• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.122-130
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• 2009

Conventional approaches for car number plate detection have dealt with those input images having similar sizes and simple background acquired under well organized environment. Thus their performance get reduced when input images include number plates with different sizes and when they are acquired under different lighting conditions. To solve these problem, this paper proposes a new scheme that uses the geometrical features of number plates and their topological information with reference to other features of the car. In the first step, those edges constructing a rectangle are detected and several pixels neighboring those edges are selected as the seed pixels for region growing. For region growing, color and intensity are used as the features, and the result regions are merged to construct the candidate for a number plate if their features are within a certain boundary. Once the candidates for the number plates are generated then their topological relations with other parts of the car such as lights are tested to finally determine the number plate region. The experimental results have shown that the proposed method can be used even for detecting small size number plates where characters are not visible.

• The Journal of the Korea Contents Association
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• v.4 no.3
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• pp.125-130
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• 2004

This paper proposes a method of the car license plate recognition from digital camera image. Lots of technology advancement has been accomplished for the least several years. The key issue for recognition rate improvement has been the extraction of correct area on the plate. In the previous studies, the information from an edge or an color on a plate hasn't been used but some declination also taken into account in most cases due to the difficulty of area extraction on a tilted plate The proposed method focuses on transforming a slant plate image to the normalized form to be recognized. It shows good robustness on situations defined by a variety of locations, slants and heights of the license plate, because it detects the edge of license plate by using both the color information and linear regression method. The computer simulation shows that the proposed method records 92％ detection rates of license plate and can recognize characters of slant plate with about 50 degrees.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.181-184
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• 2009

본 논문은 번호판 내 명암도 대비를 이용한 자동차 번호판 검출 기법을 제안한다. 평균값 필터와 라플라시안 필터를 사용하여 영상의 잡음을 제거하는 동시에 에지 성분을 향상시킨 후 조명 환경 변화에 강인한 번호판 내 명암도 대비 특징을 이용하여 문자 후보를 검출한다. 다음으로 검출된 문자 후보가 열을 이루는 텍스트 후보를 검출하고, 이 영역을 Otsu 이진화 기업을 사용하여 x축에 투영하였을 시 나타나는 패턴을 평가함으로써 최종적으로 자동차 번호판을 검출하게 된다. 제안하는 기법의 성능을 평가하기 위해 다수의 데이터를 사용하여 실험하였고, 이를 분석하여 제안하는 기법의 우수성을 검증하였다.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.07a
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• pp.303-306
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• 2003

본 논문은 비밀번호 인증의 신뢰성 강화에 관한 연구로서 비밀번호 인증의 취약성과 공격방식을 살펴보고 이에 대한 신뢰성 강화 방안을 제시한다. 본 논문은 비밀번호 인증 처리에 있어서 사용자와 시스템간의 상호인증 방법을 제시하여 사용자가 알아차리지 못하는 사이에 중요 정보가 유출되는 것을 방지하며, 커널 수준에서 접근제어 기능을 제공하여 트로이 목마 유형의 공격으로부터 인증 처리 프로세스를 보호함으로서 기존의 비밀번호 인증 처리의 신뢰성을 향상하였다. 본 논문은 비밀번호 인증의 신뢰성을 강화하기 위해 비밀번호 자체의 보호를 강조하던 기존의 연구들과 달리 인증 처리 프로세스를 보호할 수 있는 메커니즘을 제안한다. 또한, 실험을 통한 검증을 이용하여 연구 결과의 정당성을 뒷받침하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05a
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• pp.639-642
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• 2003

차량의 수가 급격히 증가함에 따라 보다 지능적인 번호판 자동인식체계가 요구된다. 따라서 본 논문은 주행하는 차량에서 기울어진 번호판을 포함한 효율적인 자동차 번호판 인식방법을 제안하였다. 실험결과로서 일반적인 환경에서 획득된 인식 비율은 약 99%의 높은 성공률을 나타내었으며, 번호판이 차량에 비례하여 많이 기울어지게 위치해 있을 경우에도 97%의 성공률을 나타내었다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.1
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• pp.29-35
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• 2009

In this paper by using the image taken from the rear of the vehicle to effectively extract the license plate and how to recognize the characters appearing in the offer. How to existing research on the entire video by following the pre-edge (edge) images to obtain yijinhwa. Qualified heopeu in a binary image (Hough) to convert the horizontal and vertical lines to obtain, using the characteristics of the plates to extract the license plate area. The problem with this method, the processing time is so difficult to handle real-time status of irregular points, and visual contrast with yagangwan border does not appear in the plates to extract the license plate area is that it is not. In addition, the rear of the vehicle license plate area from images taken using the characteristics of the plates myeongamgap changes sutjapok in the area, background area and the number number area of the region confirmed the contrast of the car and identified the number and the number of 42 of distance to extract the license plate area. How to research, the existing damage to the border of the plate to fail to extract the license plate area, a matter of hours to resolve problems in real-time, practical application is processed. Chapter 100 as the results of the experiment the sample video image in a car that far experiment results automatically read license plates have been able to extract the license plate and failing to represent 13% of images, character recognition result of failing to represent the image was 0.4%

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.381-384
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• 2008

요즈음 교통사고를 줄이기 위하여 IT 기술을 이용한 교통사고 연구가 많이 진행되고 있다. 그러나, 뺑소니 교통사고 발생하면 가해차량을 현장에서 찾기가 매우 어렵다. 본 논문에서는 이러한 문제점을 해결하기위해서 RFID TAG를 이용해서 뺑소니 교통사고가 발생할 경우에 차량에 내장된 RFID 리더기가 상대방 차량의 차량번호를 인식할 수 있는 모의실험을 하였다. 뿐만 아니라, PDA를 이용한 인터넷 기반에서 교통사고가 발생한 경우에 현장에서 운전자가 교통사고현장 자료 및 운전자 인적사항을 경찰서나 보험회사에 전송할 수 있는 SW를 모의실험 하였다. 모의실험결과 통과차량속도가 저속인 경우에는 70%이상 차량번호를 익식할 수 있음을 확인하였다.

• Journal of Korea Multimedia Society
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• v.11 no.11
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• pp.1515-1524
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• 2008

This paper proposes a method that detects a license plate in complex background using a multiple-color model and character layout information. A layout of a green license plate is different from that of a white license plate. So, this study used a strategy that firstly assumes the plate color and then utilizes its layout information. At first, it extracts green areas from an input image using a multiple-color model which combined HIS and YIQ color models with RGB color model. If green areas are detected, it searches the character layout of the green plate by analyzing the connected components in each areas. If not detected, it searches the character layout of the white plate in all area. Finally, it extracts a license plate by grouping the connected components which corresponds to characters. Experimental result shows that 98.1% of 419 input images are correctly detected. It also shows that the proposed method is robust against illumination, shadow, and weather condition.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.239-245
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• 2017

For privacy protection, we propose a vehicle license plate region detection method in road view image served from portal site. Because vehicle license plate regions in road view images have different feature depending on distance, long distance vehicle license plate regions are not detected by feature of low resolution. Therefore, we suggest a method to detect short distance vehicle license plate regions by edge feature and long distance vehicle license plate regions using MSER feature. And then, we select candidate region of vehicle license plate region from detected region of each method, because the number of the vehicle license plate has a structural feature, we used it to detect the final vehicle license plate region. As the experiment result, we got a recall rate of 93%, precision rate of 75%, and F-Score rate of 80% in various road view images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.1987-1996
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• 2009

Recently, the color of vehicle license plate has been changed from green to white. Thus the vehicle plate recognition system used for parking management systems, speed and signal violation detection systems should be robust to the both colors. This paper presents a vehicle license plate recognition system, which works on both of green and white plate at the same time. In the proposed system, the image of license plate is taken from a captured vehicle image by using morphological information. In the next, each character region in the license plate image is extracted based on the vertical and horizontal projection of plate image and the relative position of individual characters. Finally, for the recognition process of extracted characters, PCA(Principal Component Analysis) and LDA(Linear Discriminant Analysis) are sequentially utilized. In the experiment, vehicle license plates of both green background and white background captured under irregular illumination conditions have been tested, and the relatively high extraction and recognition rates are observed.