• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.792-794
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• 2014

Character recognition is an image processing technique for obtaining the character information such as documents and automobile license plate and for this edge detection methods are commonly used. The previous edge detection methods are mostly applying the weighted value mask on the image and because it applies the same mask to the entire areas of the image, the processing results are somewhat insufficient. Therefore, this paper has proposed an edge detection algorithm by applying the weighted value mask considering the distribution and location of pixels to be suitable for the character recognition.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.437-440
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• 2011

본 논문은 이동식 자동영상속도측정기로 과속 단속된 영상자료 중 역광 원인으로 자동차 번호판을 인식할 수 없어 폐기되는 영상자료에 대한 번호판 인식률을 향상시키는 알고리즘을 제안하였다. 명암값 분포가 불규칙한 자동차 번호판 이미지나 영상 자체에 손상이 많은 자동차 번호판 이미지를 지역적 적응 이진화 알고리즘을 사용함으로써, 오츠 전역적 이진화 알고리즘보다 뛰어난 자동차 번호판 인식률을 얻었다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.617-620
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• 2020

최근, 국내 자동차 보유율은 매년 증가하고 있으며, 자동차 증가율에 따라 자동차로 인한 사건, 사고 발생률 또한 증가하고 있다. 국가에서도 지능형교통시스템(ITS) 중 차량 변호판을 인식하는 연구가 활발히 진행되고 있다. 차량 번호판 인식은 사건·사고 발생차량을 추적하거나 주차 무인시스템 등의 분야에 적용된다. 본 논문에서는 차량 번호판 영역을 추출하기 위한 여러 가지 방법들을 비교 분석하여 각 상황에 맞는 알고리즘을 적용하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.473-475
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• 2023

자동차 번호판 인식은 영상 내 검출한 차량의 번호판의 문자열을 인식하여 차량을 식별하고 추적하는 기술로 주변 환경에 의한 잡음, 왜곡과 차량의 움직임으로 발생한 흐림, 영상 입력 장치와의 물리적 거리 등에 강인해야 한다. 본 논문에서는 차량 움직임으로 발생한 흐림이 있는 저해상도 영상에 대한 번호판 인식 성능의 향상을 위해 디블러링 모델과 초해상화 모델을 이용한 영상 복원 방법을 제안한다. 실험을 통해 디블러링 모델과 초해상화 모델을 결합하여 흐림이 있는 저해상도 국내 번호판 영상에서의 인식 성능을 개선하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.4
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• pp.595-604
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• 2013

Currently, registered number of imported vehicles is increasing rapidly over the years. Accordingly, environment improvements of vehicle maintenance company for maintenance of luxury vehicle such as imported vehicle are continuously being made. In this paper, we propose a key frame extraction method based on HSV color model for smart vehicle management system implementation to offer for customer reliability of maintenance vehicle. After automatically recognize the license plates of the vehicle using vehicle license plate recognition system when the vehicle come in the car center, we check the repair history and request of the vehicle based on it. We implement mobile services which provide extracted key frame images to the user after extract key frames from vehicle repair video. In addition, we verify the superiority of key frame extraction method by applying a smart vehicle management system. Finally, we convert the RGB color to HSV color to improve the performance of proposed key frame extraction scheme. As a result, we confirmed that our scheme is more excellence about 30% in terms of recall than RGB color model from the performance evaluations.

• Journal of Platform Technology
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• v.11 no.3
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• pp.56-67
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• 2023

Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.

• Journal of Energy Engineering
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• v.25 no.1
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• pp.153-162
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• 2016

Experimental investigation was carried out on the CHF(Critical Heat Flux) under downward flow condition in narrow rectangular channels simulating subchannel of plate-type-fuel for JRTR(Jordan Research and Training Reactor). The experiments covers the license requirement of the research reactor. Two test sections used in this study simulate full scale subchannels for fission moly uranium target and plate-type-fuel, respectively. From the experimental results, the parameters affecting on the CHF are investigated. By using experimental data, the existing CHF prediction models were evaluated. Finally, the applicability of correlations were analysed to predict CHF in the narrow rectangular channel under the downward flow condition.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.270-274
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• 2015

We suggest that HSV Color Space may be used to detect a vehicle detecting system at nighttime. It is essential that a licence plate should be extracted when a vehicle is under surveillance. To do so, a licence plate may be enlarged to certain size after the aimed vehicle is taken picture from a distance by using Pan-Tilt-Zoom Camera. Either Mean-Shift or Optical Flow Algorithm is generally used for the purpose of a vehicle detection and trace, even though those algorithms have tendency to have difficulty in detection and trace a vehicle at night. By utilizing the fact that a headlight or taillight of a vehicle stands out when an input image is converted in to HSV Color Space, we are able to achieve improvement on those algorithms for the vehicle detection and trace. In this paper, we have shown that at night, the suggested method is efficient enough to detect a vehicle 93.9% from the front and 97.7% from the back.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.95-101
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• 2014

This paper explains effective tracking method for a vehicle cutting in a line on the road automatically. The method employs KLT based on optical flow using play-back image sequence. Main contribution of this paper is play-back image sequence that is in order image frames for rewind direction from a reference point in time. The moment when recognizing camera can read a license plate very well can usually be the reference point in time. The biggest images of object traced can usually be obtained at this moment also. When optic flow is applied, the bigger image of the object traced can be obtained, the more feature points can be obtained. More many feature points bring good result of tracking object. After the recognizing cameras read a license plate on the vehicle suspected of cut-in-line violation, and then the system extracts the play-back image sequence from the tracking cameras for watching wide range. This paper compares using play-back image sequence as normal method for tracking to using play-forward image sequence as suggested method on the results of the experiment and also shows the suggested algorithm has a good performance that can be applied to the unmanned system for watching cut-in-line violation.

• 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.