• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3683-3693
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• 1999

Most recognition methods of car licence plate have difficulties concerning plate recognition rates and system stability in that restricted car images are used and good image capture environment is required. To overcome these difficulties, I proposed a new recognition method of car licence plates, in which both intensity variation and color information are used. For a captured car image, multiple candidate plate-bands are extracted based on the number of intensity variation. To have an equal performance on abnormally dark and bright Images. plate lightness is calculated and adjusted based on the brightness of plate background. Candidate plate regions are extracted using contour following on plate color pixels in oath plate band. A candidate region is decided as a real plate region after extracting character regions and then recognizing them. I recognize characters using template matching since total number of possible characters is small and they art machine printed. To show the efficiency of the proposed method, I tested it on 200 car images and found that the method shows good performance.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.131-141
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• 2012

This paper proposes a method of analyzing unrecognizable numbers of license plate images, which are degraded by various factors such as low resolution, low light level, geometric distortion, and periodic noise, to name a few. With existing vehicle license plate recognition methods, it is difficult to recognize license plate if images are not recognizable in the pre-process of removing degradation factors. Although images of license plate have not been improved to be recognizable in the pre-process, the proposed method makes it possible to recognize numbers of license by distorting pre-saved reference images of license plate numbers same as sample plates, and by assuming likelihood ratio using statistical methods. The proposed method also makes it possible to identify suspect vehicle license plate under unstable light conditions and with low resolution images that are unrecognizable by the naked eye. This method has been used in real criminal investigation to recognize numbers of license plate of criminal vehicle, and has proved to be useful as criminal evidence through experiments under various conditions.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.423-431
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• 2016

In general LPR(License Plate Recognition) in outdoor image is not so simple differently from in the image captured from manmade environment, because of geometric shape distortion and large illumination changes. this paper proposes three techniques for LPR in outdoor images captured from CCTV. At first, a serially connected multi-stage Adaboost LP detector is proposed, in which different complementary features are used. In the proposed detector the performance is increased by the Haar-like Adaboost LP detector consecutively connected to the MB-LBP based one in serial manner. In addition the technique is proposed that makes image processing easy by the prior determination of LP type, after correction of geometric distortion of LP image. The technique is more efficient than the processing the whole LP image without knowledge of LP type in that we can take the appropriate color to gray conversion, accurate location for separation of text/numeric character sub-images, and proper parameter selection for image processing. In the proposed technique we use DBN(Deep Belief Network) to achieve a robust character recognition against stroke loss and geometric distortion like slant due to the incomplete image processing.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1708-1714
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• 2010

In this paper, the full color LED billboard or a general quality improvement methods of quality gamma correction, brightness, and brightness adjustment, etc., regardless of the overall color of images uniformly bright or dark have been taken care of. The video itself, but simply expressed as a uniform brightness of a certain size, how to adjust the brightness of input video signal does not reflect the characteristics of the entire screen with just a lighter or darker line is only feeling was brought. So, unlike conventional video transmission system with new LED display technology in the histogram analysis of image data is input by the input image data by determining the luminance values of the attributes are reflected, as appropriate based on the histogram of the distribution of brightness values By controlling the LED display is expressed in the uniform image can improve the brightness control, histogram distribution of the image as full color billboards driven processing technology is proposed.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.15-25
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• 2002

This paper proposes a vehicle license plate recognition system, which has relatively a simple structure and is highly tolerant of noise, by using the DCT(Discrete Cosine Transform) coefficients extracted from the character region of a license plate and the LVQ(Learning Vector Quantization) neural network. The image of a license plate is taken from a captured vehicle image based on RGB color information, and the character region is derived by the histogram of the license plate and the relative position of individual characters in the plate. The feature vector obtained by the DCT of extracted character region is utilized as an input to the LVQ neural classifier fur the recognition process. In the experiment, 109 vehicle images captured under various types of circumstances were tested with the proposed method, and the relatively high extraction rate of license plates and recognition rate were achieved.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.416-421
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• 2008

This paper realizes a system that recognizes traffic safety signs by applying the principle used for game in reverse. The game used for this paper is one that expresses the shape of temporary objects intended by the maker when the maker sees the numerical image provided on (x, y) coordinates and then expresses it on the mesh. After separating the traffic safety sign image from the input image, the system is realized by outputting the content of the sign into letters by recognizing the forms and colors constituting the sign using the puzzle game above. Our system has fast process time and better rate of recognition than the existing system with black-and-white image processing and recognition without any penciling progress.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.524-526
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• 1999

본 논문은 환경에 독립적인 자동차 영상에서 자동차 번호판 영역을 추출하는 방법을 제안하고 실험 결과를 기술한다. 번호판 주위환경에는 다양한 조건이 존재하며 이에 적응성을 가지고 빠른 추출을 수행하는 것은 매우 중요한 문제이다. 본 논문은 이러한 문제를 해결하기 위해 HSI 컬러 모델에 기반하여 번호판을 면밀히 분석하여 번호판을 유형별로 그룹화하고, 지역 분할 및 병합을 통해 빠른 시간안에 번호판 후보 영역을 검색한다. 그리고 번호판이 갖는 특성을 이용하여 후보 영역에서 번호판 영역임을 검증함으로써 자동차 번호판 영역을 찾는다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.04a
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• pp.457-462
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• 2000

교통 법규 위반 단속이나 주차 관리를 위한 차량 번호판 인식 시스템을 구현하기 위해서는 크게 차량 번호판 추출, 문자 분할, 문자 인식의 세부분으로 이루어진다. 본 논문에서는 차량 번호판 인식 시스템의 구현을 위해 번호판 영역의 색상정보를 이용하여 차량 번호판을 추출하는 방법을 제안하고, 번호판 영역 문자들의 사전 정보와 색상성분을 사용하여 정확하게 번호판 문자 분할을 하는 방법을 제안한다. 자가용과 영업용 차량 영상을 주간/dirks 및 정면/후면으로 나누어 다양하게 취득하여 실험한 결과, 94.6%의 번호판 추출률과 86.8%의 문자분할률을 얻었다.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.71-77
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• 2011

In this paper, we propose a learning based super resolution algorithm using local block for image enhancement of vehicle license plate. Local block is defined as the minimum measure of block size containing the associative information in the image. Proposed method essentially generates appropriate local block sets suitable for various imaging conditions. In particular, local block training set is first constructed as ordered pair between high resolution local block and low resolution local block. We then generate low resolution local block training set of various size and blur conditions for matching to all possible blur condition of vehicle license plates. Finally, we perform association and merging of information to reconstruct into enhanced form of image from training local block sets. Representative experiments demonstrate the effectiveness of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1361-1362
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• 2015

차량의 수요가 증가함에 따르는 지능적인 통제시스템의 요구된다. 그리고 과학기술의 발달과 시스템의 자동화에 따라 사람뿐만 아니라 차량도 인식이 필요하게 되었다. 따라서 본 논문은 다항식 기반 RBFNNs를 이용하여 차량의 번호판 인식을 수행한다. 번호판 영역과 번호는 영상처리에서 영상 이진화와 영상 모폴로지 기법 등 전처리 과정을 거친 후 검출하고, 차량 번호를 인식하기 위해 0~9사이의 숫자를 클래스 별로 데이터의 차원을 축소시켜 다항식 기반 RBFNNs에 학습하고, 테스트 차량의 번호판에서 번호별로 분류하여 차량번호를 인식한다.