing untreated and treated fibre and are tested for their
mechanical, properties strictly as per ASTM procedures.
Hybrid Engine (Stirling Engine + IC Engine + Electric Motor)IJMER
Hybrid engine is a combination of Stirling engine, IC engine and Electric motor. All these 3 are
connected together to a single shaft. The power source of the Stirling engine will be a Solar Panel. The aim of
this is to run the automobile using a Hybrid engine
Fabrication & Characterization of Bio Composite Materials Based On Sunnhemp F...IJMER
This document summarizes research on the fabrication and characterization of bio-composite materials using sunnhemp fibre. The document discusses how sunnhemp fibre was used to reinforce an epoxy matrix through hand lay-up methods. Various mechanical properties of the bio-composites were tested, including tensile, flexural, and impact properties. The results of the mechanical tests on the bio-composite specimens are presented. Potential applications of the sunnhemp fibre bio-composites are also suggested, such as in fall ceilings, partitions, packaging, automotive interiors, and toys.
Geochemistry and Genesis of Kammatturu Iron Ores of Devagiri Formation, Sandu...IJMER
The Greenstone belts of Karnataka are enriched in BIFs in Dharwar craton, where Iron
formations are confined to the basin shelf, clearly separated from the deeper-water iron formation that
accumulated at the basin margin and flanking the marine basin. Geochemical data procured in terms of
major, trace and REE are plotted in various diagrams to interpret the genesis of BIFs. Al2O3, Fe2O3 (T),
TiO2, CaO, and SiO2 abundances and ratios show a wide variation. Ni, Co, Zr, Sc, V, Rb, Sr, U, Th,
ΣREE, La, Ce and Eu anomalies and their binary relationships indicate that wherever the terrigenous
component has increased, the concentration of elements of felsic such as Zr and Hf has gone up. Elevated
concentrations of Ni, Co and Sc are contributed by chlorite and other components characteristic of basic
volcanic debris. The data suggest that these formations were generated by chemical and clastic
sedimentary processes on a shallow shelf. During transgression, chemical precipitation took place at the
sediment-water interface, whereas at the time of regression. Iron ore formed with sedimentary structures
and textures in Kammatturu area, in a setting where the water column was oxygenated.
Experimental Investigation on Characteristic Study of the Carbon Steel C45 in...IJMER
In this paper, the mechanical characteristics of C45 medium carbon steel are investigated
under various working conditions. The main characteristic to be studied on this paper is impact toughness
of the material with different configurations and the experiment were carried out on charpy impact testing
equipment. This study reveals the ability of the material to absorb energy up to failure for various
specimen configurations under different heat treated conditions and the corresponding results were
compared with the analysis outcome
Non linear analysis of Robot Gun Support Structure using Equivalent Dynamic A...IJMER
Robot guns are being increasingly employed in automotive manufacturing to replace
risky jobs and also to increase productivity. Using a single robot for a single operation proves to be
expensive. Hence for cost optimization, multiple guns are mounted on a single robot and multiple
operations are performed. Robot Gun structure is an efficient way in which multiple welds can be done
simultaneously. However mounting several weld guns on a single structure induces a variety of
dynamic loads, especially during movement of the robot arm as it maneuvers to reach the weld
locations. The primary idea employed in this paper, is to model those dynamic loads as equivalent G
force loads in FEA. This approach will be on the conservative side, and will be saving time and
subsequently cost efficient. The approach of the paper is towards creating a standard operating
procedure when it comes to analysis of such structures, with emphasis on deploying various technical
aspects of FEA such as Non Linear Geometry, Multipoint Constraint Contact Algorithm, Multizone
meshing .
Static Analysis of Go-Kart Chassis by Analytical and Solid Works SimulationIJMER
This paper aims to do modelling, simulation and performing the static analysis of a go
kart chassis consisting of Circular beams. Modelling, simulations and analysis are performed using 3-D
modelling software i.e. Solid Works and ANSYS according to the rulebook provided by Indian Society of
New Era Engineers (ISNEE) for National Go Kart Championship (NGKC-14).The maximum deflection is
determined by performing static analysis. Computed results are then compared to analytical calculation,
where it is found that the location of maximum deflection agrees well with theoretical approximation but
varies on magnitude aspect.
In récent year various vehicle introduced in market but due to limitation in
carbon émission and BS Séries limitd speed availability vehicle in the market and causing of
environnent pollution over few year There is need to decrease dependancy on fuel vehicle.
bicycle is to be modified for optional in the future To implement new technique using change in
pedal assembly and variable speed gearbox such as planetary gear optimise speed of vehicle
with variable speed ratio.To increase the efficiency of bicycle for confortable drive and to
reduce torque appli éd on bicycle. we introduced epicyclic gear box in which transmission done
throgh Chain Drive (i.e. Sprocket )to rear wheel with help of Epicyclical gear Box to give
number of différent Speed during driving.To reduce torque requirent in the cycle with change in
the pedal mechanism
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based on the combination of, two techniques using decision tree and Association rule mining
efficiently detected probe attacks. Experimental results shows better results for detecting intrusions as
compared to others existing methods
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measures application in areas like lighting, motors, compressors, transformer, ventilation system etc.
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Investigation found that major areas of energy conservation are-
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Discrete Model of Two Predators competing for One PreyIJMER
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for different sets of parameter values. Also bifurcation diagrams are plotted to show dynamical behavior
of the system in selected range of growth parameter
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Mislaid character analysis using 2-dimensional discrete wavelet transform for edge refinement
1. www.ijmer.com
International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-3134-3136
ISSN: 2249-6645
Mislaid character analysis using 2-dimensional discrete wavelet
transform for edge refinement
Kushal Kumar1, Anamika Yadav2, Himanshi Rani3, Yashasvi Nijhawan4
1
(Electronics and Communication Engineering, Jaypee University of Engineering and Technology, India, 2013)
(Electronics and Communication Engineering, Bhagwan Parshuram Institute of Technology, GGSIPU, Delhi, India, 2012)
3
(Electronics and Communication Engineering, Vellore Institute of Technology, Chennai, India, 2015)
4
(Electronics and Communication, Jaypee University of Information Technology, Waknaghat, India, 2013)
2
ABSTRACT: Character recognition is an important tool used for many purposes limited only by imagination, some of
them being automatic number plate recognition and digital conversion of texts. In the present methods, edge detection
techniques perform well but they are time consuming and have errors if the data provided is not up to the mark. In this
paper, a novel method is proposed to minimize those errors and perform the edge detection of characters using 2dimensional wavelet transform pre-processing.
Keywords: 2-dimensional wavelets, Character recognition, Machine vision, Image processing, ANPR.
I.
INTRODUCTION
Today, many character recognition systems are used worldwide. The system works fine too in most of the cases, but
sometimes the characters on given image aredifficult to identify because of many reasons like bad lightning, or
mislaid/broken characters. In this paper, a vehicle number plate with difficult to detect characters is taken and, a novel image
processing method for detection of characters using wavelet pre-processing is proposed to segment the characters from that
image. The criterion used to compare different methods is touse the number of pixels of the characters the method could
detect with the conventional edge detection techniques to emphasize the benefit of 2D-DWT over those methods.
A series of steps in wavelet pre-processed edge detection are performed in a systematic way which detects the
characters. Edge detection is almost a prerequisite in various recognition tasks, like automatic number plate recognition,
which we have done in this paper. Edge is a boundary between two homogeneous surfaces. Fig.1 shows the text which was
used for edge detection in the proposed method and the conventional edge-detection methods (Sobel, Prewitt and Canny).
Various conventional techniques for edge detection of IC’s are available in literature[1]. Huang et al. (2011) proposes an
improved algorithm for canny edge detection. It uses an improved switch median filter algorithm instead of Gaussian filter
algorithms for filtering. [2]Somyot et al.(2012) used wavelet transforms to compress the image before edge detection.
II.
EDGE DETECTION
An edge is an abrupt change in the intensity level, which characterizes high frequency component in an image.
Noise is an unwanted signal which can cause inefficiency in edge detection.
In practice due to imperfection in image acquisition or sampling, the edges get blurred and tend to become thick.
However the derivatives play an important role in detecting the edges and locating the edge pixels in an image. The first
derivative is positive at the point of intensity variation and zero in the areas of constant intensity. The magnitude of first
derivative can be used to detect the presence of an edge. The second derivative is positive if the transition occurs on the dark
side of an edge and it is negative if transition is on the light side of an image. Hence, a second derivative can be used to
locate the edge pixels. For edge detection second derivative can also be used but its sensitivity towards noise limits its
application in edge detection. In the subsequent sections we will be discussing about the approximated first derivative
operators that are used for edge detection in the present investigation.
III.
CONVENTIONAL EDGE DETECTION METHODS
The edge detection methods used in this paper are Sobel, Prewitt and Canny, which are compared to each other and
then the best one of them is compared to the proposed algorithm. The algorithms are compared based on how much amount
of the character data can they extract from the given image. So, first we should know briefly what these methods are and
how do they work. Next, we extract the pin information from the original image as well as segmented edge-detected image
in the form of number of pin-pixels and compare which method extracts the maximum pin-information for analysis. In the
original image, the no. of pixels contained by the characters are 1882.
3.1 SOBEL
The Sobel edge detector is an approximated, first derivative two dimensional edge detector. It calculates gradient in
X and Y direction. It uses a convolutional mask to calculate the gradients as in equation (1) and gradient directions as in
equation (2). The masks are slid over the image and gradient values are calculated. In Sobel the centre coefficient of the
mask uses a weight of two, it is used so as to achieve a smoothing by giving more weightage to the central term of the mask.
The segmented image obtained by using a Sobel operator is shown in Fig.2. The number of pin-pixels detected by this
algorithm was 203.
|G|=|GX|+|GY|
(1)
-1 𝐺 𝑌
Θ=tan [ ]
(2)
𝐺𝑋
www.ijmer.com
3134 | Page
2. International Journal of Modern Engineering Research (IJMER)
www.ijmer.com
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-2719-2727
ISSN: 2249-6645
3.2 PREWITT
Prewitt edge detector is also an approximated first derivative two dimensional edge detector. It uses aconvolutional
mask to calculate the gradient in X and Y directions respectively. The segmented image obtained by using Prewitt operator is
shown in Fig.3. The number of pin-pixels detected by this algorithm was 201.
3.3 CANNY
Canny edge detection is another method of edge detection. It follows a series of steps. In the first step it eliminates
the noise from the Image by filtering the Image using Gaussian filter. In the second step it calculates the gradient and the
edge direction of the Image using Sobel edge detection. In the third step it performs non-maximum suppression. The pixels
along the edge direction which do not satisfy (3) are set to 0 or considered as non-edge pixel. Further suppression is done
using hysteresis. Hysteresis uses two thresholds. T1 and T2. If the magnitude is below the first threshold then it is set to 0
(non-edge pixel). If the magnitude is above threshold T2 then it is considered as an edge pixel. If the magnitude lies between
T1 and T2 then depending upon the path between the current pixel and the pixel with magnitude greater than T2 the pixel is
considered as an edge pixel or non-edge pixel. The segmented image obtained by using a canny edge detector is shown in
Fig.4. The number of pin-pixels detected by this algorithm was 978.
IV.
WAVELETS
Wavelets are a small portion of the wave. Wavelet transform uses wavelets to capture different frequency
components of the signal whose resolution matches up with its scale. This technique is known as multi-resolution Analysis.
It comprises of a scaling function and a wavelet function. Scaling function gives the series of approximation of the signal,
where each approximated signal differs by a factor of two. Wavelet functions are used to add the detailed information in the
difference of the two neighbouring approximations. Hence in wavelet analysis we get the approximated part and the detailed
part of the signal.
In case of Images the wavelet analysis is carried out in two dimensions. In X and Y direction respectively, the two
dimensional wavelet decomposition is shown in the form of an image in Fig. 5. It is known as filter bank analysis. It consists
of high pass and low pass filters. First the analysis is done along the columns and then along the rows. The output of the low
pass filter gives the approximated coefficients and the output of the high pass filter gives detailed coefficients. The
approximated coefficients at scale j+1 are used to construct the detailed and approximated coefficients at scale j. In case of
two dimensions we get three sets of detailed coefficients (rest three squares) and one set of approximated coefficient (upper
left square).
V.
PROPOSED METHOD
In the proposed method, we have first subjected the image to a 2-Dimensional discrete wavelet transform (2-D
DWT). Doing this, we get a set of 4 images, one is the set of approximated coefficients and the other three are set of detailed
coefficients. We ignore the approximated coefficient and reconstruct the image using the set of detailed coefficients, i.e. we
take inverse 2-D DWT. The image is now ready to be edge-detected using any conventional algorithm like Canny in this
case. So, we choose the best one of the conventional methods, which comes out to be Canny and then compare it with our
proposed method in Fig. 6. The number of pin-pixels detected by this algorithm was 5636, i.e. 84.25% of the pin-information
is accurately extracted.
VI.
Fig.1 Original IC image.
detected image.
Fig.3 Pin segmentation on Prewitt edgedetected image
FIGURES
Fig.2Character segmentation on Sobel edge-
Fig.4
www.ijmer.com
Character
segmentation
edge-detected image.
on
Canny
3135 | Page
3. www.ijmer.com
International Journal of Modern Engineering Research (IJMER)
Vol. 3, Issue. 5, Sep - Oct. 2013 pp-2719-2727
ISSN: 2249-6645
Fig.5 2-D DWT illustration.
Fig.6 Pin segmentation on Wavelet preprocessed Canny edge-detected image.
VII.
CONCLUSION
Based on the results the following inferences can be made. When wavelet pre-processing was not performed, canny
edge detection, Fig.4 was found to be the most efficient method followed by Sobel, Fig.2 and Prewitt, Fig.3, which are pretty
close to each other. When wavelet pre-processing was used, the results obtained are as shown in Fig. 6 which arefar more
accurate than the results obtained without using wavelet pre-processing as in Fig. 2, 3 and 4. The proposed method detects
over 50% of the pixels while the conventional methods could detect only about 10%. On using wavelet pre-processing the
low frequency component of the image was removed and high frequency components were retained during reconstruction.
The edges which comprises of high frequencies were efficiently detected. Thus the choice of using wavelet pre-processing
made edge detection more efficient. Better and efficient extraction of IC pin information was achieved.
Many sectors could benefit from this approach, like the traffic regulation sector or the handwriting analysis sector. The
number of man-hours will be greatly reduced and the results would be more accurate than any of the current methods. This
method could be implemented over existing hardware.
ACKNOWLEDGMENTS
I, Kushal Kumar, would like to thank Dr. Sudha Radhika who was an inspiration for me to take up this project.
REFERENCES
[1]
[2]
[3]
[4]
[5]
Ying Huang, Qi Pan,Qi Liu,XinPeng He,Yun Feng Liu,Yong Quan Yu, “Application of Improved Canny Algorithm on the IC
Chip pin Inspection”,Advanced Materials Research Vols. 317-319 (2011) pp 854-858.
K. Somyot, S. Anakapon and K. Anantawat, “Pattern recognition technique for IC pins inspection using wavelet transform with
chain code discrete Fourier Transform and signal correlation”, International Journal of Physical Sciences, Vol.7 (9), pp. 1326-1332,
23 February 2012.
Tim Edwards, “Discrete Wavelet Transform: Implementation and theory”, Stanford University, September 1991.
Rafael C. Gonzalez, Richard E. Woods Digital Image Processing (ISBN-13: 978-0131687288,3rdEdition, 2007)
Barroso, J. ; Seccao de Engenharias, Dagless, E.L. ; Rafael, A. ; Bulas-Cruz, J., “Number plate reading using computer vision”,
ISIE '97., Proceedings of the IEEE International Symposium on Industrial Electronics, 1997.
www.ijmer.com
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