After Reading A tons of papers, Here i present Review of Some Relevant Papers. It will help anyone to get an great idea on License Plate Recognition System. If you have any query about this slide you can directly mail me. Thank You.
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.
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.
An overview of gradient descent optimization algorithms Hakky St
勾配降下法についての論文をスライドにしたものです。
This is the slide for study meeting of gradient descent.
I use this paper and this is very good information about gradient descent.
https://arxiv.org/abs/1609.04747
This model is proposed to Automatically detect the number plate of vehicles. It uses YOLO You Look Only Once algorithm in order to detect the license plate. It takes the image as an input and puts it through Neural Network , then gives the output with bounding boxes. The method proposed here have some benefits over the traditional methods of detection of object. Yolo is really fast and efficient to handle detection of objects and it detects objects at a high speed up to 155 frames per second. Importance of automatically detecting number plate is that there are many fraud activities happening around us, to eliminate this mainly and then, also to retrieve vehicle details later after detecting the number plate. It detects the number plate and then make recognition or identify the license plate from the source image, which is called as image processing. This also works for number plates of different regions, it can detect for both grayscale as well as colour images. Also images can be captured by webcam and license plate can be detected. Number plates maybe broken sometimes, this model detects for broken ones also. It is also practical because of the low computational cost. It also has high accuracy and real time performance. Anagha Jayakumar TN | Dr. S. K Manju Bargavi "Detection of Number Plate using Yolo" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41286.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/41286/detection-of-number-plate-using-yolo/anagha-jayakumar-tn
Ever wondered how computers recognize and track human faces? Netlighter Saksham Gautam held a talk at Netlight Grand Edge Data Munich and dissected this seemingly complex problem of object recognition and tracking into digestible pieces. You will get a good understanding of what happens behind the scenes when, for instance, you walk through automatic passport control at the airport, or how Google's self driven car 'sees' the road signs. We will see how these generic algorithms and techniques can be applied to other machine learning and pattern recognition problems as well.
Automatic number plate recognition using matlabChetanSingh134
The project is based on Image processing.It basically detects the number plate while following an algorithm based on image processing.It does that by following certain steps like image detection, character segmentation, OCR, and template matching.Have a look at the ppt and you will understand each step clearly
With so much of our lives computerized, it is vitally important that machines and humans can understand one another and pass information back and forth. Mostly computers have things their way we have to & talk to them through relatively crude devices such as keyboards and mice so they can figure out what we want them to do. However, when it comes to processing more human kinds of information, like an old-fashioned printed book or a letter scribbled with a fountain pen, computers have to work much harder. That is where optical character recognition (OCR) comes in. Here we process the image, where we apply various pre-processing techniques like desk wing, binarization etc. and algorithms like Tesseract to recognize the characters and give us the final document. T.Gnana Prakash | K. Anusha"Text Extraction from Image using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd2501.pdf http://www.ijtsrd.com/computer-science/simulation/2501/text-extraction-from-image-using-python/tgnana-prakash
camera-based Lane detection by deep learningYu Huang
lane detection, deep learning, autonomous driving, CNN, RNN, LSTM, GRU, lane localization, lane fitting, ego lane, end-to-end, vanishing point, segmentation, FCN, regression, classification
License Plate Recognition Using Python and OpenCVVishal Polley
License Plate Recognition Systems use the concept of optical character recognition to read the characters on a vehicle license plate. In other words, LPR takes the image of a vehicle as
the input and outputs the characters written on its license plate.
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.
An overview of gradient descent optimization algorithms Hakky St
勾配降下法についての論文をスライドにしたものです。
This is the slide for study meeting of gradient descent.
I use this paper and this is very good information about gradient descent.
https://arxiv.org/abs/1609.04747
This model is proposed to Automatically detect the number plate of vehicles. It uses YOLO You Look Only Once algorithm in order to detect the license plate. It takes the image as an input and puts it through Neural Network , then gives the output with bounding boxes. The method proposed here have some benefits over the traditional methods of detection of object. Yolo is really fast and efficient to handle detection of objects and it detects objects at a high speed up to 155 frames per second. Importance of automatically detecting number plate is that there are many fraud activities happening around us, to eliminate this mainly and then, also to retrieve vehicle details later after detecting the number plate. It detects the number plate and then make recognition or identify the license plate from the source image, which is called as image processing. This also works for number plates of different regions, it can detect for both grayscale as well as colour images. Also images can be captured by webcam and license plate can be detected. Number plates maybe broken sometimes, this model detects for broken ones also. It is also practical because of the low computational cost. It also has high accuracy and real time performance. Anagha Jayakumar TN | Dr. S. K Manju Bargavi "Detection of Number Plate using Yolo" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41286.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/41286/detection-of-number-plate-using-yolo/anagha-jayakumar-tn
Ever wondered how computers recognize and track human faces? Netlighter Saksham Gautam held a talk at Netlight Grand Edge Data Munich and dissected this seemingly complex problem of object recognition and tracking into digestible pieces. You will get a good understanding of what happens behind the scenes when, for instance, you walk through automatic passport control at the airport, or how Google's self driven car 'sees' the road signs. We will see how these generic algorithms and techniques can be applied to other machine learning and pattern recognition problems as well.
Automatic number plate recognition using matlabChetanSingh134
The project is based on Image processing.It basically detects the number plate while following an algorithm based on image processing.It does that by following certain steps like image detection, character segmentation, OCR, and template matching.Have a look at the ppt and you will understand each step clearly
With so much of our lives computerized, it is vitally important that machines and humans can understand one another and pass information back and forth. Mostly computers have things their way we have to & talk to them through relatively crude devices such as keyboards and mice so they can figure out what we want them to do. However, when it comes to processing more human kinds of information, like an old-fashioned printed book or a letter scribbled with a fountain pen, computers have to work much harder. That is where optical character recognition (OCR) comes in. Here we process the image, where we apply various pre-processing techniques like desk wing, binarization etc. and algorithms like Tesseract to recognize the characters and give us the final document. T.Gnana Prakash | K. Anusha"Text Extraction from Image using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-6 , October 2017, URL: http://www.ijtsrd.com/papers/ijtsrd2501.pdf http://www.ijtsrd.com/computer-science/simulation/2501/text-extraction-from-image-using-python/tgnana-prakash
camera-based Lane detection by deep learningYu Huang
lane detection, deep learning, autonomous driving, CNN, RNN, LSTM, GRU, lane localization, lane fitting, ego lane, end-to-end, vanishing point, segmentation, FCN, regression, classification
License Plate Recognition Using Python and OpenCVVishal Polley
License Plate Recognition Systems use the concept of optical character recognition to read the characters on a vehicle license plate. In other words, LPR takes the image of a vehicle as
the input and outputs the characters written on its license plate.
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.
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.
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%.
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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.
Vehicle Number Plate Recognition using MATLABAI Publications
The VPR (Vehicle Number plate Recognition) system is based on image processing technology. It is one of the necessary systems designed to detect the vehicle number plate. In today’s world with the increasing number of vehicle day by day it’s not possible to manually keep a record of the entire vehicle. With the development of this system it becomes easy to keep a record and use it whenever required. The main objective here is to design an efficient automatic vehicle identification system by using vehicle number plate. The system first would capture the vehicles image as soon as the vehicle reaches the security checking area. The captured images are then extracted by using the segmentation process. Optical character recognition is used to identify the characters. The obtained data is then compared with the data stored in their database. The system is implemented and simulated on MATLAB and performance is tested on real images. This type of system is widely used in Traffic control areas, tolling, parking area .etc. This system is mainly designed for the purpose of security system. Basically video surveillance system is used for security purpose as well as monitoring systems. But Detection of moving object is a challenging part of video surveillance. Video surveillance system is used for Home security, Military applications, Banking /ATM security, Traffic monitoring etc. Now a day’s due to decreasing costs of high quality video surveillance systems, human activity detection and tracking has become increasingly in practical. Accordingly, automated systems have been designed for numerous detection tasks, but the task of detecting illegally parked vehicles has been left largely to the human operators of surveillance systems. The detection of Indian vehicles by their number plates is the most interesting and challenging research topic from past few years.
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.
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Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
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Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
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introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
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adversary training.
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5. Advanced License Plate Recognition System For Car Parking
Resize Image RGB->GRAY Adaptive Threshold
Canny Edge Detector
Contours(Hystersis
Thresholding)
Connected
Component Analysis
Pixel Gradient
6. Vehicle Number Plate Recognition System: A Literature Review and
Implementation using Templete Matching
Original Image Gray Image Threshold
Find Rectengle (7:3)Median Filter
Bounding Box of
Characters
7. Bangla License Plate Reader for Metropolitan Cities of Bangladesh
Using Template Matching
8. EDGE DETECTION OF LICENSE PLATE USING SOBEL OPERATOR
Original Image
Convolve with Filter
Horizontal Mask
Vertical Mask
Calculation of G =√(horizontal convolution ^2 +
Vertical convolution^2)
9. Development of an Automatic Vehicle License Plate Detection and
Recognition System for Bangladesh
Original Image Contrast Enhacement Sobel Edge Detector
Noise Removal
Find
Rectangle(1.6~2.15)
Find Possible Plates
based on edges
Each Plates are
Examined Further
Least Square based
skew detection
Connected Object
Detection-> Pixel
Connection