• IE interfaces
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• v.14 no.3
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• pp.296-301
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• 2001

The focus of this study is to redesign the Korean license plate by comparing the USA's plate with European plate formed by 1-line system in order to increase a read rate of Korea license plate. And we have compared the read rate of the new design license plate with that of the present license plate and that of the license plate studied so far. As an experimental method (used in a precedent research), we use three kinds of methods that are the measurement of the read-distance, the measurement reading-rate under the short-term exposure and the measurement of the reading-rate when driving. First, three kinds of measurements for plates of five nations are performed. Then we redesign the new Korean license plate under the base of read rates obtained by five nation's plate. As alternatives, we choose five license plates. Those alternatives are the redesigned license plate, the present license plate, the license plate studied so far, and two types of eternity license plates made by the Korea Transport Institute. When we compare results of the read-distance, there is no significant in term of different the read-distance between the alternatives. But there is a significant difference in term of the misreading-rate and the read-rate when diving. Therefore, it is necessary to redesign the present license plates because of a high misreading-rate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.142-149
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• 2016

This paper proposes a method to detect LP(License Plate) of vehicles in indoor and outdoor parking lots. In restricted environment, there are many conventional methods for detecting LP. But, it is difficult to detect LP in natural and complex scenes with background clutters because several patterns similar with text or LP always exist in complicated backgrounds. To verify the performance of LP text detection in natural images, we apply MB-LGP feature by combining with ensemble machine learning algorithm in purpose of selecting optimal features of small number in huge pool. The feature selection is performed by adaptive boosting algorithm that shows great performance in minimum false positive detection ratio and in computing time when combined with cascade approach. MSER is used to provide initial text regions of vehicle LP. Throughout the experiment using real images, the proposed method functions robustly extracting LP in natural scene as well as the controlled environment.

• Proceedings of KOSOMES biannual meeting
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• 2007.11a
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• pp.87-89
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• 2007

선행 연구개발한 집단감시 디지털 시스템(Group Digital Surveillance System for Fishery Safety and Security, GDSS- F2S)은 대단위 양식장에 침입하는 도적을 방어하기 위하여 레이더 추적정보와 적아식별 정보를 제공하는 시스템이다. 그러나 GDSS-F2S에서 제공하는 두 가지 정보만으로는 도적행위를 입증할 수 있는 법적 증거자료로 미흡하다. 본 논문에서는 이러한 문제점 해결방안의 하나로 CCD 카메라를 이용한 영상획득 장치를 개발하여 GDSS-F2S에 부가한 연구내용을 기술한다. 영상획득 장치 개발에 앞서, 실험지역의 지리적인 특성을 고려한 도적침입 예상경로 분석과 도적행위 시나리오를 기반으로 유효한 대응수단을 검토한 결과, 영상획득 장치가 유효한 대응수단임을 확인하였다. 영상획득 장치는 저가이변서 성능이 우수한 0.0001 룩스의 초저조도 CCD 카메라와 부가장치를 이용하여 개발하였다. 6개월 이상의 장기 현장실험을 통하여 본 연구에서 개발한 시스템을 평가한 결과, 주간은 물론 1 미터 앞도 식별할 수 없는 야간에도 차량의 행동과 번호판 및 사람의 행동과 인상착의 등의 영상정보를 확보할 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.877-889
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• 2006

This paper introduces a simple but effective method for recognizing vehicle models corresponding to each maker by information and images for moving vehicles. The proposed approach is implemented by combination of the breadth detection mechanism using the vehicle's pressure, exact height detection by a laser scanning, and license plate recognition for classifying specific vehicles. The implemented system is therefore capable of robust classification with real-time vehicle's moving images and established sensors. Simulation results using the proposed method on synthetic data as well as real world images demonstrate that proposed method can maintain an excellent recognition rate for moving vehicle models because of image acquisition by 2-D CCD and various image processing algorithms.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.1-7
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• 2003

This study is a research on character recognition based on image processing, using only color tape to mark guidelines instead of magnetic tape or electric wire used by existing AGV. AGV must follow given courses, and stop recognizing signs such as marks and numbers that indicate destinations. In this study. marks to stop AGV employed blue characters of the same font and size as those of number plates. Yellow driving lines and blue numeric characters were marked in corridors. AGV ran ing the characteristics of colors and detecting lines, and temporarily stopped recognizing numbers of 100％ through DP pattern matching. This study presented the image processing technique and the result of operating AGV.

• Journal of Korean Port Research
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• v.13 no.2
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• pp.303-312
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• 1999

The automated gate operating system is developed in this paper that controls the information of container at gate in the ACT. This system can be divided into three parts and consists of container identifier recognition car plate recognition container deformation perception. We linked each system and organized efficient gate operating system. To recognize container identifier the preprocess using LSPRD(Line Scan Proper Region Detection)is performed and the identifier is recognized by using neural network MBP When car plate is recognized only car image is extracted by using color information of car and hough transform. In the port of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container deformation perception firstly background is removed by using moving window. Secondly edge is detected from the image removed characters on the surface of container. Thirdly edge is fitted into line segment so that container deformation is perceived. As a results of the experiment with this algorithm superior rate of identifier recognition is shown and the car plate recognition system and container deformation perception that are applied in real-time are developed.

• Journal of Convergence Society for SMB
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• v.6 no.3
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• pp.85-91
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• 2016

It was difficult to verify the car number or face of inspector in the closed circuit television because of low CCD pixels and low brightness of lens. So CCTV lens should have higher pixels and brightness. In this paper, the design of zoom lens for mega pixel Closed-Circuit Television (CCTV) was introduced. We applied aspheric lens in order to reduce the spherical aberration and distortional aberration. And we applied focal length of 6-60mm, F number of 1.2, 3 million pixel resolution and magnifying power of 10 times. Also we applied infrared correction in order to use the CCTV camera in day and night effectively. These norms are the most powerful in CCTV zoom lens of focal length of 6-60mm. And if we apply this lens to the box style CCTV camera, we can verify the car number or face within 50m. Auto controlling system will be continued.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1167-1174
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• 2006

Text region detection from a natural scene is useful in many applications such as vehicle license plate recognition. Therefore, in this paper, we propose a text region extraction method using pattern histogram of character-edge maps. We create 16 kinds of edge maps from the extracted edges and then, we create the 8 kinds of edge maps which compound 16 kinds of edge maps, and have a character feature. We extract a candidate of text regions using the 8 kinds of character-edge maps. The verification about candidate of text region used pattern histogram of character-edge maps and structural features of text region. Experimental results show that the proposed method extracts a text regions composed of complex background, various font sizes and font colors effectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.203-207
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• 2006

Nowadays, Cars are continuing to grow at an alarming rate but they also cause many problems such as traffic accident, pollutions and so on. One of the most effective methods that prevent traffic accidents is the use of traffic monitoring systems, which are already widely used in many countries. The monitoring system is beginning to be used in domestic recently. An intelligent monitoring system generates photo images of cars as well as identifies cars by recognizing their plates. That is, the system automatically recognizes characters of vehicle plates. An automatic vehicle plate recognition consists of two main module: a vehicle plate locating module and a vehicle plate number identification module. We study for a vehicle plate number identification module in this paper. We use image preprocessing, feature extraction, multi-layer neural networks for recognizing characters of vehicle plates and we present a feature-comparison method for improving the performance of vehicle plate number identification module. In the experiment on identifying vehicle plate number, 300 images taken from various scenes were used. Of which, 8 images have been failed to identify vehicle plate number and the overall rate of success for our vehicle plate recognition algorithm is 98%.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.555-562
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• 2021

In this paper, we propose a sorting method for extracting accurate license plate information, which is currently used in Korea, after detecting objects using YOLO. We propose sorting methods for the five types of vehicle license plates managed by the Ministry of Land, Infrastructure and Transport by classifying the plates with the number of lines, Korean characters, and numbers. The results of experiments with 5 license plates show that the proposed algorithm identifies all license plate types and information by focusing on the object with high reliability score in the result label file presented by YOLO and deleting unnecessary object information. The proposed method will be applicable to all systems that recognize license plates.