IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
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.
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.
Face recognition using selected topographical features IJECEIAES
This paper represents a new features selection method to improve an existed feature type. Topographical (TGH) features provide large set of features by assigning each image pixel to the related feature depending on image gradient and Hessian matrix. Such type of features was handled by a proposed features selection method. A face recognition feature selector (FRFS) method is presented to inspect TGH features. FRFS depends in its main concept on linear discriminant analysis (LDA) technique, which is used in evaluating features efficiency. FRFS studies feature behavior over a dataset of images to determine the level of its performance. At the end, each feature is assigned to its related level of performance with different levels of performance over the whole image. Depending on a chosen threshold, the highest set of features is selected to be classified by SVM classifier.
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
The automatic license plate recognition(alpr)eSAT Journals
Abstract Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO). In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many attributes like illumination, blur, background color, foreground color etc. will pose a problem. Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
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.
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.
Face recognition using selected topographical features IJECEIAES
This paper represents a new features selection method to improve an existed feature type. Topographical (TGH) features provide large set of features by assigning each image pixel to the related feature depending on image gradient and Hessian matrix. Such type of features was handled by a proposed features selection method. A face recognition feature selector (FRFS) method is presented to inspect TGH features. FRFS depends in its main concept on linear discriminant analysis (LDA) technique, which is used in evaluating features efficiency. FRFS studies feature behavior over a dataset of images to determine the level of its performance. At the end, each feature is assigned to its related level of performance with different levels of performance over the whole image. Depending on a chosen threshold, the highest set of features is selected to be classified by SVM classifier.
License Plate Recognition using Morphological Operation. Amitava Choudhury
This paper describes an efficient technique of locating and
extracting license plate and recognizing each segmented
character. The proposed model can be subdivided into four
parts- Digitization of image, Edge Detection, Separation of
characters and Template Matching. In this work, we propose a
method which is based on morphological operations where
different Structuring Elements (SE) are used to maximally
eliminate non-plate region and enhance plate region.
Character segmentation is done using Connected Component
Analysis. Correlation based template matching technique is
used for recognition of characters. This system is
implemented using MATLAB7.4.0. The proposed system is
mainly applicable to Indian License Plates.
Vehicle logo recognition using histograms of oriented gradient descriptor and...TELKOMNIKA JOURNAL
Most of vehicle have the similar structures and designs. It is extremely complicated and difficult to identify and classify vehicle brands based on their structure and shape. As we requirea quick and reliable response, so vehicle logos are an alternative method of determining the type of a vehicle. In this paper, we propose a method for vehicle logo recognition based on feature selection method in a hybrid way. Vehicle logo images are first characterized by histograms of oriented gradient descriptors and the final features vector are then applied feature selection method to reduce the irrelevant information. Moreover, we release a new benchmark dataset for vehicle logo recognition and retrieval task namely, VLR-40. The experimental results are evaluated on this database which show the efficiency of the proposed approach.
Vehicle License Plate Recognition (VLPR) is an important system for harmonious traffic. Moreover this system is helpful in many fields and places as private and public entrances, parking lots, border control and theft control. This paper presents a new framework for Sudanese VLPR system. The proposed framework uses Multi Objective Particle Swarm Optimization (MOPSO) and Connected Component Analysis (CCA) to extract the license plate. Horizontal and vertical projection will be used for character segmentation and the final recognition stage is based on the Artificial Immune System (AIS). A new dataset that contains samples for the current shape of Sudanese license plates will be used for training and testing the proposes framework.
Bangla Optical Digits Recognition using Edge Detection MethodIOSR Journals
Abstract:This paper is based on Bangla Optical Digit Recognition (ODR) by the Edge detection technique. In this method, Bangla digit image converted into gray-scale which distributed by an M by N array form. Here input data are considered off-line printed digit’s image which collected from computer generated image, scanned documents or printed text. After addressing the gray-scale image against a variable in the form of an M by N array, where the value of array pointers are shown 255 for total white space, 0 (zero) for total dark space and value between 255 and 0 for mix of white and dark space of the image. At the next process, four edgestouch points as well as each touch point’s ratio use as parameters to determine each Bangla digit uniquely. Keywords-Edge, image,gray-scale, Matrix,ODR.
An Efficient Model to Identify A Vehicle by Recognizing the Alphanumeric Char...IJMTST Journal
Automatic Engine Number Recognition (AENR) is the digital image processing and an important aspect/role to identify the theft vehicles by recognizing characters, digits and special symbols. There is increase in the theft of vehicles, so to identify these theft vehicles, the proposed system is introduced. The proposed system controls the theft vehicles by recognizing a digits and characters in the number plate and chassis region and stores in the database in ASCII format to check the theft vehicles are registered or unregistered. Both system consists of 4 common phases: - Preprocessing, Character Extraction (ROI), Character Segmentation, and Character Recognition. This paper proposes a new scheme for engine number and chassis number extraction from the pre-processed image of the vehicle’s engine and chassis region using preprocess techniques, Region of Interest(ROI), Binarization, thresholding, template matching.
The Framework of Image Recognition based on Modified Freeman Chain CodeCSCJournals
Image recognition of line drawing involves feature extraction and feature comparison. Works on the extraction required the representation of the image to be compared. Combining these two requirements, a framework that develops a new extraction algorithm of a chain code representation is presented. In addition, new corner detection is presented as pre-processing to the line drawing input in order to derive the chain code. This paper presents a new framework that consist of five steps namely pre-processing and image processing, new corner detection algorithm, chain code generator, feature extraction algorithm, and recognition process. Heuristic approach that is applied in the corner detection algorithm accepts input of thinned binary image and produce a modified thinned binary image consisted of J character to represent corners in the image. Using the modified thinned binary image, a new chain code scheme that is based on Freeman chain code is proposed and an algorithm is developed to generate a single chain code series that is representing the line drawing input. The feature extraction algorithm is then extracting the three pre-defined features of the chain code for recognition purpose. The features are corner properties, distance between corners, and angle from a corner to the connected corner. The explanation of steps in the framework is supported with two line drawings. The results show that the framework successfully recognizes line drawing into five categories namely not similar line drawing, and four other categories that are similar but with attributes of rotation angle and scaling ratio.
Robotic navigation algorithm with machine vision IJECEIAES
In the field of robotics, it is essential to know the work area in which the agent is going to develop, for that reason, different methods of mapping and spatial location have been developed for different applications. In this article, a machine vision algorithm is proposed, which is responsible for identifying objects of interest within a work area and determining the polar coordinates to which they are related to the observer, applicable either with a fixed camera or in a mobile agent such as the one presented in this document. The developed algorithm was evaluated in two situations, determining the position of six objects in total around the mobile agent. These results were compared with the real position of each of the objects, reaching a high level of accuracy with an average error of 1.3271% in the distance and 2.8998% in the angle.
Traffic sign detection via graph based ranking and segmentationPREMSAI CHEEDELLA
The majority of the existing traffic sign detection system use shape information, but the methods of remain limited in regard to detecting and segmenting traffic signs from a complex background.
Facial Expression Recognition Using SVM Classifierijeei-iaes
Facial feature tracking and facial actions recognition from image sequence attracted great attention in computer vision field. Computational facial expression analysis is a challenging research topic in computer vision. It is required by many applications such as human-computer interaction, computer graphic animation and automatic facial expression recognition. In recent years, plenty of computer vision techniques have been developed to track or recognize the facial activities in three levels. First, in the bottom level, facial feature tracking, which usually detects and tracks prominent landmarks surrounding facial components (i.e., mouth, eyebrow, etc), captures the detailed face shape information; Second, facial actions recognition, i.e., recognize facial action units (AUs) defined in FACS, try to recognize some meaningful facial activities (i.e., lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize some meaningful facial activities (i.e., lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize facial expressions that represent the human emotion states. In this proposed algorithm initially detecting eye and mouth, features of eye and mouth are extracted using Gabor filter, (Local Binary Pattern) LBP and PCA is used to reduce the dimensions of the features. Finally SVM is used to classification of expression and facial action units.
License Plate Recognition using Morphological Operation. Amitava Choudhury
This paper describes an efficient technique of locating and
extracting license plate and recognizing each segmented
character. The proposed model can be subdivided into four
parts- Digitization of image, Edge Detection, Separation of
characters and Template Matching. In this work, we propose a
method which is based on morphological operations where
different Structuring Elements (SE) are used to maximally
eliminate non-plate region and enhance plate region.
Character segmentation is done using Connected Component
Analysis. Correlation based template matching technique is
used for recognition of characters. This system is
implemented using MATLAB7.4.0. The proposed system is
mainly applicable to Indian License Plates.
Vehicle logo recognition using histograms of oriented gradient descriptor and...TELKOMNIKA JOURNAL
Most of vehicle have the similar structures and designs. It is extremely complicated and difficult to identify and classify vehicle brands based on their structure and shape. As we requirea quick and reliable response, so vehicle logos are an alternative method of determining the type of a vehicle. In this paper, we propose a method for vehicle logo recognition based on feature selection method in a hybrid way. Vehicle logo images are first characterized by histograms of oriented gradient descriptors and the final features vector are then applied feature selection method to reduce the irrelevant information. Moreover, we release a new benchmark dataset for vehicle logo recognition and retrieval task namely, VLR-40. The experimental results are evaluated on this database which show the efficiency of the proposed approach.
Vehicle License Plate Recognition (VLPR) is an important system for harmonious traffic. Moreover this system is helpful in many fields and places as private and public entrances, parking lots, border control and theft control. This paper presents a new framework for Sudanese VLPR system. The proposed framework uses Multi Objective Particle Swarm Optimization (MOPSO) and Connected Component Analysis (CCA) to extract the license plate. Horizontal and vertical projection will be used for character segmentation and the final recognition stage is based on the Artificial Immune System (AIS). A new dataset that contains samples for the current shape of Sudanese license plates will be used for training and testing the proposes framework.
Bangla Optical Digits Recognition using Edge Detection MethodIOSR Journals
Abstract:This paper is based on Bangla Optical Digit Recognition (ODR) by the Edge detection technique. In this method, Bangla digit image converted into gray-scale which distributed by an M by N array form. Here input data are considered off-line printed digit’s image which collected from computer generated image, scanned documents or printed text. After addressing the gray-scale image against a variable in the form of an M by N array, where the value of array pointers are shown 255 for total white space, 0 (zero) for total dark space and value between 255 and 0 for mix of white and dark space of the image. At the next process, four edgestouch points as well as each touch point’s ratio use as parameters to determine each Bangla digit uniquely. Keywords-Edge, image,gray-scale, Matrix,ODR.
An Efficient Model to Identify A Vehicle by Recognizing the Alphanumeric Char...IJMTST Journal
Automatic Engine Number Recognition (AENR) is the digital image processing and an important aspect/role to identify the theft vehicles by recognizing characters, digits and special symbols. There is increase in the theft of vehicles, so to identify these theft vehicles, the proposed system is introduced. The proposed system controls the theft vehicles by recognizing a digits and characters in the number plate and chassis region and stores in the database in ASCII format to check the theft vehicles are registered or unregistered. Both system consists of 4 common phases: - Preprocessing, Character Extraction (ROI), Character Segmentation, and Character Recognition. This paper proposes a new scheme for engine number and chassis number extraction from the pre-processed image of the vehicle’s engine and chassis region using preprocess techniques, Region of Interest(ROI), Binarization, thresholding, template matching.
The Framework of Image Recognition based on Modified Freeman Chain CodeCSCJournals
Image recognition of line drawing involves feature extraction and feature comparison. Works on the extraction required the representation of the image to be compared. Combining these two requirements, a framework that develops a new extraction algorithm of a chain code representation is presented. In addition, new corner detection is presented as pre-processing to the line drawing input in order to derive the chain code. This paper presents a new framework that consist of five steps namely pre-processing and image processing, new corner detection algorithm, chain code generator, feature extraction algorithm, and recognition process. Heuristic approach that is applied in the corner detection algorithm accepts input of thinned binary image and produce a modified thinned binary image consisted of J character to represent corners in the image. Using the modified thinned binary image, a new chain code scheme that is based on Freeman chain code is proposed and an algorithm is developed to generate a single chain code series that is representing the line drawing input. The feature extraction algorithm is then extracting the three pre-defined features of the chain code for recognition purpose. The features are corner properties, distance between corners, and angle from a corner to the connected corner. The explanation of steps in the framework is supported with two line drawings. The results show that the framework successfully recognizes line drawing into five categories namely not similar line drawing, and four other categories that are similar but with attributes of rotation angle and scaling ratio.
Robotic navigation algorithm with machine vision IJECEIAES
In the field of robotics, it is essential to know the work area in which the agent is going to develop, for that reason, different methods of mapping and spatial location have been developed for different applications. In this article, a machine vision algorithm is proposed, which is responsible for identifying objects of interest within a work area and determining the polar coordinates to which they are related to the observer, applicable either with a fixed camera or in a mobile agent such as the one presented in this document. The developed algorithm was evaluated in two situations, determining the position of six objects in total around the mobile agent. These results were compared with the real position of each of the objects, reaching a high level of accuracy with an average error of 1.3271% in the distance and 2.8998% in the angle.
Traffic sign detection via graph based ranking and segmentationPREMSAI CHEEDELLA
The majority of the existing traffic sign detection system use shape information, but the methods of remain limited in regard to detecting and segmenting traffic signs from a complex background.
Facial Expression Recognition Using SVM Classifierijeei-iaes
Facial feature tracking and facial actions recognition from image sequence attracted great attention in computer vision field. Computational facial expression analysis is a challenging research topic in computer vision. It is required by many applications such as human-computer interaction, computer graphic animation and automatic facial expression recognition. In recent years, plenty of computer vision techniques have been developed to track or recognize the facial activities in three levels. First, in the bottom level, facial feature tracking, which usually detects and tracks prominent landmarks surrounding facial components (i.e., mouth, eyebrow, etc), captures the detailed face shape information; Second, facial actions recognition, i.e., recognize facial action units (AUs) defined in FACS, try to recognize some meaningful facial activities (i.e., lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize some meaningful facial activities (i.e., lid tightener, eyebrow raiser, etc); In the top level, facial expression analysis attempts to recognize facial expressions that represent the human emotion states. In this proposed algorithm initially detecting eye and mouth, features of eye and mouth are extracted using Gabor filter, (Local Binary Pattern) LBP and PCA is used to reduce the dimensions of the features. Finally SVM is used to classification of expression and facial action units.
Fault model analysis by parasitic extraction method for embedded srameSAT 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
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.
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
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
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.
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
Study of characterization of (peo+kclo4) polymer electrolyte systemeSAT 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
Dispersion modeling of nitrous oxide emissions from a nitric acid plant in de...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 and implementation of an ancrchitecture of embedded web server for wir...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.
Analysis of multi hop relay algorithm for efficient broadcasting in manetseSAT 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
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.
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
Performance analysis of cmos comparator and cntfet comparator designeSAT 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
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.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
The review on automatic license plate recognition (alpr)eSAT Journals
Abstract
Abstract explanation should be Times New Roman, Font Size 10, Single line spacing, Italic, Text alignment should be justify, should
contain at least 250 words. Abstract explanation should be Times New Roman, Font Size 10, Single line spacing, Italic, Text
alignment should be justify, should contain at least 250 words. Abstract explanation should be Times New Roman, Font Size 10,
Single line spacing, Italic, Text alignment should be justify, should contain at least 250 words. Abstract explanation should be Times
New Roman, Font Size 10, Single line spacing, Italic, Text alignment should be justify, should contain at least 250 words. Abstract
explanation should be Times New Roman, Font Size 10, Single line spacing, Italic, Text alignment should be justify, should contain at
least 250 words. Abstract explanation should be Times New Roman, Font Size 10, Single line spacing, Italic, Text alignment should be
justify, should contain at least 250 words.
Keywords: Key word1, Key word2, Key word3, and Key word4 etc…
The review on automatic license plate recognition (alpr)eSAT Journals
Abstract
Nowadays vehicles play a very big role in transportation. Also the use of vehicles has been increasing because of population growth
and human needs in recent years. Therefore, control of vehicles is becoming a big problem and much more difficult to solve . The
presence of noise, blurring in the image, uneven illumination, dim light and foggy conditions make the task even more difficult.
Nowadays, intelligent transportation systems (ITSs) have a significant impact on people’s lives. ITSs include intelligent infrastructure
systems and intelligent vehicle systems. In the current information technology era, the use of automations and intelligent systems is
becoming more and more widespread. Automatic license plate recognition (ALPR) has turned out to be an important research issue.
ALPR has many applications in traffic monitoring system, including controlling the traffic volume, ticketing vehicles without the
human control, vehicle tracking, policing, security, and so on. In this paper categorize different ALPR techniques according to the
features they used for each stage, and compare them in terms of pros, cons, recognition accuracy and processing speed.
Index Terms: Automatic license plate recognition (ALPR) system, literature review, reference
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.
Vhdl implementation for edge detection using log gabor filter for disease det...eSAT Journals
Abstract Edge detection is first and essential step in the field of image processing. Detected edges play a very important role such as image enhancement, object detection, focus area selection and many more. In medical application like tonsillitis, tumor, fracture can be detected in its early stage by detecting edges of disease. There are different and many ways for edge detection, However, the most may be grouped into three categories, first order gradient, second order and optimal edge detection.. Sobel edge detection is gradient based edge detection method used for finding edges of image. Also Sobel edge detection method provide one more advantage that it having better noise sensitivity as compared to other edge detection method. Here new concept Log-Gabor filter is used for best contrast ridges, efficient noise reduction and improved edges of an images. Most image processing tools such LabVIEW are not suited for strong real-time constraints, so to overcome this problem hardware implementation FPGA used. Proposed model for disease detection is design in LabVIEW platform with NI Vision Assistant tool 14.0 . Keywords: Edge Detection, Sobel Operator, Log-Gabor Filter, Labview 14.0.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
License plate recognition for toll payment applicationeSAT Journals
Abstract Automatic License Plate Recognition (ALPR) is the method for the extraction of vehicle license plate information from images. It can be used on various applications such as Pay-Per -Use roads (Electronic Toll Collection), Parking lots and arterial traffic conditions monitoring. Automatic License Plate Recognition uses infrared cameras to capture images under varied lighting and weather conditions. The objective of this paper is to implement K-Means Clustering Algorithm for License plate extraction & Maximally stable extreme region for license plate segmentation , Template matching method for license plate recognition & also payment in toll plaza and parking lots automatically by detecting the number plates of vehicles which in turn reduce the traffic and consumption of time in toll stations. Keywords: Automatic License Plate Recognition (ALPR), Maximally Stable Extreme Region (MSER), Template matching, and Character Recognition
Smart License Plate Recognition System based on Image Processingijsrd.com
This report describes the Smart License Plate Reorganization System, which can be installed into a tollbooth for automated acceptation of vehicle license plate details using an image of a vehicle. This Smart License Plate Reorganization system could then be implemented to control the payment of fees, highways, bridges, parking areas or tunnels, etc. This report contains new algorithm for acceptation number plate using Structural operation, Thresholding operation, Edge detection, Bounding box analysis for number plate extraction, character separation using separation and character acceptation using Template method and Feature extraction.
IRJET-Analysis of Face Recognition System for Different ClassifierIRJET Journal
M.Manimozhi, A. John Dhanaseely "Analysis of Face Recognition System for Different Classifier ", International Research Journal of Engineering and Technology (IRJET), Volume2,issue-01 April 2015.e-ISSN:2395-0056, p-ISSN:2395-0072. www.irjet.net .published by Fast Track Publications
Abstract
Face recognition plays vital role for authenticating system. Human Face recognition is a challenging task in computer vision and pattern recognition. Face recognition has attracted much attention due to its potential value in security and law enforcement applications and its theoretical challenges. Different methods are used for feature extraction and classification. Kernel fisher analysis is used for feature extraction. The performance analysis for Euclidean, support vector machine is evaluated. The whole process is done using MATLAB software. A set of 10 person real time images is taken for our work. The classifier recognizes the similar posture as an output.
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.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Use of horizontal and vertical edge processing technique to improve number pl...eSAT Journals
Abstract
Automatic Number Plate Recognition (ANPR) is a bulk investigation system that catches the image of vehicles and identifies their
license number. ANPR may be supported in the finding of taken vehicles. The recognition of taken vehicles may be done in an
effective means by means of the ANPR systems situated on the highways. This paper proposes a recognition technique in which
the vehicle plate image is found by the digital cameras and the image is processed to acquire the number plate data. A back image
of a vehicle is taken and administered using numerous algorithms.
Key Words: Image Processing, Histogram, Skew Correction, Segmentation
Abstract
Field of image processing has vast applications in medical, forensic, research etc., It includes various domains like enhancement,
classification, segmentation, etc., which are widely used for these applications. Image Enhancement is the pre processing step on
which the accuracy of the result lies. Image enhancement aims to improve the visual appearance of an image, without affecting
the original attributes (i.e.,) image contrast is adjusted and noise is removed to produce better quality image. Hence image
enhancement is one of the most important tasks in image processing. Enhancement is classified into two categories spatial domain
enhancement and frequency domain enhancement. Spatial domain enhancement acts upon pixel value whereas frequency domain
enhancement acts on the Fourier transform of the image. The enhancement techniques to be used depend on modality, climatic
and visual perspective etc., In this paper, we present a survey on various existing image enhancement techniques.
Keywords: Enhancement, Spatial domain enhancement, Frequency domain enhancement, Contrast, Modality.
DIGITAL RESTORATION OF TORN FILMS USING FILTERING T ECHNIQUESAM Publications
The acceptance of digital imaging is motivating many photography enthusiasts to transfer their
photographic archive to digital form. Scans of negatives and positives are preferred to be scanned at high resolution
which makes small cracks and scratches very apparent. These unsightly defects have become an important issue
for consumers. Filtering techniques are used for the restoration process which is fully automatic whereas the existing
systems were semi-automatic or completely manual. The method used for the detection of tear is dilation process and
top-hat transform. Top-hat transform might misinterpret dark brush strokes as cracks. In order to avoid these
unwanted alterations to the original image, brush strokes are separated from the actual cracks using clustering
technique. Tear removal includes order statistics filtering which deals with the reconstruction of missing or
damaged image areas.
Tracking number plate from vehicle usingijfcstjournal
In Traffic surveillance, Tracking of the number plate from the vehicle is an important task, which demands
intelligent solution. In this document, extraction and Recognization of number plate from vehicles image
has been done using Matlab. It is assumed that images of the vehicle have been captured from Digital
Camera. Alphanumeric Characters on plate has been Extracted and recognized using template images of
alphanumeric characters.
This paper presents a new algorithm in MATLAB which has been used to extract the number plate from the
vehicle in various luminance conditions. Extracted image of the number plate can be seen in a text file for
verification purpose. Number plate identification is helpful in finding stolen cars, car parking management
system and identification of vehicle in traffic.
An expanded haar wavelet transform and morphological deal based approach for ...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
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
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Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
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THE AUTOMATIC LICENSE PLATE RECOGNITION(ALPR)
Rinku Solanki1
, Rajeshkumar Rai2
, Teena Raikwar3
1
M.tech student, digital communication, NRI-IST, Bhopal, Madhya Pradesh, India,
2
Assistant professor, Professor, Head of the department of E.C, NIIST, Bhopal, Madhya Pradesh, India
3 Assistant professor, electronica & communication dept., (NRI-IST, Bhopal), Madhya Pradesh, India
rinkusolanki86@gmail.com, raj.rai1008@gmail.com, t_raikwar.2006@yahoo.co.in
Abstract
Every country uses their own way of designing and allocating number plates to their country vehicles. This license number plate is
then used by various government offices for their respective regular administrative task like- traffic police tracking the people who are
violating the traffic rules, to identify the theft cars, in toll collection and parking allocation management etc. In India all motorized
vehicle are assigned unique numbers. These numbers are assigned to the vehicles by district-level Regional Transport Office (RTO).
In India the license plates must be kept in both front and back of the vehicle. These plates in general are easily readable by human due
to their high level of intelligence on the contrary; it becomes an extremely difficult task for the computers to do the same. Many
attributes like illumination, blur, background color, foreground color etc. will pose a problem.
Index Terms: Automatic license plate recognition (ALPR) system, proposed methodology, reference
-----------------------------------------------------------------------***-----------------------------------------------------------------------
1. INTRODUCTION
The purpose of this paper is to provide researchers a systematic
survey of existing ALPR research by categorizing existing
methods according to the features they used, by analyzing the
pros/cons of these features, and by comparing them in terms of
recognition performance and processing speed, and to open
some issues for the future research.
Basic block diagram of the ALPR system is shown in fig 1.for
above steps different techniques used by different author which
are studied in literature review. An example of the number
plate extraction is given .by this figure block diagram is easily
understand, in this figure all steps of block diagram is shown
by indicating number A, B, C, D.
Automatic license plate recognition (ALPR) applies image
processing and character recognition technology to identify
vehicles by automatically reading their number plates.and this
system mainly devide in three steps:all ateps are better explain
in proposed methodology.
FIGURE (1) BASIC BLOCKDIAGRAM OF ALPR
SYSTEM
The variations of the plate types or environments cause
challenges in the detection and recognition of license plates.
They are summarized as follows:
1) Location: Plates exist in different locations of an image.
2) Quantity: An image may contain no or many plates.
3) Size: Plates may have different sizes due to the camera
distance and the zoom factor.
4) Color: Plates may have various characters and
background colors due to different plate types or capturing
devices.
5) Font: Plates of different nations may be written in
different fonts and language.
6) Occlusion: Plates may be obscured by dirt.
7) Inclination: Plates may be tilted.
8) Other: In addition to characters, a plate may contain
frames and screws.
Environment variations:
1) Illumination: Input images may have different types of
illumination, mainly due to environmental lighting and
vehicle headlights.
2) Background: The image background may contain
patterns similar to plates, such as numbers stamped on a
vehicle, bumper with vertical patterns, and textured floors.
2. PROPOSEDMETHODOLOGY
Vehicle license plate (VLP) constitutes an unambiguous
identifier of a vehicle participating in road traffic. Reading a
license plate is the first step in determining the identities of
parties involved in traffic incidents. An efficient automatic
license plate recognition process may become the core of fully
2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 02 Issue: 08 | Aug-2013, Available @ http://www.ijret.org 354
computerized road traffic monitoring systems, electronic fee
collection solutions, surveillance devices and safety
supervision systems. It is important that the recognition
accuracy of such a process is very high. Tracking and
registering dangerous behavior in traffic may be used for
prosecuting offenders.
License-Plate Recognition System consists of three
main modules:
(1) License plate detection
(2) Character segmentation
(3)Character Recognition (CR)
Step(1)image acquisition, in image acquisition explained that
from where images are acquire Image can be input to the
system by different methods by analog camera,or by digital
cameras, but nowadays digital technology has their advantages
so better input method is by digital cameras or by direct digital
photos.
2.1 License Plate Detection
by whole capturing image we having license plate covered by
background of vehicle body,so by this step only plate are is
extracted from whole body. our task now is to identify the
region containing the license plate. In this experiment, two
features are defined and extracted in order to decide if a
candidate region contains a license plate or not , these features
are
2.1.1 Preprocessing
Since we have assumed that the license plate has a yellow
background, the first step is to identify the regions in the image
that contain the intensity of RGB corresponding to the color
yellow. We Filter the yellow colored part from the image using
values obtained by experiments on the 10 sample images. (i) -
(a< R< b) && (p< G< q) && (x< B< y) Where R is the
intensity of the color Red , G of Green and B that of
Blue.Based on this condition we obtain a Binary Image. We
change yellow to white and non-yellow to black.
2.1.2 Morphological Operations:
These are Non-linear filters, with the function of restraining
noises, extracting features and segmenting images etc The
following morphological operations have been used
Fill (MATLAB function – imfill): fills holes in the binary
image. A hole is a set of background pixels that cannot be
reached by filling in the background from the edge of the
image.
Open (MATLAB function – imopen): performs morphological
opening on the grayscale or binary image with the pre-defined
structuring element.
Dilate (MATLAB function – imdilate): dilates the grayscale,
binary, or packed binary image returning the dilated image
(I)On applying these morphological operations on „im1.jpg‟
we obtain the Image.
2.1.3 Horizontal Segmentation
Once the Preprocessing is over, the next step is to segment the
license plate candidates from the image. We first do a
horizontal segmentation of the image using the histogram
method.
Steps:
For this we calculate the horizontal and vertical projections of
intensity. Then we find the mean of the local minimas of
horizontal projection plot .Based on the threshold calculated
from the above local minimas, we find x locations of the
segmented regions. In order to locate the right and left edges of
License plate from candidate region, the vertical projection
after mathematical morphology deal is changed into binary
image. The arithmetic for doing this is:
TfLf TTT ≥= 1)( TfLf TTT <= 0)(
Where fT (1,i) is the vertical projection after mathematical
morphology, T is the threshold. Then scan the function of fT
(1,i) and register the portions where values change from 0 to 1
and from 1 to 0 in stack1 and stack2 respectively. So the
candidate position of the left and right edge of the license plate
are in stack1 (1,i) and stack2(1,i) respectively, and the
candidate’s width of the license plate is calculated by: width(1,
i) stack2(1, i) - stack1(1, i) respectively. So the candidate
position of the left and right edge of the license plate are in
stack1 (1,i) and stack2(1,i) respectively, and the candidate’s
width of the license plate is calculated by: width(1, i) stack2(1,
i) - stack1(1, i) These give the x coordinates of the potentially
candidates regions
2.1.4 Getting Potential Candidates
After getting the horizontal segments of the candidate regions,
we would now want to get the vertical coordinates, in order to
extract the exact area from the image For each of the horizontal
segments, in order find the vertical location, we once again use
the vertical projections of intensity. Then converting to a
binary image using the threshold as discussed in the previous
section we get the desired vertical coordinates. Now we have
all our candidate regions. An candidate regions obtained from
our sample image „im1.jpg‟ are :
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Volume: 02 Issue: 08 | Aug-2013, Available @ http://www.ijret.org 355
Figure (2) Candidate regions
2.1.5 Identifying the License Plate:
Out of the many candidate regions that we have obtained from
the so far mentioned procedure, our task now is to identify the
region containing the license plate. In this experiment, two
features are defined and extracted in order to decide if a
candidate region contains a license plate or not , these features
are
1. Aspect ratio
2. Edge Density
Even though these features are not scale-invariant, luminance-
invariant, rotation-invariant, but they are insensitive to many
environment changes.
Aspect ratio
The aspect ratio is defined as the ratio of the width to the height
of the region.
Aspect Ratio = width/height
Since the minimum enclosing rectangle(MER) of the object
region can be computed via rotating the region in previous
section, the dimension of the object‟s MER can be taken as the
width and the height of the region.
Edge density
Applying the above feature to filter the segmented regions, a
lot of nonlicense plate regions can be removed. However, there
are still many candidate regions left which take similar
rectangularity and aspect ratio features as the license plate
regions do, such as often the head lights. Considering that the
license plate regions generally take higher local variance in its
pixels‟ values due to the presence of characters, an important
feature to describe license plate region is local variance, which
is quantized using the edge density. The edge density is
measured in a region R by averaging the intensities of all edge
pixels within the region as
∑∈
=
Rnm
D
nmE
NR
R ,
1 ),(
Where E(i,j) represents the edge magnitude at location (i,j), and
NR is the number of pixels in region R. License plate Sets used
for training to calculate aspect ratio and edge density: We used
24 license plates as training data. They are contained in the
directory named
“edge_density_and_aspect_ratio_training_images”.
After performing this experiment, we found the average values
of the above mentioned features as follow:
Aspect ratio = 4.4912 edge density = 0.1359
On using the above mentioned features we are able to drop the
incorrect regions and get the final result as the extracted license
plate from the input image.
For the candidate images shown above, above tests rules out
the first candidate and gives the following output –
Figure (3) Number Plate
2.2 SEGMENTATION
This step characters on license plate are segmented and
identify. This step is the most important step in license plate
recognition because all further steps rely on it. This is the
second major part of the License Plate detection algorithm.
There are many factors that cause the character segmentation
task difficult, such as image noise, plate frame, rivet, space
mark, plate rotation and illumination variance. We here
propose the algorithm that is quite robust and gives
significantly good results on images having the above
mentioned problems for the segmentation preprocessing is
required by conversion to gray scale and binarization. Different
algorithms are used for segmentation which are explained
further later in literature review.
In the segmentation of plate characters, license plate is
segmented into its constituent parts obtaining the characters
individually. Firstly, image is filtered for enhancing the image
and removing the noises and unwanted spots. Then dilation
operation is applied to the image for separating the characters
from each other if the characters are close to each other. After
this operation, horizontal and vertical smearing are applied for
finding the character regions. The result of this segmentation is
in Figure given below.
Figure (4) Locations of plate characters
The next step is to cut the plate characters. It is done by finding
starting and end points of characters in horizontal direction.
The individual characters cut from the plate are as follows in
Figure given below.
4. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 02 Issue: 08 | Aug-2013, Available @ http://www.ijret.org 356
Figure (5) Number plate characters
2.3 CHARACTER RECOGNITISON:
Automatically locate license plates by principal visual word
(PVW), discovery and local feature matching. Observing that
characters in different license plates are duplicates of each
other, we bring in the idea of using the bag-of words (Bow)
model popularly applied in partial-duplicate image search.
Unlike the classic Bow model, for each plate character, we
automatically discover the PVW characterized with geometric
context. Given a new image, the license plates are extracted by
matching local features with PVW. Besides license plate
detection, our approach can also be extended to the detection of
logos and trademarks. Due to the invariance virtue of scale-
invariant feature transform feature, our method can adaptively
deal with various changes in the license plates, such as rotation,
scaling, illumination, etc. Promising results of the proposed
approach are demonstrated with an experimental study in
license plate detection. We formulate license plate detection as
a visual matching problem. For each character, we collect SIFT
features falling into the character region and generate PVW by
unsupervised clustering. The amount of PVW for each plate
character is determined automatically Besides SIFT
descriptors, each visual word contains some geometric
information, such as orientation, ratio of scale to character
height, and relative position in the character region. Those
geometric clues will be used to filter false feature matches and
estimate the character and plate size. In testing, every valid
match votes a support for plate location, and all supports are
unified to discover potential license plates. Due to the
invariance virtue of SIFT feature, our method can adaptively
deal with various changes of license plate, such as distortion
from observation views, scaling, and illumination. Multiple
license plates in a single image can also be automatically
detected.
In visual word matching and license plate locating, we compare
the extracted SIFT features of the test image with all
discovered PVW, and locate the license plate based on the
matching results. Let us denote the PVW set as {D, G} ={(di ,
gi ), i = 1, . . . , N}, where di denotes appearance descriptor,
and gi denotes the geometric clues, N denotes the visual word
number. Once the PVW of an object category is discovered, we
can use it for detection in a new image. Given features F = { fi
} for a test image, the probability that the test image
corresponds to a sign of interest is
)0,(
),(
)0()0,(
),0( ii
ii
ii
ii gdp
gdp
pgdp
gdp α
⋅
=
……………………………. (1)
Where p(O) is prior of plate. The likelihood p(di , gi |O) is
deduced as
∑ ⋅=
j
jjiiii fpfgdpgdp )0()0,,()0,(
……………………………. (2)
Where p(di , gi | f j , O) is modeled by matching feature f j to
the descriptor di of the PVW.
Figure (6) Illustration of a PVW (red arrow) in the character
“6”
Consequently, by searching for the local maxima of the
likelihood function given by (1) for all PVW, we can find the
initial hypotheses for license plate location. Some other prior
heuristics can also be imposed to remove potential false
positives. In the following subsections, we will discuss PVW
generation and local feature matching to extract license plate in
detail.
A. PVW Generation
There are a certain number of sorted characters in license
plates, each with the same format, but maybe undergoing
illumination change or affine transformation. Since SIFT
feature is invariant to changes in scale and rotation, and robust
to illumination change and affine distortion [2], some
repeatable and distinctive SIFT features to each character exist,
called PVW. As shown in Fig., a PVW is denoted as V (des,
ori, rat, pos), where des is the 128-D SIFT descriptor, ori is the
SIFT orientation (−π ≤ ori < π), rat = H/s (s is the SIFT scale),
and pos = ( f/W, e/H) is a 2-D vector denoting the relative
position of the key point in the character region. Both des and
ori are originated from the standard SIFT features [2] des
captures the local visual appearance with a concatenation of 8-
D orientation histograms from 4 by 4 subpatches around local
interest point. ori denotes the dominant directions of local
gradients around a key point. Relative to ori and des is
represented to achieve invariance to image rotation changes .
Ideally, for a feature with high repeatability in a certain
character, rat shall be identical. Given this specific SIFT
feature with scale s, we can estimate the corresponding
character height as rat · s. Given an image patch of the
character with height, v, we can also derive the scale of the
SIFT feature as v/rat. We collect many training images, each
5. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 02 Issue: 08 | Aug-2013, Available @ http://www.ijret.org 357
containing one or more license plates. License plates in the
training images are all upright, with little affine distortion.
Each character in the license plate is annotated and all SIFT
features in each character region are extracted. Usually, many
noisy features also exist. To discover the PVW of each
character, we need to cluster the local features of each
character and discover the most representative cluster centers
as the PVW, which can be found automatically in the
clustering process. In affinity propagation, a similarity matrix
of samples shall be defined. We first give the distance metric,
which will be used to define the similarity metric. The distance
between two feature samples V j and Vk is defined in (3)
PrOdkj DDDDd ⋅+⋅+⋅+⋅= δγβα,
…..……..(3)
where α, β, γ, and δ are constant weighting factors, Dd ,Do, Dr,
and Dp are the distance of descriptor, orientation, height-scale
ratio, and position, respectively, and are defined as follows:
∑=
−=
128
1
2
)(
1
i
k
i
j
id desdesD
σ
……………… (4)
( )kjkj
O orioriorioriD −−−⋅= π
π
2,min
1
……………. (5)
kj
r ratrat
N
D −=
1
…………. (6)
∑=
−=
2
1
2
)(
2
1
i
k
i
j
ip posposD
………………... (7)
Where σ and N are normalization factors to make sure that both
Dd and Dr range from 0 to 1.
The similarity metric is a decreasing function of the distance
metric. There are many choices for it. In our implementation,
the pair wise similarity between two feature samples V j and
Vk is defined as
)0(,)( ,, >−= ndS n
kjkj
(8)
In affinity propagation, the diagonal elements in the similarity
matrix are referred to as exemplar preference, which will
influence the number of identified clusters. Generally, without
any priori, we set it as the median of the input similarities, after
clustering; we need to discover the most representative clusters.
For each cluster, we count the number of image patches which
contain at least one feature falling into the cluster. Then an
image-number histogram is built. To select those representative
clusters, a threshold thresh shall be specified on the histogram.
Any cluster with image number above thresh will be selected.
In each selected cluster, the PVW are defined as the average of
all samples falling into that cluster. In our experiments, we set
thresh = 0.6·Num, where Num is the total sample number of
the specific character. Fig. illustrates the feature clustering
results of three characters: “0,” “6,” and “9.” In each character,
the PVW are highlighted in red color on the patch with its
geometric information: ori, rat, and pos. The PVW of
characters from “0” to “9” are shown in Fig. while those of
characters from “A” to “Z” excluding “I” and“O” are
illustrated in Fig. 5. There are no PVW of character “I” and
“O” as these two characters are not found in any training plate.
B. Visual Word Matching
Given a test image, we will discover those characters with
features matched to the PVW. We first extract SIFT features
from the test image. Then each SIFT feature F(des, ori, scl) is
compared with the PVW of each character. A feature is
considered as a candidate match if the minimum descriptor
distance to a certain PVW of a certain character is less than
constant threshold T
{ } Tdesdestd d
t
F
td
≤−=
2,
**
argmin,
(9)
Where desF denotes the descriptor vector of a test SIFT
feature, des d t denotes the descriptor vector of the t-th PVW in
the d-th plate character. In standard SIFT features, descriptors
are all normalized to be a constant const. In our experiments,
we set T = 0.5 · const. Each candidate match is recorded as
C(x, y, angle, height, pos), where x and y denote spatial
position of the test SIFT feature in the image plane, angle is the
rotation angle from the test feature to the matched visual word,
height = rat dt* · sclF is the estimated height of the
corresponding license plate, pos = pos d*t* denotes the relative
position in character.
Figure (7) PVW of each digit in Chinese license plate each
arrow denotes a PVW
6. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 08 | Aug-2013, Available @ http://www.ijret.org 358
Figure (8) PVW of each letter in Chinese license plate, from
“A” to “Z,”excluding “I” and “O” each arrow denotes a PVW.
2.3. License Plate Locating
Once the character features in the test image are identified, we
can make use of the geometric context of the matched PVW to
locate the license plate. A bounding box will be estimated to
encompass license plate by determining the upper, lower, left,
and right bounding lines sequentially.
We first estimate the upper and lower bounding lines of license
plate in images. Specially, each matched feature C(x, y, angle,
height, pos) estimates a point (xup, yup) of the upper bounding
line by (10) and (11)
)sin(cos)2( θθ −⋅⋅−= hposxxuo (10)
)cos(sin)2( θθ +⋅⋅−= hposyyup
(11)
Where h and θ are the median of height and angle of all valid
matched features C, respectively, pos(2) = e/H. The origin is
assumed to be at the upper-left corner of the image plane.
Then, for all upper bounding points, we estimate a line with
linear regression. Similarly, we can also determine the lower
bounding points (xdown, ydown) with (12) and (13) and
estimate the lower bounding line of license plate.
)sin(cos))2(1( θθ −⋅⋅−+= hposxxdown (12)
)cos(sin))2(1( θθ +⋅⋅−+= hposyydown (13)
After that, we can also roughly estimate the left and right
bounding lines. In license plate, the ratio of plate width to
height is constant. When the plate height h is estimated, we can
obtain the plate width w. Since license plate must cover all
matched key points of SIFT feature, the interval between the
left bound and the most right key point of matched feature shall
be no less than w, so is that of the interval between the right
bounding line and the most left key point. Consequently, we
can determine the minimal bounding box containing the license
plate although some background patch is also included, they
can be removed with some other information, such as edge
map. However, this is not our focus in this paper.
3. EXPERIMENTAL RESULTS
To evaluate the proposed approach containing 410 Chinese
license plate images. Of them, 160 license plate images are
downloaded from the Internet while another 250 images are
taken by the authors. The second dataset contains 112 images
with resolution of 896 ?592, each contains a U.S. license plate
with a cluttered background, such as trees or grass. In this
dataset, the plate character height ranges from about 16 to 23.
On the first dataset, it achieves a 93.2% “true” detection rate,
On the second dataset, the “true” detection rate of our approach
is 84.8%,All the “true” detection rates of four approaches are
lower than that on the first dataset. This is because the plates in
the second dataset are of smaller size, and the background is
much more cluttered. The false positive rate of our approach is
also much lower than that of the three comparison approaches.
We investigate the time efficiency from two aspects. The first
one is feature extraction time, and the second one is detection
time after feature extraction. Our approach is based on SIFT
feature, whose extraction time cost is larger than that of edge
maps, as used in the other three comparison approaches. The
detection time cost of our approach is proportional to the SIFT
feature amount of image, while the detection efficiency of the
three comparison approaches are determined by the complexity
extent of image texture. In open environment, there are various
observation views from cameras, which will make the edge
map-based methods difficult to accurately extract the whole
plate. However, benefiting from the invariance property of
SIFT feature, our approach can effectively address that
difficulty when the observation angle is within some tolerance
range. Some results seen in figure12
Figure (9) Sample detection results of license plates
CONCLUSIONS
In general, an ALPR system consists of four processing stages.
In the image acquisition stage, some points have to be
considered when choosing the ALPR system camera, such as
the camera resolution and the shutter speed. In the license plate
extraction stage, the license plate is extracted based on some
features such as the color, the boundary, or the existence of the
characters. In the license plate segmentation stage, the
characters are extracted by projecting their color information,
by labeling them, or by matching their positions with template.
Finally, the characters are recognized in the character
recognition stage by template matching, or by classifiers such
7. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 08 | Aug-2013, Available @ http://www.ijret.org 359
as neural networks and fuzzy classifiers. Automatic license
plate recognition is quite challenging due to the different
license plate formats and the varying environmental conditions.
There are numerous ALPR techniques have been proposed in
recent years.
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BIOGRAPHIES:
Rinku K. Solanki, M.Tech student (digital communication),
NRI-IST, Bhopal, Madhya Pradesh, India,
Rinkusolanki86@gmail.com
RAJESH KUMAR RAI, Asst. Prof.(Head of the department
of E.C.), NIIST, Bhopal, Madhya Pradesh, India
raj.rai1008@gmail.com
Teena Raikwar, Assistant professor, electronica &
communication dept., (NRI-IST, Bhopal), Madhya Pradesh,
India
t_raikwar.2006@yahoo.co.in