License plate recognition system is one of the core technologies in intelligent traffic control. In this paper, a new and tunable algorithm which can detect multiple license plates in high resolution applications is proposed. The algorithm aims at investigation into and identification of the novel Iranian and some European countries plate, characterized by both inclusion of blue area on it and its geometric shape. Obviously, the suggested algorithm contains suitable velocity due to not making use of heavy pre-processing operation such as image-improving filters, edge-detection operation and omission of noise at the beginning stages. So, the recommended method of ours is compatible with model-adaptation, i.e., the very blue section of the plate so that the present method indicated the fact that if several plates are included in the image, the method can successfully manage to detect it. We evaluated our method on the two Persian single vehicle license plate data set that we obtained 99.33, 99% correct recognition rate respectively. Further we tested our algorithm on the Persian multiple vehicle license plate data set and we achieved 98% accuracy rate. Also we obtained approximately 99% accuracy in character recognition stage.
Help the Genetic Algorithm to Minimize the Urban Traffic on IntersectionsIJORCS
Control of traffic lights at the intersections of the main issues is the optimal traffic. Intersections to regulate traffic flow of vehicles and eliminate conflicting traffic flows are used. Modeling and simulation of traffic are widely used in industry. In fact, the modeling and simulation of an industrial system is studied before creating economically and when it is affordable. The aim of this article is a smart way to control traffic. The first stage of the project with the objective of collecting statistical data (cycle time of each of the intersection of the lights of vehicles is waiting for a red light) steps where the data collection found optimal amounts next it is. Introduced by genetic algorithm optimization of parameters is performed. GA begin with coding step as a binary variable (the range specified by the initial data set is obtained) will start with an initial population and then a new generation of genetic operators mutation and crossover and will Finally, the members of the optimal fitness values are selected as the solution set. The optimal output of Petri nets CPN TOOLS modeling and software have been implemented. The results indicate that the performance improvement project in intersections traffic control systems. It is known that other data collected and enforced intersections of evolutionary methods such as genetic algorithms to reduce the waiting time for traffic lights behind the red lights and to determine the appropriate cycle.
A Novel Multiple License Plate Extraction Technique for Complex Background in...CSCJournals
License plate recognition (LPR) is one of the most important applications of applying computer techniques towards intelligent transportation systems (ITS). In order to recognize a license plate efficiently, location and extraction of the license plate is the key step. Hence finding the position of a license plate in a vehicle image is considered to be the most crucial step of an LPR system, and this in turn greatly affects the recognition rate and overall speed of the whole system. This paper mainly deals with the detecting license plate location issues in Indian traffic conditions. The vehicles in India sometimes bare extra textual regions such as owner’s name, symbols, popular sayings and advertisement boards in addition to license plate. Situation insists for accurate discrimination of text class and fine aspect ratio analysis. In addition to this additional care taken up in this paper is to extract license plate of motorcycle (size of plate is small and double row plate), car (single as well as double row type), transport system such as bus, truck, (dirty plates) as well as multiple license plates present in an image frame under consideration. Disparity of aspect ratios is a typical feature of Indian traffic. Proposed method aims at identifying region of interest by performing a sequence of directional segmentation and morphological processing. Always the first step is of contrast enhancement, which is accomplished by using sigmoid function. In the subsequent steps, connected component analysis followed by different filtering techniques like aspect ratio analysis and plate compatible filter technique is used to find exact license plate. The proposed method is tested on large database consisting of 750 images taken in different conditions. The algorithm could detect the license plate in 742 images with success rate of 99.2%.
Enhancement performance of road recognition system of autonomous robots in sh...sipij
Road region recognition is a main feature that is gaining increasing attention from intellectuals because it
helps autonomous vehicle to achieve a successful navigation without accident. However, different
techniques based on camera sensor have been used by various researchers and outstanding results have
been achieved. Despite their success, environmental noise like shadow leads to inaccurate recognition of
road region which eventually leads to accident for autonomous vehicle. In this research, we conducted an
investigation on shadow and its effects, optimized the road region recognition system of autonomous
vehicle by introducing an algorithm capable of detecting and eliminating the effects of shadow. The
experimental performance of our system was tested and compared using the following schemes: Total
Positive Rate (TPR), False Negative Rate (FNR), Total Negative Rate (TNR), Error Rate (ERR) and False
Positive Rate (FPR). The performance result of the system improved on road recognition in shadow
scenario and this advancement has added tremendously to successful navigation approaches for
autonomous vehicle.
A Much Advanced and Efficient Lane Detection Algorithm for Intelligent Highwa...cscpconf
This paper presents a much advanced and efficient lane detection algorithm. The algorithm is based on (ROI) Region of Interest segmentation. In this algorithm images are pre-processed by top-hat transform for de-noising and enhancing contrast. ROI of a test image is then extracted. For detecting lines in the ROI, Hough transform is used. Estimation of the distance between Hough origin and lane-line midpoint is made. Lane departure decision is made based on the difference between these distances. As for the simulation part we have used Matlab software.Experiments show that the proposed algorithm can detect the lane markings accurately and quickly.
Help the Genetic Algorithm to Minimize the Urban Traffic on IntersectionsIJORCS
Control of traffic lights at the intersections of the main issues is the optimal traffic. Intersections to regulate traffic flow of vehicles and eliminate conflicting traffic flows are used. Modeling and simulation of traffic are widely used in industry. In fact, the modeling and simulation of an industrial system is studied before creating economically and when it is affordable. The aim of this article is a smart way to control traffic. The first stage of the project with the objective of collecting statistical data (cycle time of each of the intersection of the lights of vehicles is waiting for a red light) steps where the data collection found optimal amounts next it is. Introduced by genetic algorithm optimization of parameters is performed. GA begin with coding step as a binary variable (the range specified by the initial data set is obtained) will start with an initial population and then a new generation of genetic operators mutation and crossover and will Finally, the members of the optimal fitness values are selected as the solution set. The optimal output of Petri nets CPN TOOLS modeling and software have been implemented. The results indicate that the performance improvement project in intersections traffic control systems. It is known that other data collected and enforced intersections of evolutionary methods such as genetic algorithms to reduce the waiting time for traffic lights behind the red lights and to determine the appropriate cycle.
A Novel Multiple License Plate Extraction Technique for Complex Background in...CSCJournals
License plate recognition (LPR) is one of the most important applications of applying computer techniques towards intelligent transportation systems (ITS). In order to recognize a license plate efficiently, location and extraction of the license plate is the key step. Hence finding the position of a license plate in a vehicle image is considered to be the most crucial step of an LPR system, and this in turn greatly affects the recognition rate and overall speed of the whole system. This paper mainly deals with the detecting license plate location issues in Indian traffic conditions. The vehicles in India sometimes bare extra textual regions such as owner’s name, symbols, popular sayings and advertisement boards in addition to license plate. Situation insists for accurate discrimination of text class and fine aspect ratio analysis. In addition to this additional care taken up in this paper is to extract license plate of motorcycle (size of plate is small and double row plate), car (single as well as double row type), transport system such as bus, truck, (dirty plates) as well as multiple license plates present in an image frame under consideration. Disparity of aspect ratios is a typical feature of Indian traffic. Proposed method aims at identifying region of interest by performing a sequence of directional segmentation and morphological processing. Always the first step is of contrast enhancement, which is accomplished by using sigmoid function. In the subsequent steps, connected component analysis followed by different filtering techniques like aspect ratio analysis and plate compatible filter technique is used to find exact license plate. The proposed method is tested on large database consisting of 750 images taken in different conditions. The algorithm could detect the license plate in 742 images with success rate of 99.2%.
Enhancement performance of road recognition system of autonomous robots in sh...sipij
Road region recognition is a main feature that is gaining increasing attention from intellectuals because it
helps autonomous vehicle to achieve a successful navigation without accident. However, different
techniques based on camera sensor have been used by various researchers and outstanding results have
been achieved. Despite their success, environmental noise like shadow leads to inaccurate recognition of
road region which eventually leads to accident for autonomous vehicle. In this research, we conducted an
investigation on shadow and its effects, optimized the road region recognition system of autonomous
vehicle by introducing an algorithm capable of detecting and eliminating the effects of shadow. The
experimental performance of our system was tested and compared using the following schemes: Total
Positive Rate (TPR), False Negative Rate (FNR), Total Negative Rate (TNR), Error Rate (ERR) and False
Positive Rate (FPR). The performance result of the system improved on road recognition in shadow
scenario and this advancement has added tremendously to successful navigation approaches for
autonomous vehicle.
A Much Advanced and Efficient Lane Detection Algorithm for Intelligent Highwa...cscpconf
This paper presents a much advanced and efficient lane detection algorithm. The algorithm is based on (ROI) Region of Interest segmentation. In this algorithm images are pre-processed by top-hat transform for de-noising and enhancing contrast. ROI of a test image is then extracted. For detecting lines in the ROI, Hough transform is used. Estimation of the distance between Hough origin and lane-line midpoint is made. Lane departure decision is made based on the difference between these distances. As for the simulation part we have used Matlab software.Experiments show that the proposed algorithm can detect the lane markings accurately and quickly.
TRAFFIC-SIGN RECOGNITION FOR AN INTELLIGENT VEHICLE/DRIVER ASSISTANT SYSTEM U...cseij
In order to be deployed in driving environments, Intelligent transport system (ITS) must be able to
recognize and respond to exceptional road conditions such as traffic signs, highway work zones and
imminent road works automatically. Recognition of traffic sign is playing a vital role in the intelligent
transport system, it enhances traffic safety by providing drivers with safety and precaution information
about road hazards. To recognize the traffic sign, the system has been proposed with three phases. They
are Traffic board Detection, Feature extraction and Recognition. The detection phase consists of RGBbased
colour thresholding and shape analysis, which offers robustness to differences in lighting situations.
A Histogram of Oriented Gradients (HOG) technique was adopted to extract the features from the
segmented output. Finally, traffic signs recognition is done by k-Nearest Neighbors (k-NN) classifiers. It
achieves an classification accuracy upto 63%.
Improved algorithm for road region segmentation based on sequential monte car...csandit
In recent years, many researchers and car makers put a lot of intensive effort into development
of autonomous driving systems. Since visual information is the main modality used by human
driver, a camera mounted on moving platform is very important kind of sensor, and various
computer vision algorithms to handle vehicle surrounding situation are under intensive
research. Our final goal is to develop a vision based lane detection system with ability to
handle various types of road shapes, working on both structured and unstructured roads, ideally
under presence of shadows. This paper presents a modified road region segmentation algorithm
based on sequential Monte-Carlo estimation. Detailed description of the algorithm is given,
and evaluation results show that the proposed algorithm outperforms the segmentation
algorithm developed as a part of our previous work, as well as an conventional algorithm based
on colour histogram.
Path Planning for Mobile Robot Navigation Using Voronoi Diagram and Fast Marc...Waqas Tariq
For navigation in complex environments, a robot needs to reach a compromise between the need for having efficient and optimized trajectories and the need for reacting to unexpected events. This paper presents a new sensor-based Path Planner which results in a fast local or global motion planning able to incorporate the new obstacle information. In the first step the safest areas in the environment are extracted by means of a Voronoi Diagram. In the second step the Fast Marching Method is applied to the Voronoi extracted areas in order to obtain the path. The method combines map-based and sensor-based planning operations to provide a reliable motion plan, while it operates at the sensor frequency. The main characteristics are speed and reliability, since the map dimensions are reduced to an almost unidimensional map and this map represents the safest areas in the environment for moving the robot. In addition, the Voronoi Diagram can be calculated in open areas, and with all kind of shaped obstacles, which allows to apply the proposed planning method in complex environments where other methods of planning based on Voronoi do not work.
Circular Traffic Signs Recognition Using The Number of Peaks AlgorithmCSCJournals
Smart cars nowadays include embedded computers to guide the driver in his trip. An important application that should be added to any car is the detection and recognition of traffic signs. In this paper, we focus on the recognition of a wide set of circular traffic signs using the Number of Peaks Algorithm [1]. After detecting a traffic sign, the algorithm draws three horizontal lines and three vertical lines across the image. The number of peaks (crossing from a black pixel to a white pixel) is calculated for each of the six lines as the image is scanned from right to left (for horizontal lines) or top to bottom (for vertical lines). The resulting numbers of peaks are used by the decision-tree-like search algorithm to distinguish between 51 circular road signs with a mean detection time of 8 milliseconds, 100% detection rate and in a fairly noisy environment.
A Path Planning Technique For Autonomous Mobile Robot Using Free-Configuratio...CSCJournals
This paper presents the implementation of a novel technique for sensor based path planning of autonomous mobile robots. The proposed method is based on finding free-configuration eigen spaces (FCE) in the robot actuation area. Using the FCE technique to find optimal paths for autonomous mobile robots, the underlying hypothesis is that in the low-dimensional manifolds of laser scanning data, there lies an eigenvector which corresponds to the free-configuration space of the higher order geometric representation of the environment. The vectorial combination of all these eigenvectors at discrete time scan frames manifests a trajectory, whose sum can be treated as a robot path or trajectory. The proposed algorithm was tested on two different test bed data, real data obtained from Navlab SLAMMOT and data obtained from the real-time robotics simulation program Player/Stage. Performance analysis of FCE technique was done with existing four path planning algorithms under certain working parameters, namely computation time needed to find a solution, the distance travelled and the amount of turning required by the autonomous mobile robot. This study will enable readers to identify the suitability of path planning algorithm under the working parameters, which needed to be optimized. All the techniques were tested in the real-time robotic software Player/Stage. Further analysis was done using MATLAB mathematical computation software.
License Plate Localization based on Statistical Measures of License Plate Fea...idescitation
License plate localization is considered as the most important part of license
plate recognition system. The high accuracy rate of license plate recognition is depended on
the ability of license plate detection. This paper presents a novel method for license plate
localization bases on license plate features. This proposed method consists of two main
processes. First, candidate regions extraction step, Sobel operator is applied to obtain
vertical edges and then potential candidate regions are extracted by deploying mathematical
morphology operations [5]. Last, license plate verification step, this step employs the
standard deviation of license plate features to confirm license plate position. The
experimental results show that the proposed method can achieve high quality license plate
localization results with high accuracy rate of 98.26 %.
This paper deals with the optimization of the capacity of a terminal railway station using the
Ant Colony Optimization algorithm. The capacity of the terminal station is defined as the
number of trains that depart from the station in unit interval of time. The railway capacity
optimization problem is framed as a typical symmetrical Travelling Salesman Problem (TSP),
with the TSP nodes representing the train arrival /departure events and the TSP total cost
representing the total time-interval of the schedule. The application problem is then optimized
using the ACO algorithm. The simulation experiments validate the formulation of the railway
capacity problem as a TSP and the ACO algorithm produces optimal solutions superior to those
produced by the domain experts.
REVIEW OF LANE DETECTION AND TRACKING ALGORITHMS IN ADVANCED DRIVER ASSISTANC...ijcsit
Lane detection and tracking is one of the key features of advanced driver assistance system. Lane detection is finding the white markings on a dark road. Lane tracking use the previously detected lane markers and adjusts itself according to the motion model. In this paper, review of lane detection and tracking algorithms developed in the last decade is discussed. Several modalities are considered for lane detection which
include vision, LIDAR, vehicle odometry information,information from global positioning system and digital maps. The lane detection and tracking is one of the challenging problems in computer vision.Different vision based lane detection techniques are explained in the paper. The performance of different lane detection and tracking algorithms is also compared and studied.
Artificial Intelligence in Robot Path Planningiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
A Method for Sudanese Vehicle License Plates Detection and ExtractionEditor IJCATR
License Plate Detection and Extraction is an important phase of Vehicle License Plate Recognition systems, which has been
an active research topic in the computer vision domain in order to identify vehicles by their license plates without direct human
intervention. This paper presents a simple, fast and automatic License Plate Detection method for the current shape of Sudanese license
plate. The proposed method involves several steps: green channel extraction, edge detection, regions of interest selection, dilation
operation with especial structural element and connected component analysis. In order to analyze the performance and efficiency of the
proposed method a data set for Sudanese vehicles has been created. Using this new data set, number of experiments has been carried
out. Comparing with other countries license plate detection the achieved results is satisfactory.
TRAFFIC-SIGN RECOGNITION FOR AN INTELLIGENT VEHICLE/DRIVER ASSISTANT SYSTEM U...cseij
In order to be deployed in driving environments, Intelligent transport system (ITS) must be able to
recognize and respond to exceptional road conditions such as traffic signs, highway work zones and
imminent road works automatically. Recognition of traffic sign is playing a vital role in the intelligent
transport system, it enhances traffic safety by providing drivers with safety and precaution information
about road hazards. To recognize the traffic sign, the system has been proposed with three phases. They
are Traffic board Detection, Feature extraction and Recognition. The detection phase consists of RGBbased
colour thresholding and shape analysis, which offers robustness to differences in lighting situations.
A Histogram of Oriented Gradients (HOG) technique was adopted to extract the features from the
segmented output. Finally, traffic signs recognition is done by k-Nearest Neighbors (k-NN) classifiers. It
achieves an classification accuracy upto 63%.
Improved algorithm for road region segmentation based on sequential monte car...csandit
In recent years, many researchers and car makers put a lot of intensive effort into development
of autonomous driving systems. Since visual information is the main modality used by human
driver, a camera mounted on moving platform is very important kind of sensor, and various
computer vision algorithms to handle vehicle surrounding situation are under intensive
research. Our final goal is to develop a vision based lane detection system with ability to
handle various types of road shapes, working on both structured and unstructured roads, ideally
under presence of shadows. This paper presents a modified road region segmentation algorithm
based on sequential Monte-Carlo estimation. Detailed description of the algorithm is given,
and evaluation results show that the proposed algorithm outperforms the segmentation
algorithm developed as a part of our previous work, as well as an conventional algorithm based
on colour histogram.
Path Planning for Mobile Robot Navigation Using Voronoi Diagram and Fast Marc...Waqas Tariq
For navigation in complex environments, a robot needs to reach a compromise between the need for having efficient and optimized trajectories and the need for reacting to unexpected events. This paper presents a new sensor-based Path Planner which results in a fast local or global motion planning able to incorporate the new obstacle information. In the first step the safest areas in the environment are extracted by means of a Voronoi Diagram. In the second step the Fast Marching Method is applied to the Voronoi extracted areas in order to obtain the path. The method combines map-based and sensor-based planning operations to provide a reliable motion plan, while it operates at the sensor frequency. The main characteristics are speed and reliability, since the map dimensions are reduced to an almost unidimensional map and this map represents the safest areas in the environment for moving the robot. In addition, the Voronoi Diagram can be calculated in open areas, and with all kind of shaped obstacles, which allows to apply the proposed planning method in complex environments where other methods of planning based on Voronoi do not work.
Circular Traffic Signs Recognition Using The Number of Peaks AlgorithmCSCJournals
Smart cars nowadays include embedded computers to guide the driver in his trip. An important application that should be added to any car is the detection and recognition of traffic signs. In this paper, we focus on the recognition of a wide set of circular traffic signs using the Number of Peaks Algorithm [1]. After detecting a traffic sign, the algorithm draws three horizontal lines and three vertical lines across the image. The number of peaks (crossing from a black pixel to a white pixel) is calculated for each of the six lines as the image is scanned from right to left (for horizontal lines) or top to bottom (for vertical lines). The resulting numbers of peaks are used by the decision-tree-like search algorithm to distinguish between 51 circular road signs with a mean detection time of 8 milliseconds, 100% detection rate and in a fairly noisy environment.
A Path Planning Technique For Autonomous Mobile Robot Using Free-Configuratio...CSCJournals
This paper presents the implementation of a novel technique for sensor based path planning of autonomous mobile robots. The proposed method is based on finding free-configuration eigen spaces (FCE) in the robot actuation area. Using the FCE technique to find optimal paths for autonomous mobile robots, the underlying hypothesis is that in the low-dimensional manifolds of laser scanning data, there lies an eigenvector which corresponds to the free-configuration space of the higher order geometric representation of the environment. The vectorial combination of all these eigenvectors at discrete time scan frames manifests a trajectory, whose sum can be treated as a robot path or trajectory. The proposed algorithm was tested on two different test bed data, real data obtained from Navlab SLAMMOT and data obtained from the real-time robotics simulation program Player/Stage. Performance analysis of FCE technique was done with existing four path planning algorithms under certain working parameters, namely computation time needed to find a solution, the distance travelled and the amount of turning required by the autonomous mobile robot. This study will enable readers to identify the suitability of path planning algorithm under the working parameters, which needed to be optimized. All the techniques were tested in the real-time robotic software Player/Stage. Further analysis was done using MATLAB mathematical computation software.
License Plate Localization based on Statistical Measures of License Plate Fea...idescitation
License plate localization is considered as the most important part of license
plate recognition system. The high accuracy rate of license plate recognition is depended on
the ability of license plate detection. This paper presents a novel method for license plate
localization bases on license plate features. This proposed method consists of two main
processes. First, candidate regions extraction step, Sobel operator is applied to obtain
vertical edges and then potential candidate regions are extracted by deploying mathematical
morphology operations [5]. Last, license plate verification step, this step employs the
standard deviation of license plate features to confirm license plate position. The
experimental results show that the proposed method can achieve high quality license plate
localization results with high accuracy rate of 98.26 %.
This paper deals with the optimization of the capacity of a terminal railway station using the
Ant Colony Optimization algorithm. The capacity of the terminal station is defined as the
number of trains that depart from the station in unit interval of time. The railway capacity
optimization problem is framed as a typical symmetrical Travelling Salesman Problem (TSP),
with the TSP nodes representing the train arrival /departure events and the TSP total cost
representing the total time-interval of the schedule. The application problem is then optimized
using the ACO algorithm. The simulation experiments validate the formulation of the railway
capacity problem as a TSP and the ACO algorithm produces optimal solutions superior to those
produced by the domain experts.
REVIEW OF LANE DETECTION AND TRACKING ALGORITHMS IN ADVANCED DRIVER ASSISTANC...ijcsit
Lane detection and tracking is one of the key features of advanced driver assistance system. Lane detection is finding the white markings on a dark road. Lane tracking use the previously detected lane markers and adjusts itself according to the motion model. In this paper, review of lane detection and tracking algorithms developed in the last decade is discussed. Several modalities are considered for lane detection which
include vision, LIDAR, vehicle odometry information,information from global positioning system and digital maps. The lane detection and tracking is one of the challenging problems in computer vision.Different vision based lane detection techniques are explained in the paper. The performance of different lane detection and tracking algorithms is also compared and studied.
Artificial Intelligence in Robot Path Planningiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
A Method for Sudanese Vehicle License Plates Detection and ExtractionEditor IJCATR
License Plate Detection and Extraction is an important phase of Vehicle License Plate Recognition systems, which has been
an active research topic in the computer vision domain in order to identify vehicles by their license plates without direct human
intervention. This paper presents a simple, fast and automatic License Plate Detection method for the current shape of Sudanese license
plate. The proposed method involves several steps: green channel extraction, edge detection, regions of interest selection, dilation
operation with especial structural element and connected component analysis. In order to analyze the performance and efficiency of the
proposed method a data set for Sudanese vehicles has been created. Using this new data set, number of experiments has been carried
out. Comparing with other countries license plate detection the achieved results is satisfactory.
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.
Number Plate Recognition for Indian Vehiclesmonjuri10
This paper presents Automatic Number Plate
extraction, character segmentation and recognition for
Indian vehicles. In India, number plate models are not
followed strictly. Characters on plate are in different
Indian languages, as well as in English. Due to variations
in the representation of number plates, vehicle number
plate extraction, character segmentation and recognition
are crucial. We present the number plate extraction,
character segmentation and recognition work, with english
characters. Number plate extraction is done using Sobel
filter, morphological operations and connected component
analysis. Character segmentation is done by using
connected component and vertical projection analysis.
Character recognition is carried out using Support Vector
machine (SVM). The segmentation accuracy is 80% and
recognition rate is 79.84 %.
Automatic license plate recognition system for indian vehicle identification ...Kuntal Bhowmick
Automatic License Plate Recognition (ANPR) is a practical application of image processing which uses number (license) plate is used to identify the vehicle. The aim is to design an efficient automatic vehicle identification system by using the
vehicle license plate. The system is implemented on the entrance for security control of a highly restricted area like
military zones or area around top government offices e.g.Parliament, Supreme Court etc.
It is worth mentioning that there is a scarcity in researches that introduce an automatic number plate recognition for indian vechicles.In this paper, a new algorithm is presented for Indian vehicle’s number plate recognition system. The proposed algorithm consists of two major parts: plate region extraction and plate recognition.Vehicle number plate region is extracted using the image segmentation in a vechicle image.Optical character recognition technique is used for the character recognition. And finally the resulting data is used to compare with the records on a database so as to come up with the specific information like the vehicle’s owner, registration state, address, etc.
The performance of the proposed algorithm has been tested on real license plate images of indian vechicles. Based on the experimental results, we noted that our algorithm shows superior performance special in number plate recognition phase.
Artificial Neural Network (ANN), Automatic Number Plate Recognition (ANPR), Character Segmentation,Edge detection, Extraction plate region, Image Segmentation, Number plate recognition, Number Plate, Optical Character Recognition.
Number plate identification perimeter protection system. Control which vehicle access your premise. Assign rules for vehicles trying to enter the premise. Blacklist vehicles. Generate Alert if a blacklisted or unregistered vehicle trying to enter the area. Make efficient use of your security staff
AUTOMATIC LICENSE PLATE RECOGNITION SYSTEM FOR INDIAN VEHICLE IDENTIFICATION ...Kuntal Bhowmick
Automatic License Plate Recognition (ANPR) is a practical application of image processing which uses number (license) plate is used to identify the vehicle. The aim is to design an efficient automatic vehicle identification system by using the
vehicle license plate. The system is implemented on the entrance for security control of a highly restricted area like
military zones or area around top government offices e.g.Parliament, Supreme Court etc.
It is worth mentioning that there is a scarcity in researches that introduce an automatic number plate recognition for indian vechicles.In this paper, a new algorithm is presented for Indian vehicle’s number plate recognition system. The proposed algorithm consists of two major parts: plate region extraction and plate recognition.Vehicle number plate region is extracted using the image segmentation in a vechicle image.Optical character recognition technique is used for the character recognition. And finally the resulting data is used to compare with the records on a database so as to come up with the specific information like the vehicle’s owner, registration state, address, etc.
The performance of the proposed algorithm has been tested on real license plate images of indian vechicles. Based on the experimental results, we noted that our algorithm shows superior performance special in number plate recognition phase.
Abstract:
With an everyday increase in the number of cars on our roads and highways, we are facing numerous problems, for example:
• Smuggling of cars
• Invalid license plates
• Identification of stolen cars
• Usage of cars in terrorist attacks/illegal activities
In order to address the above issues, we took up the project of developing a prototype, which can perform license plate recognition (LPR). This project, as the name signifies, deals with reading, storing and comparing the license plate numbers retrieved from snapshots of cars to ensure safety in the country and ultimately help to reduce unauthorized vehicles access and crime.
License Plate Recognition (LPR) has been a practical technique in the past decades. It is one of the most important applications for Computer Vision, Patter Recognition and Image Processing in the field of Intelligent Transportation Systems (ITS).
Generally, the LPR system is divided into three steps, license plate locating, license plate character segmentation and license plate recognition. This project discusses a complete license plate recognition system with special emphasis on the Localization Module.In this study, the proposed algorithm is based on extraction of plate region using morphological operations and shape detection algorithms. Segmentation of plate made use of horizontal and vertical smearing and line detection algorithms. Lastly, template matching algorithms were used for character recognition.
The implementation of the project was done in the platforms of Matlab and OpenCV.
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.
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.
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.
Research on License Plate Recognition and Extraction from complicated ImagesIJERA Editor
Vehicle number plate recognition has attracted many researchers for intelligent transportation systems such as the payment of parking fee, controlling the traffic volume, traffic data collection, etc. We are presenting an enhanced license plate extraction methodology which includes edge statistics and the morphology. The proposed methodology includes vertical edge extraction, background curve and noise removing, edge statistical analysis and morphology-based license plate extraction.
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.
Automatic License Plate Recognition Using Optical Character Recognition Based...IJARIIE JOURNAL
A License plate is a rectangular plate which is alphanumeric. The license plate is fixed on the vehicle and used to
identify the vehicle along with honor of that vehicle. There is a huge number of vehicles on the road so that traffic
control and vehicle owner identification has become a major problem.
The automatic number plate reorganization (ANPR) is one of the solutions of such kind of problem. There are
different methodologies but it is challenging task as some of the factors like high speed of vehicles, languages of
number plate & mostly non-uniform letter on number plate effects a lot in recognition. The license plate recognition
system mainly has four stages: image acquisition, license plate detection, character segmentation and character
recognition. The license plate recognition (LPR) system have many applications like payment of parking fees; toll
fee on the highway; traffic monitoring system; border security system; signal system etc.
In this paper, template matching algorithm for character recognition is used. The system presented here mainly
focuses on recognition of ambiguous characters based on position of the character. It is observed that the developed
system successfully detects & recognizes the vehicle number plate on real images and the problem of recognizing
ambiguous character is solved.
Street Mark Detection Using Raspberry PI for Self-driving SystemTELKOMNIKA JOURNAL
Self driving is an autonomous vehicle that can follow the road with less human intervention. The development of self driving utilizes various methods such as radar, lidar, GPS, camera, or combination of them. In this research, street mark detection system was designed using webcam and raspberry-pi mini computer for processing the image. The image was processed by HSV color filtering method. The processing rate of this algorithm was 137.98 ms correspondinig to 7.2 FPS. The self-driving prototype was found to be working optimally for “hue” threshold of 0-179, “saturation” threshold of 0-30, and “value” threshold of 200-255. Street mark detection has been obtained from the coordinates of street mark object which had range 4-167 on x axis and 4-139 on y axis. As a result, we have successfully built the street mark detection by COG method more effectively and smoothly in detection in comparison with Hough transform method.
An Approach for Benin Automatic Licence Plate RecognitionCSCJournals
In this work, we read licence plates using Optical Character Recognition. Our algorithm relies on the detection of plates on the basis of contours and text that they contain. Thank to the combinaison of these two detection mode, our algorithm remains effective even when the plate is slightly obstructed. For the separation of false positive from real images of license plates, we use filters based on text and registration plates general characteristics. This gives our algorithm a great ability to adapt to different contexts. Following our experimental test on license plates in Benin, we obtained a recall rate of 86% and an accuracy rate of 60%.
A License plate is a rectangular plate which is alphanumeric. The license plate is fixed on the vehicle and used to identify the
vehicle along with honor of that vehicle. There is a huge nos. of vehicles are on the road word wile so that traffic control and
vehicle owner identification has become a major problem.
The automatic number plate reorganization (ANPR) is one of the solutions of such kind of problem. There is nos. of methodologies
but it is challenging task as some of the factors like high speed of vehicles, languages of number plate & mostly non-uniform
letter on number plate effects a lot in recognition. The license plate recognition (LPR) system have many application like payment
of parking fees; toll fee on highway; traffic monitoring system; border security system; signal system etc.
In this paper, the different method of license plate recognition is discussed. The systems first detects the vehicle and capture the
image then the number plate of vehicle is extracted from the image using image Segmentation optical character recognition technique
is used for the character recognition. Then the resulting date is compared with the database record so we come up the information
like the vehicle’s owner, vehicle registration place, address etc. it is observed that developed system successfully defect
& recognize the vehicle number plate on real image.
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.
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.
Similar to Real-Time Multiple License Plate Recognition System (20)
Welcoming the research scholars, scientists around the globe in the Open Access Dimension, IJORCS is now accepting manuscripts for its next issue (Volume 4, Issue 4). Authors are encouraged to contribute to the research community by submitting to IJORCS, articles that clarify new research results, projects, surveying works and industrial experiences that describe significant advances in field of computer science.
All paper submissions (http://www.ijorcs.org/submit-paper) are received and managed electronically by IJORCS Team. Detailed instructions about the submission procedure are available on IJORCS website (http://www.ijorcs.org/author-guidelines)
FPGA Implementation of FIR Filter using Various Algorithms: A RetrospectiveIJORCS
This Paper is a review study of FPGA implementation of Finite Impulse response (FIR) with low cost and high performance. The key observation of this paper is an elaborate analysis about hardware implementations of FIR filters using different algorithm i.e., Distributed Arithmetic (DA), DA-Offset Binary Coding (DA-OBC), Common Sub-expression Elimination (CSE) and sum-of-power-of-two (SOPOT) with less resources and without affecting the performance of the original FIR Filter.
Using Virtualization Technique to Increase Security and Reduce Energy Consump...IJORCS
An approach has been presented in this paper in order to generate a secure environment on internet Based Virtual Computing platform and also to reduce energy consumption in green cloud computing. The proposed approach constantly checks the accuracy of stored data by means of a central control service inside the network environment and also checks system security through isolating single virtual machines using a common virtual environment. This approach has been simulated on two types of Virtual Machine Manager (VMM) Quick EMUlator (Qemu), HVM (Hardware Virtual Machine) Xen and outputs of the simulation in VMInsight show that when service is getting singly used, the overhead of its performance will be increased. As a secure system, the proposed approach is able to recognize malicious behaviors and assure service security by means of operational integrity measurement. Moreover, the rate of system efficiency has been evaluated according to the amount of energy consumption on five applications (Defragmentation, Compression, Linux Boot Decompression and Kernel Boot). Therefore, this has been resulted that to secure multi-tenant environment, managers and supervisors should independently install a security monitoring system for each Virtual Machines (VMs) which will come up to have the management heavy workload of. While the proposed approach, can respond to all VM’s with just one virtual machine as a supervisor.
Algebraic Fault Attack on the SHA-256 Compression FunctionIJORCS
The cryptographic hash function SHA-256 is one member of the SHA-2 hash family, which was proposed in 2000 and was standardized by NIST in 2002 as a successor of SHA-1. Although the differential fault attack on SHA-1compression function has been proposed, it seems hard to be directly adapted to SHA-256. In this paper, an efficient algebraic fault attack on SHA-256 compression function is proposed under the word-oriented random fault model. During the attack, an automatic tool STP is exploited, which constructs binary expressions for the word-based operations in SHA-256 compression function and then invokes a SAT solver to solve the equations. The simulation of the new attack needs about 65 fault injections to recover the chaining value and the input message block with about 200 seconds on average. Moreover, based on the attack on SHA-256 compression function, an almost universal forgery attack on HMAC-SHA-256 is presented. Our algebraic fault analysis is generic, automatic and can be applied to other ARX-based primitives.
Enhancement of DES Algorithm with Multi State LogicIJORCS
The principal goal to design any encryption algorithm must be the security against unauthorized access or attacks. Data Encryption Standard algorithm is a symmetric key algorithm and it is used to secure the data. Enhanced DES algorithm works on increasing the key length or complex S-BOX design or increased the number of states in which the information is to be represented or combination of above criteria. By increasing the key length, the number of combinations for key will increase which is hard for the intruder to do the brute force attack. As the S-BOX design will become the complex there will be a good avalanche effect. As the number of states increases in which the information is represented, it is hard for the intruder to crack the actual information. Proposed algorithm replace the predefined XOR operation applied during the 16 round of the standard algorithm by a new operation called “Hash function” depends on using two keys. One key used in “F” function and another key consists of a combination of 16 states (0,1,2…13,14,15) instead of the ordinary 2 state key (0, 1). This replacement adds a new level of protection strength and more robustness against breaking methods.
Hybrid Simulated Annealing and Nelder-Mead Algorithm for Solving Large-Scale ...IJORCS
This paper presents a new algorithm for solving large scale global optimization problems based on hybridization of simulated annealing and Nelder-Mead algorithm. The new algorithm is called simulated Nelder-Mead algorithm with random variables updating (SNMRVU). SNMRVU starts with an initial solution, which is generated randomly and then the solution is divided into partitions. The neighborhood zone is generated, random number of partitions are selected and variables updating process is starting in order to generate a trail neighbor solutions. This process helps the SNMRVU algorithm to explore the region around a current iterate solution. The Nelder- Mead algorithm is used in the final stage in order to improve the best solution found so far and accelerates the convergence in the final stage. The performance of the SNMRVU algorithm is evaluated using 27 scalable benchmark functions and compared with four algorithms. The results show that the SNMRVU algorithm is promising and produces high quality solutions with low computational costs.
Welcoming the research scholars, scientists around the globe in the Open Access Dimension, IJORCS is now accepting manuscripts for its next issue (Volume 4, Issue 2). Authors are encouraged to contribute to the research community by submitting to IJORCS, articles that clarify new research results, projects, surveying works and industrial experiences that describe significant advances in field of computer science.
To view complete list of topics coverage of IJORCS, Aim & Scope, please visit, www.ijorcs.org/scope
Welcoming the research scholars, scientists around the globe in the Open Access Dimension, IJORCS is now accepting manuscripts for its next issue (Volume 4, Issue 1). Authors are encouraged to contribute to the research community by submitting to IJORCS, articles that clarify new research results, projects, surveying works and industrial experiences that describe significant advances in field of computer science.
Voice Recognition System using Template MatchingIJORCS
It is easy for human to recognize familiar voice but using computer programs to identify a voice when compared with others is a herculean task. This is due to the problem that is encountered when developing the algorithm to recognize human voice. It is impossible to say a word the same way in two different occasions. Human speech analysis by computer gives different interpretation based on varying speed of speech delivery. This research paper gives detail description of the process behind implementation of an effective voice recognition algorithm. The algorithm utilize discrete Fourier transform to compare the frequency spectra of two voice samples because it remained unchanged as speech is slightly varied. Chebyshev inequality is then used to determine whether the two voices came from the same person. The algorithm is implemented and tested using MATLAB.
Channel Aware Mac Protocol for Maximizing Throughput and FairnessIJORCS
The proper channel utilization and the queue length aware routing protocol is a challenging task in MANET. To overcome this drawback we are extending the previous work by improving the MAC protocol to maximize the Throughput and Fairness. In this work we are estimating the channel condition and Contention for a channel aware packet scheduling and the queue length is also calculated for the routing protocol which is aware of the queue length. The channel is scheduled based on the channel condition and the routing is carried out by considering the queue length. This queue length will provide a measurement of traffic load at the mobile node itself. Depending upon this load the node with the lesser load will be selected for the routing; this will effectively balance the load and improve the throughput of the ad hoc network.
A Review and Analysis on Mobile Application Development Processes using Agile...IJORCS
Over a last decade, mobile telecommunication industry has observed a rapid growth, proved to be highly competitive, uncertain and dynamic environment. Besides its advancement, it has also raised number of questions and gained concern both in industry and research. The development process of mobile application differs from traditional softwares as the users expect same features similar to their desktop computer applications with additional mobile specific functionalities. Advanced mobile applications require assimilation with existing enterprise computing systems such as databases, legacy applications and Web services. In addition, the lifecycle of a mobile application moves much faster than that of a traditional Web application and therefore the lifecycle management associated therein must be adjusted accordingly. The Security and application testing are more stimulating and interesting in mobile application than in Web applications since the technology in mobile devices progresses rapidly and developers must stay in touch with the latest developments, news and trends in their area of work. With the rising competence of software market, researchers are seeking more flexible methods that can adjust to dynamic situations where software system requirements are changing over time, producing valuable software in short duration and within low budget. The intrinsic uncertainty and complexity in any software project therefore requires an iterative developmental plan to cope with uncertainty and a large number of unknown variables. Agile Methodologies were thus introduced to meet the new requirements of the software development companies. The agile methodologies aim at facilitating software development processes where changes are acceptable at any stage and provide a structure for highly collaborative software development. Therefore, the present paper aims in reviewing and analysing different prevalent methodologies utilizing agile techniques that are currently in use for the development of mobile applications. This paper provides a detailed review and analysis on the use of agile methodologies in the proposed processes associated with mobile application skills and highlights its benefit and constraints. In addition, based on this analysis, future research needs are identified and discussed.
Congestion Prediction and Adaptive Rate Adjustment Technique for Wireless Sen...IJORCS
In general, nodes in Wireless Sensor Networks (WSNs) are equipped with limited battery and computation capabilities but the occurrence of congestion consumes more energy and computation power by retransmitting the data packets. Thus, congestion should be regulated to improve network performance. In this paper, we propose a congestion prediction and adaptive rate adjustment technique for Wireless Sensor Networks. This technique predicts congestion level using fuzzy logic system. Node degree, data arrival rate and queue length are taken as inputs to the fuzzy system and congestion level is obtained as an outcome. When the congestion level is amidst moderate and maximum ranges, adaptive rate adjustment technique is triggered. Our technique prevents congestion by controlling data sending rate and also avoids unsolicited packet losses. By simulation, we prove the proficiency our technique. It increases system throughput and network performance significantly.
A Study of Routing Techniques in Intermittently Connected MANETsIJORCS
A Mobile Ad hoc Network (MANET) is a self-configuring infrastructure less network of mobile devices connected by wireless. These are a kind of wireless Ad hoc Networks that usually has a routable networking environment on top of a Link Layer Ad hoc Network. The routing approach in MANET includes mainly three categories viz., Reactive Protocols, Proactive Protocols and Hybrid Protocols. These traditional routing schemes are not pertinent to the so called Intermittently Connected Mobile Ad hoc Network (ICMANET). ICMANET is a form of Delay Tolerant Network, where there never exists a complete end – to – end path between two nodes wishing to communicate. The intermittent connectivity araise when network is sparse or highly mobile. Routing in such a spasmodic environment is arduous. In this paper, we put forward the indication of prevailing routing approaches for ICMANET with their benefits and detriments
Improving the Efficiency of Spectral Subtraction Method by Combining it with ...IJORCS
In the field of speech signal processing, Spectral subtraction method (SSM) has been successfully implemented to suppress the noise that is added acoustically. SSM does reduce the noise at satisfactory level but musical noise is a major drawback of this method. To implement spectral subtraction method, transformation of speech signal from time domain to frequency domain is required. On the other hand, Wavelet transform displays another aspect of speech signal. In this paper we have applied a new approach in which SSM is cascaded with wavelet thresholding technique (WTT) for improving the quality of speech signal by removing the problem of musical noise to a great extent. Results of this proposed system have been simulated on MATLAB.
An Adaptive Load Sharing Algorithm for Heterogeneous Distributed SystemIJORCS
Due to the restriction of designing faster and faster computers, one has to find the ways to maximize the performance of the available hardware. A distributed system consists of several autonomous nodes, where some nodes are busy with processing, while some nodes are idle without any processing. To make better utilization of the hardware, the tasks or load of the overloaded node will be sent to the under loaded node that has less processing weight to minimize the response time of the tasks. Load balancing is a tool used effectively for balancing the load among the systems. Dynamic load balancing takes into account of the current system state for migration of the tasks from heavily loaded nodes to the lightly loaded nodes. In this paper, we devised an adaptive load-sharing algorithm to balance the load by taking into consideration of connectivity among the nodes, processing capacity of each node and link capacity.
The Design of Cognitive Social Simulation Framework using Statistical Methodo...IJORCS
Modeling the behavior of the cognitive architecture in the context of social simulation using statistical methodologies is currently a growing research area. Normally, a cognitive architecture for an intelligent agent involves artificial computational process which exemplifies theories of cognition in computer algorithms under the consideration of state space. More specifically, for such cognitive system with large state space the problem like large tables and data sparsity are faced. Hence in this paper, we have proposed a method using a value iterative approach based on Q-learning algorithm, with function approximation technique to handle the cognitive systems with large state space. From the experimental results in the application domain of academic science it has been verified that the proposed approach has better performance compared to its existing approaches.
An Enhanced Framework for Improving Spatio-Temporal Queries for Global Positi...IJORCS
To efficiently process continuous spatio-temporal queries, we need to efficiently and effectively handle large number of moving objects and continuous updates on these queries. In this paper, we propose a framework that employs a new indexing algorithm that is built on top of SQL Server 2008 and avoid the overhead related to R-Tree indexing. To answer range queries, we utilize dynamic materialized view concept to efficiently handle update queries. We propose an adaptive safe region to reduce communication costs between the client and the server and to minimize position update load. Caching of results was utilized to enhance the overall performance of the framework. To handle concurrent spatio-temporal queries, we utilize publish/subscribe paradigm to group similar queries and efficiently process these requests. Experiments show that the overall proposed framework performance was able to outperform R-Tree index and produce promising and satisfactory results.
A PSO-Based Subtractive Data Clustering AlgorithmIJORCS
There is a tremendous proliferation in the amount of information available on the largest shared information source, the World Wide Web. Fast and high-quality clustering algorithms play an important role in helping users to effectively navigate, summarize, and organize the information. Recent studies have shown that partitional clustering algorithms such as the k-means algorithm are the most popular algorithms for clustering large datasets. The major problem with partitional clustering algorithms is that they are sensitive to the selection of the initial partitions and are prone to premature converge to local optima. Subtractive clustering is a fast, one-pass algorithm for estimating the number of clusters and cluster centers for any given set of data. The cluster estimates can be used to initialize iterative optimization-based clustering methods and model identification methods. In this paper, we present a hybrid Particle Swarm Optimization, Subtractive + (PSO) clustering algorithm that performs fast clustering. For comparison purpose, we applied the Subtractive + (PSO) clustering algorithm, PSO, and the Subtractive clustering algorithms on three different datasets. The results illustrate that the Subtractive + (PSO) clustering algorithm can generate the most compact clustering results as compared to other algorithms.
Dynamic Map and Diffserv Based AR Selection for Handoff in HMIPv6 Networks IJORCS
In HMIPv6 Networks, most of the existing handoff decision mechanisms deal mainly with the selection of Mobility Anchor Point (MAP), ignoring the selection of access router (AR) under each MAP. In this paper, we propose a new mechanism called “Dynamic MAP and Diffserv based ARs selection for Handoff in HMIPv6 networks” and it deals with selecting the MAP as well as ARs. MAP will be selected dynamically by checking load, session mobility ratio (SMR), Binding update cost and Location Rate. After selecting the best MAP, the Diffserv approach is used to select the AR under the MAP, based on its resource availability. The AR is implemented at the edge router of Diffserv. DiffServ can be used to provide low-latency to critical network traffic such as voice or streaming media while providing simple best-effort service to non-critical services such as web traffic or file transfers. By using this mechanism, we can assure that better resource utilization and throughput can be attained during Handoff in HMIPv6 networks.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Real-Time Multiple License Plate Recognition System
1. International Journal of Research in Computer Science
eISSN 2249-8265 Volume 4 Issue 2 (2014) pp. 11-17
www.ijorcs.org, A Unit of White Globe Publications
doi: 10.7815/ijorcs.42.2014.080
www.ijorcs.org
Real-Time Multiple License Plate Recognition System
Babak Azad1
, Eslam Ahmadzadeh2
1
Technical and Engineering College, University of Mohaghegh Ardabili, Ardebil, IRAN
Email: babak.babi72@gmail.com
2
Zand higher education Institute, Shiraz, IRAN
Email: ahmadzadeh1358@yahoo.com
Abstract: License plate recognition system is one of
the core technologies in intelligent traffic control. In
this paper, a new and tunable algorithm which can
detect multiple license plates in high resolution
applications is proposed. The algorithm to the
investigation and identification of the novel Iranian
and some European countries plate, characterized by
both inclusion of blue area on it and its geometric
shape. Obviously, the suggested algorithm contains
suitable velocity due to not making use of heavy pre-
processing operation such as image-improving filters,
edge-detection operation and omission of noise at the
beginning stages. So the method recommended here is
compatible with model-adaptation, i.e. using the very
blue section of the plate. The present method indicates
the fact that, if several plates are included in the
image, this method can successfully manage to detect
them. We evaluated our method on the two Persian
single vehicle license plate data set that we obtained
99.33, 99% correct recognition rate respectively.
Further we tested our algorithm on the Persian
multiple vehicle license plate data set and we achieved
98% accuracy rate. Also we obtained approximately
99% accuracy in character recognition stage.
Keywords: Multiple license plate recognition, real-
time; color space, pattern recognition
I. INTRODUCTION
Automatic license plate recognition plays an
important role in numerous real-life applications, such
as unattended parking lots, security control of
restricted areas, traffic law enforcement, congestion
pricing, and automatic toll collection [1-6]. In the most
of present methods, the conditions of environment and
plate, affect on the performance of the method,
therefore these methods have limitations. So, reaching
the methods that offer the acceptable results is
expected. A license plate recognition system generally
consists of three main parts: 1) license plate
recognition 2) characters segmentation 3) characters
recognition [7]. Among these stages, the license plate
recognition has a special sensitivity and is one of the
most difficult stages in this process. To detect the
region of car license plate, many techniques have been
used. In [8] combination of edge statistics and
mathematical morphology showed very good results,
but it is time consuming and because of this problem,
[9] uses block-base algorithm. In [10] a novel method
called "N row distance" is implemented. This method
scans an image with N row distance and counts the
existent edges. If the number of the edges is greater
than a threshold then the license plate is recognized, if
not threshold have to be reduced and algorithm will be
repeated. This method is fast and has good results for
simple images. Disadvantage of this paper is that the
edge based algorithms are sensitive to unwanted edges
such as noise edges, and they fail when they are
applied to complex images. A wavelet transform-based
algorithm is used in [11] for extraction of the
important features to be used for license plate location.
This method can locate more than one license plate in
an image. Methods which are symmetry based are
mentioned in [12].
In [13] the plate is a location with the black
background and white writings. In this way that,
firstly, takes the image into the HSI and applies the
capability of being black color of its background for
this purpose, it uses a mask and segments the image
according to HSI color intensity parameter and creates
a binary image. For canceling probable noises, it uses
the operation of erosion and dilation, then labels the
existing candidates and for canceling the candidates
which aren’t the location of plate, it applies the
geometric capability of the plate and other characters,
then for recognizing a primary candidate, it uses the
color intensity histogram, and recognizes the location
of plate.
The current paper aims at investigation into and
identification of the novel Iranian and some European
countries plate characterized by both inclusion of blue
area on it and its geometric shape. Figure 1 shows the
sample license plate of these countries. Obviously, the
suggested system contains suitable velocity due to not
making use of heavy pre-processing operation such as
image-improving filters, edge-detection operation and
omission of noise at the beginning stages. So, the
2. 12 Babak Azad, Eslam Ahmadzadeh
www.ijorcs.org
recommended method of ours is compatible with
model-adaptation, i.e., the very blue section of the
plate so that the present method indicated the fact that
if several plates are included in the image, the method
can successfully manage to detect it. In section two the
proposed algorithm is elaborated. In section three the
practical result of the paper and in section four,
conclusion is presented.
Figure 1: Sample of plates in some countries
a: Iran country b: France country
c: German country d: Polish country
II. PROPOSED METHOD
General diagram of the proposed algorithm is
shown in Figure 2.
Figure 2: General diagram of the proposed algorithm
Our Proposed Algorithm is based on pattern
recognition. The suggested algorithm is a robust and
tunable algorithm that can be used for detection any
kind of plate in the images. The algorithm needs two
parameters; pattern and test image. The pattern
parameter is used as an object to localizing in the test
image. In this research we considered Iranian license
plate as our patterns; Figure 1(a) shows these patterns.
For detection pattern on test image at first time, the
information such as Character Scheme Feature (CSF)
and Color Feature (CF) in pattern parameters is
computed. Then for finding the pattern (license plate)
in test image, first the test image is converted to the
HSV or L*A*B color spaces. Then instead of
processing whole image region, the image is broken to
list of preparatory zones and in order during frequent
process, zones are selected. The existence a SF of
pattern is investigated in it. For investigate of zones
only its lip pixel used, that are consisted of 23.44% of
zone pixels. Whenever a zone with pattern area is
found, by investigation its top, down and side blocks
and considering SF of pattern, the considerable place is
selected as a candidate and supplemented to candidate
region. Upper operation is continued to finishing of all
zones.
A. Extracting Pattern Information
In this section the nominate pattern information is
extracted for detection it in the test image. We
considered Iranian license plate as our patterns. For
obtaining statistical feature (SF) and character scheme
feature (CSF) we considered Iranian license plate as
two parts, Figure 3 shows these parts; and by Equation
(1) and Equation (2) we extracted the SF and CSF
feature respectively.
Figure 3: The CF and CSF parts of Iranian license plate
country
CF = RatioBlu epart
=
Hig htSF Region
Width SF Region
(1)
for each i ∈ Image. row (m)
JumpArray [i] = �[𝐼𝐼 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼(
𝑛𝑛−1
𝑗𝑗 =1
𝑖𝑖, 𝑗𝑗) 𝑋𝑋𝑋𝑋𝑋𝑋 𝐼𝐼 𝐼𝐼𝐼𝐼𝐼𝐼𝐼𝐼(𝑖𝑖, 𝑗𝑗 + 1)]
𝑒𝑒𝑒𝑒𝑒𝑒 𝑓𝑓𝑓𝑓𝑓𝑓
CSF.K= mean (Jump_Array )
CSF.T= Count (Jump_Array>CSF.K) (2)
3. Real-Time Multiple License Plate Recognition System 13
www.ijorcs.org
Where image is a pattern (like figure 1(a)) and m,n
are the size of pattern image.
B. HSV and L*A*B Color Space
Even although RGB color space is ideal for
monitor, it is unnatural for human being. For stance,
recognizing how to make a color lighter in RGB color
space is more difficult work. It is easier for human to
use hue, saturation and brightness features for
explanation [14]. The superior of this color space to
RGB, is lack of relation between producer elements
hue, saturation with brightness amount. Whereas plate
number recognition system is made by subjectivity that
human has from colors. So, use of suitable color space
is necessary for carefulness in work.
A Lab color space is a color-opponent space with
dimension L for lightness and A, B for the color-
opponent dimensions, based on nonlinearly
compressed CIE XYZ color space coordinates. This
color space is better suited to many digital image
manipulations than the RGB space, which is typically
used in image editing programs. In our investigation as
a practical result we achieved better result when we
used HSV color space rather than L*A*B.
C. Candidate Region Detection
For determining the plate location, initially the
input image is converted to the HSV color space. Then
the image is broken to zones in N*M size and that N
and M amount as a practical result is obtained in order
15,16. Figure 4(b) shows the result of operation of
HSV color space for the image entered. After creating
the lists from zones in order, evaluation starts from the
bottom corner and left hand image area as the blue
area lies in left hand and bottom corner. In evaluation
of each zone only its lip pixels that it consist 23.44%
of it are re-evaluated. If in the process, the blue pixel is
found the evaluation process would be done for the
whole pixel zone. Further, with the evaluation of it’s
upper and lower blocks we can find the steady blue
area, retrieving its width and height. If the width and
height retrieved of the blue area that is selected as a
pattern is SF (RatioBlu epart
), plate height is obtained
equally with theSF(HightSFRegion
). And its width is
obtained by increasing the SF(WidthSFRegion
)8 times.
Figure 4(c) shows the result.
Figure 4: (a): entrance image in RGB mode (b): image in
HSV mode (c): extracted plate SF region
By finding candidate area this area is added to plate
candidates list and increase blocks that are in this area
are omitted from preparatory blocks list and operation
is done on reminder blocks. In this algorithm the worst
state is happened if the plate isn’t in image or it is
scratched. In this state all blocks will be studied and
therefore 23.44% of image will be processed.
D. Plate Recognition
In this step, first the exploited candidates from last
step are labeled. And in a repeated process are
evaluated the number of color jump. If evaluation of a
candidate is successful and plate kind such as
governmental, public, private is specified, this
candidate considered as plate location and its tilt will
be resolved.
In this step by the use of color jump and color kind
of plate we determined that candidate as plate or not.
With regard to the plate area consists of successive 8
characters and its color violence change rate is more
than to other area we use these features for the plate
specifying. For determining of a color change range, in
every line the number of color change is counted from
white color to black color or inverse. If the number of
color change is more than CSF.K amount and
successive line numbered more than CSF.T, this area
as a plate area is considered. Figure 5 shows exploited
plate from entrance image.
Figure 5: The image of extracted candidate
E. Character Segmentation and Recognition
In this paper from last step, the area that is
exploited as a plate, first probable noising are solved,
then plate image is complemented till its writing of
plate inside is seen such white violence. Then this area
is labeled and through the available regions, the
regions that are bigger are stored as exploited
characters in 60*30 sizes. Figure 6(a) shows the
extracted plate after removing noise and Figure 6(b)
shows its histograms.
Figure 6: (a): extracted plate after removing the noise (b):
histogram of extracted plate
The extracted characters are then recognized and
the output is the license plate number. To recognition
the characters of car license plate, many techniques
have been used. In [15], the feature vector is generated
4. 14 Babak Azad, Eslam Ahmadzadeh
www.ijorcs.org
by dividing the binary character into blocks of 3×3
pixels. Then, the number of black pixels in each block
is counted. In [16], the feature vector is generated by
dividing the binary character after a thinning
operation into 3 × 3 blocks and counting the number of
elements that have 0°, 45°, 90°, and 135° inclination.
In [17], the character is scanned along a central axis.
This central axis is the connection between the upper
bound horizontal central moment and lower bound
horizontal central moment. Then the number of
transitions from character to background and spacing
between them form a feature vector for each character.
This method is invariant to the rotation of the character
because the same feature vector is generated. Template
matching is performed in [18] - [21] after resizing the
extracted character into the same size. Several
similarity measuring techniques are defined in the
literature. Some of them are Mahalanobis distance and
the Bayes decision technique [19], Jaccard value [20],
Hausdorff distance [21]. In [22] and [23] the feature
vector is generated by dividing the binary character
into blocks of pixels. Then, the angle and distance of
black pixels in each block is extracted.
In this system, we computed the features based on
chain-code directional frequencies of contour pixels of
the images as follows: First we found the bounding
box (minimum rectangle containing the hand gesture)
of each input image which is a two-tone image. Then
for better result and independency of features to size
and position (invariant to scale and translation), we
converted each image (located in bounding box) to a
normal size of 49×49 pixels. We chose this normalized
value based of various experiments and a statistical
study. In Figure 7(a), a normalized image with its
bounding box is shown. We extracted the contour of
the normalized image Figure 7(b).
Figure 7: (a): Bounding box of a normalized image (b):
Digit ‘5’ in Persian and its contour
We scanned the image contour horizontally by
keeping a window-map of size 7×7 on the image from
the top left most point to down right most point (49 no
overlapped blocks). For each block the chain code
frequencies for all 8 directions were computed (8
directions were shown in Figure 8(a)). Instead of
expressing the features in terms of 8 directions, we
have proposed to simplify the features into 4 sets
corresponding to 4 directions [Figure 8(b)]: i)
horizontal direction code (direction 0 and 4), ii)
vertical direction code (direction 2 and 6) iii) principal
diagonal direction code (direction 1 and 5) and iv) off
diagonal direction code (direction 3 and 7). Thus, in
each block, we got four values representing the
frequencies of these four directions and these values
were used as features (local contour direction values).
To extract features, we considered 49 (7×7) uniform
blocks in each image and we computed four features in
each block so we got 49×4=196 features for each
image.
Figure 8: (a): 8 direction code (b): 4 direction codes
obtained from 8 directions
F. Character Recognition by SVM
Support vector machines (SVMs) [24] are very
popular and powerful in pattern learning because of
supporting high dimensional data and at the same time,
providing good generalization properties. Moreover,
SVMs have many usages in pattern recognition and
data mining applications such as text categorization
[25], 3D object detection [26], face recognition [27].
At the beginning, SVM was formulated for two-class
(binary) classification problems and then it extended
two most popular group: one-against-all (OAA) and
the one-against-one (OAO). In this paper we used
OAA approach for character recognition stage.
III. RESULT AND IMPLEMENTATION
In this part the practical result of proposed method
for license plate recognition system compared with
contemporary methods are detailed. Our suggestive
method have been done on Intel Core i3-2330M CPU,
2.20 GHz with 2 GB RAM under Matlab environment.
Figure 9 shows the worked system.
Figure 9: our proposed license plate recognition system
5. Real-Time Multiple License Plate Recognition System 15
www.ijorcs.org
The suggestive method is robustness against
parameters such as: the different size and situation of
plate in image, the view of videotaping and different
light situation in videotaping, injuries and pollution of
plate.
A. Evaluation of License Plate Location Stage
For evaluation of our method, first, the data set that
is mentioned in [28] and [29] is considered. This data
set consists of 150 colorful images in 640*480 sizes.
These images are variety in point of view, good light
balance, various distances and various backgrounds.
The result of the proposed method for license plate
recognition compared with these methods is shown in
Table I.
TABLE I: Accuracy rate of proposed method on first
databases
Method
Correct
Plate
Recognition
Incorrect
plate
Recognition
Percent
Efficiency
R. Azad et al.
[28]
148 2 98.66%
S.H.M Kasaei
et al. [29]
146 4 97.30%
Our Method 149 1 99.33%
The second data set that we used for our proposed
method is mentioned in [7] consist of 100 images that
are captured by a 2 mega-pixel camera of mobile
phone (Nokia 5230) from front view of car. These
images are 640*480 sizes, RGB mode, variety in point
of view, various light condition, various distances and
backgrounds. The result of the proposed method that
applied on the second data set for license plate
recognition is shown in Table II.
TABLE II: Accuracy rate of proposed method on second
databases
Method
Correct
Plate
Recognition
Incorrect
plate
Recognition
Percent
Efficiency
R. Azad et al.
[7]
98 2 98%
Our Method 99 1 99%
According to the previous license plate recognition
approaches, there is not a popular database for multiple
license plate recognition system to evaluate the
performance of its methods. Especially for Iranian
vehicle data set, because most of the proposed
approach attempts to find single plate in the image. In
this respect, to prove the quality of proposed approach,
100 images of 3 mega-pixel resolution are captured
and used by our team form front, back and side views
of the cars. These images are of diverse sizes, RGB
mode, variety in point of view; various light
conditions, various distances, complex backgrounds
and contain more than one car. The result of the
proposed method that applied on the third data set for
license plate recognition is shown in Table III.
TABLE III: Accuracy rate of proposed method on third
databases
Number
of Car
in each
image
Number
of images
Whole
Number
of
License
Plates
Correct
Plate
Recognition
Percent
Efficiency
Two
cars
50 100 99 99%
Three
cars
50
150 146 97.33%
B. Evaluation of Character Recognition Stage
In the table IV, our method is compared with
normal factoring method represented in [14], K-
Nearest- Neighbor (KNN) method [7] and template
matching mentioned in [29] that all of them used first
dataset for evaluation of their works.
TABLE IV: Accuracy rate of proposed on character
recognition stage
Total
character
Images
Method
Correct
Recognition
Efficiency
1200
R. Azad et al. [7] 1188 99%
R. Azad et al.
[14]
1164 97%
S.H.M Kasaei et
al. [29]
1104 92%
Proposed method 1194 99.50%
Further we achieved 100% and 98% accuracy rate
respectively when we evaluated our method on second
and third data set. Table V shows the information
process of our method.
TABLE V: Information process of the proposed method
PROCESS
INFORMATION
Minimum Maximum Average
Process Time for
License Plate
Recognition
0.012110 0.066235 0.030123
Number of Detected
Candidate
1 7 3
Figure 10 shows some of the detection results,
where the license plates are circled by white boxes.
From the examples, we may see that our algorithm can
detect the license plates with various sizes, positions
and colors from various backgrounds.
6. 16 Babak Azad, Eslam Ahmadzadeh
www.ijorcs.org
Figure 10: Detection results of some license plate by the
proposed method
IV. CONCLUSION AND FUTURE WORK
In this paper, a new and tunable algorithm which
can detect multiple license plates in high resolution
applications is proposed. For detection license plate on
test image at first time, the information such as
character scheme feature (CSF) and statistical feature
(SF) in pattern parameters is computed. Then for
finding the pattern (license plate) in test image, first
the test image is converted to the HSV or L*A*B color
spaces. Then instead of processing whole image
region, the image is broken to list of preparatory zones
and in order during frequent process, zones are
selected. The existence a SF of pattern is investigated
in it. For investigate of zones only its lip pixel used,
that are consisted of 23.44% of zone pixels. Whenever
a zone with pattern area is found, by investigation its
top, down and side blocks and considering SF of
pattern, the considerable place is selected as a
candidate and supplemented to candidate region.
Finally by color jump and CFS testing the real plate
location is extracted. We evaluated our method on the
two Persian single vehicle license plate data set that we
obtained 99.33, 99% correct recognition rate
respectively. Further we tested our algorithm on the
Persian multiple vehicle license plate data set and we
achieved approximately 98% accuracy rate. Also we
obtained approximately 99% accuracy in character
recognition stage. This work is implemented for still
images, for future work we have planned to extend it
for license plate detection and recognition in video
stream.
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How to cite
Babak Azad, Eslam Ahmadzadeh, “Real-Time Multiple License Plate Recognition System”. International Journal of
Research in Computer Science, 4 (2): pp. 11-17, March 2014. doi: 10.7815/ijorcs.42.2014.080