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Technique of Automatic Orientation of Car License Plate Targets

YANG Wei-ping,LI Ji-cheng,SHEN Zhen-kang,

中国图象图形学报 , 2002,
Abstract: The issue of car license plate recognition is a focus direction of studying both at home and abroad at present, its success has important application values in vehicle controlling, transportation management, parking and so-so. There are many papers published in the research domain. In order to solve the primary problem of the car license plate recognition--Automatic orientation technology of the car license plates, a method of automatic detection and orientation of car license plate based on license plate's projection invariability in the condition of lesser deflection of car license is presented in terms of the imaging characteristics of the car license plate target, which can succeed in detecting and orienting the car license plate from the complicated background. Tested actually through the scene, the method obtains satisfactory localization effect. In the end of the paper, some experimental results are given out. In virtue of the successful car license plate detection and localization, it is possible for license plate number extraction and recognition.
A Malaysian Vehicle License Plate Localization and Recognition System
Ganapathy Velappa,Dennis LUI Wen Lik
Journal of Systemics, Cybernetics and Informatics , 2008,
Abstract: Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In this paper, a license plate localization and recognition system for vehicles in Malaysia is proposed. This system is developed based on digital images and can be easily applied to commercial car park systems for the use of documenting access of parking services, secure usage of parking houses and also to prevent car theft issues. The proposed license plate localization algorithm is based on a combination of morphological processes with a modified Hough Transform approach and the recognition of the license plates is achieved by the implementation of the feed-forward backpropagation artificial neural network. Experimental results show an average of 95% successful license plate localization and recognition in a total of 589 images captured from a complex outdoor environment.
License Plate Recognition (LPR) system for Indian Vehicle License Plate Extraction and Character Segmentation.  [PDF]
Surabhi Mohindra,Dr. Shailja Shukla
International Journal of Engineering Sciences & Research Technology , 2013,
Abstract: License Plate Recognition (LPR) is a challenging area of research due to its importance to variety of commercial applications. LPR systems are widely implemented for automatic ticketing of vehicles at car parking area, tracking vehicles during traffic signal violations and related applications with huge saving of human energy and cost. The overall problem may be subdivided into three distinct key modules: (a) localization of license plate from vehicle image, (b) segmentation of the characters within the license plate and (c) recognition of segmented characters within the license plate. In this paper, we proposed a method of feature extraction[12] for an offline License Plate Recognition System based on global features to identify the license plates. Before extracting the features, preprocessing[11] of the captured image is necessary in order to isolate the license plate region from the car backround and to remove the noise present, using filter[2]. Sobel edge detection e technique [1][7] is used to determine the edges of the license plate whereas the features are extracted using Radon transform[10]. Features are saved and tested against already saved database and the availability of the vehicle is displayed as an output .In this work, 100 real time vehicle images are captured from a high resolution camera during different contrast of day. The images are stored in a centralized data server.A sample of 20 images are tested against the already saved database in order to check the authenticity of each vehicle. The performance of the system is measured at the time of recognition which is 95 % and at the time of matching i.e checking the existence of a particular vehicle is 90% in a time duration of 15 sec.
An intelligent control system using an efficient License Plate Location and Recognition Approach
Saeed Rastegar,Reza Ghaderi,Gholamreza Ardeshir,Nima Asadi
International Journal of Image Processing , 2009,
Abstract: This paper presents a real-time and robust method for license plate location andrecognition. After adjusting the image intensity values, an optimal adaptive threshold isfound to detect car edges and then the algorithm uses morphological operators to makecandidate regions. Features of each region are to be extracted in order to correctlydifferentiate the license plate regions from other candidates. It was done by analysis ofpercentage of Rectangularity of plate. Using color filter makes the algorithm more robuston license plate localization (LPL). The algorithm can efficiently determine and adjustthe plate rotation in skewed images. The Binary unit uses Otsu method to find theoptimal adaptive threshold corresponding to the intensity of image. To segment thecharacters of the license plate, a segmentation algorithm based on the profile isproposed. In the following, an optical character recognition (OCR) engine has then beenproposed. The OCR engine includes characters dilation, resizing input vector of ArtificialNeural Network (ANN). To recognize the characters on the plates, Multi layerPerceptron (MLP) has been used and compared with Hopfield, Linear VectorQuantization (LVQ) and Redial Basis Function (RBF). The results show that MLPoutperforms. According to the results, the performance of the proposed system is bettereven in case of low-quality images or images with illumination effects and noise.
An Efficient Method for Vehicle License Plate Detection in Complex Scenes  [PDF]
Mahmood Ashoori Lalimi, Sedigheh Ghofrani
Circuits and Systems (CS) , 2011, DOI: 10.4236/cs.2011.24044
Abstract: In this paper, we propose an efficient method for license plate localization in the images with various situations and complex background. At the first, in order to reduce problems such as low quality and low contrast in the vehicle images, image contrast is enhanced by the two different methods and the best for following is selected. At the second part, vertical edges of the enhanced image are extracted by sobel mask. Then the most of the noise and background edges are removed by an effective algorithm. The output of this stage is given to a morphological filtering to extract the candidate regions and finally we use several geometrical features such as area of the regions, aspect ratio and edge density to eliminate the non-plate regions and segment the plate from the input car image. This method is performed on some real images that have been captured at the different imaging conditions. The appropriate experimental results show that our proposed method is nearly independent to environmental conditions such as lightening, camera angles and camera distance from the automobile, and license plate rotation.
License Plate Recognition System Based on Color Coding Of License Plates  [PDF]
Jani Biju Babjan
Computer Science , 2015,
Abstract: License Plate Recognition Systems are used to determine the license plate number of a vehicle. The current system mainly uses Optical Character Recognition to recognize the number plate. There are several problems to this system. Some of them include interchanging of several letters or numbers (letter O with digit 0), difficulty in localizing the license plate, high error rate, use of different fonts in license plates etc. So a new system to recognize the license plate number using color coding of license plates is proposed in this paper. Easier localization of license plate can be done by searching for the start or stop patters of license plates. An eight segment display system along with traditional numbering with the first and last segments left for start or stop patterns is proposed in this paper. Practical applications include several areas under Internet of Things (IoT).
Vehicle License Plate Recognition Syst  [PDF]
Meenakshi,R. B. Dubey
International Journal of Advanced Computer Research , 2012,
Abstract: The vehicle license plate recognition system has greater efficiency for vehicle monitoring in automatic zone access control. This Plate recognition system will avoid special tags, since all vehicles possess a unique registration number plate. A number of techniques have been used for car plate characters recognition. This system uses neural network character recognition and pattern matching of characters as two character recognition techniques. In this approach multilayer feed-forward back-propagation algorithm is used. The performance of the proposed algorithm has been tested on several car plates and provides very satisfactory results.
A Simple and Efficient Algorithm for License Plate Localization

GONG Cheng-Qing,

计算机系统应用 , 2011,
Abstract: License plate location is one of the key technologies in license plate recognition system.By preprocessing the license plate image to remove the interference noise,this paper uses the method of interlaced scanning and the mothod of rectangular window searching to location the license plate's top boder,bottom boder,left boder and right boder.So it greatly improves the speed of license plate location.This paper also proposes that the changing of location area can judge the tilt condition of the license plate ...
Vehicle License Plate Recognition Based on Text-line Construction and Multilevel RBF Neural Network  [cached]
Baoming Shan
Journal of Computers , 2011, DOI: 10.4304/jcp.6.2.246-253
Abstract: License plate localization and character segmentation and recognition are the research hotspots of vehicle license plate recognition (VLPR) technology. A new method to VLPR is presented in this paper. In license plate localization section, Otsu binarization is operated to get the plate-candidates regions, and a text-line is constructed from the candidate regions. According to the text-line construction result and the characteristics of the license plate character arrangement, the license plate location will be determined. And then the locally optimal adaptive binarization is utilized to make more accurate license plate localization. After the license plate localization, the segment method of vertical projection information with prior knowledge is used to slit characters and the statistical features are extracted. Then the multilevel classification RBF neural network is used to recognize characters using the feature vector as input. The results show that this method can recognize characters precisely and improve the ability of license plate character recognition effectively.
Saudi License Plate Recognition  [PDF]
Saleh Basalamah
International Journal of Computer and Electrical Engineering , 2013, DOI: 10.7763/ijcee.2013.v5.649
Abstract: Automatic license plate recognition systems (LPR)can help reduce the number of traffic violations and make ourstreets safer. In this project we developed an automatic systemthat locates Saudi license plates in a captured image regardlessof the time of day or license plate scale. The proposed systemcan tolerate slight tilting of the license plate. The localizationprocess is fairly complex due to the highly varying nature of thebackground. Good results were obtained using the localizationstage. A second part of the system was developed to segmentand recognize the characters in the located license plate.
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