• 한국컴퓨터정보학회논문지
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• 제14권12호
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• pp.201-208
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• 2009

최근의 항만은 유비쿼터스 환경 구축에 따른 일반적인 항만 관리에 있어 U-Port 서비스를 도입하여 컨테이너 위치 추적 시스템, 항만 터미널 관리 시스템, 선진정보교환시스템 등을 구현하고 있다. 특히, 화물 차량과 컨테이너의 위치 추적 서비스는 실시간으로 화물차량과 컨테이너의 위치와 상태 정보를 제공하여 효율적인 차량 운행 관리와 문제 발생시 즉각적인 대처가 가능하게 한다. 하지만 대규모 항만 내에서 화물 차량의 무질서한 운행이나 주 정차, 도난 파손 사고 출입 관제 등의 문제를 효율적으로 관리하기에는 미흡하다. 본 논문에서는 항만 내에서의 이러한 문제점을 해결하기 위하여 자동 게이트 통관 시점부터 항만 내에 화물 차량이 체재하는 동안 차량 또는 출입자의 위치를 전자 지도상에 표시하고, 확인이 필요하거나 사고 발생 지역을 원격에서 영상으로 확인할 수 있는 항만내 차량 또는 출입자의 위치 인식 및 고해상도 영상 압축, AVE/H.264 저장 및 영상 전송을 통한 영상 확인 시스템을 구현하였다.

• Korean Journal of Mathematics
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• 제14권1호
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• pp.47-55
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• 2006

This paper presents an image analysis technique using connected components by applying SPA (shortest path algorithm) from graph theory. Software implementation of Floyd-Warshall transitive matrix labelling method is discussed. Results are also presented.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권7호
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• pp.313-318
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• 2006

An automatic sample centering system is underway at the protein crystallography beam line of the Pohang Light Source to improve the efficiency of the crystal screening process. A sample pin which contains a protein crystal is mounted on a goniometer head. Then the crystal should be moved to the center of X-ray beam by controlling the motorized goniometer to obtain diffraction data. Since the X-ray beam is located at the center of the image obtained from the CCD camera when the image of the sample pin is in focus, an auto-focusing algorithm is a very important part in the auto-sample-centering system. However the results of applying several well-known auto focusing algorithms directly to the images are not satisfactory owing to the following factors: misalignment of CCD camera, non-uniform cryo-stream in the background of the image and the supporter of the loop. The performance of an auto-focusing algorithm can be increased if the algorithm is applied to only the loop region identified. Non-uniform cryo-stream and a various illumination condition and a stain, which is shown in the image, are main obstacles to loop region identification. In this paper, a simple loop region identification algorithm, which can solve these problems, is proposed and the effective ness of the proposed scheme is shown by applying the auto-focusing algorithm to the loop region identified.

• 반도체디스플레이기술학회지
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• 제11권4호
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• pp.49-55
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• 2012

This paper proposes an efficient method of object identification and localization for image recognition. The new proposed algorithm utilizes correlogram back-projection in the YCbCr chromaticity components to handle the problem of sub-region querying. Utilizing similar spatial color information enables users to detect and locate primary location and candidate regions accurately, without the need for additional information about the number of objects. Comparing this proposed algorithm to existing methods, experimental results show that improvement of 21% was observed. These results reveal that color correlogram is markedly more effective than color histogram for this task. Main contribution of this paper is that a different way of treating color spaces and a histogram measure, which involves information on spatial color, are applied in object localization. This approach opens up new opportunities for object detection for the use in the area of interactive image and 2-D based augmented reality.

• International Journal of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.58-63
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• 2022

Recently, the improvement of computational processing ability due to the rapid development of computing technology has greatly advanced the field of artificial intelligence, and research to apply it in various domains is active. In particular, in the national defense field, attention is paid to intelligent recognition among machine learning techniques, and efforts are being made to develop object identification and monitoring systems using artificial intelligence. To this end, various image processing technologies and object identification algorithms are applied to create a model that can identify friendly and enemy weapon systems and personnel in real-time. In this paper, we conducted image processing and object identification focused on tanks among various weapon systems. We initially conducted processing the tanks' image using a convolutional neural network, a deep learning technique. The feature map was examined and the important characteristics of the tanks crucial for learning were derived. Then, using YOLOv5 Network, a CNN-based object detection network, a model trained by labeling the entire tank and a model trained by labeling only the turret of the tank were created and the results were compared. The model and labeling technique we proposed in this paper can more accurately identify the type of tank and contribute to the intelligent recognition system to be developed in the future.

• 반도체디스플레이기술학회지
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• 제10권3호
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• pp.89-94
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• 2011

The image identification methodology associates an image with a unique identifiable representation. Whenever the methodology regenerates an identifier for the same image, moreover, the newly created identifier needs to be consistent in terms of representation value. In this paper, we discuss a methodology for image identifier generation utilizing luminance correlation. We furthermore propose a method for performance enhancement of the image identifier generation. We also demonstrate the experimental evaluations for uniqueness and similarity analysis and performance improvement that have shown favorable results.

• 한국멀티미디어학회논문지
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• 제17권3호
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• pp.277-286
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• 2014

본 논문에서는 Gabor 특징과 MDLC 특징, 그리고 co-occurrence 특징의 융합에 의한 질감 특징 기반언어 인식 방법을 제안한다. 제안된 방법에서는 먼저 시험 영상에 Gabor 변환에 이은 크기 연산자를 적용하여 Gabor 크기 영상을 얻고 그 통계치를 계산하여 결과를 벡터화한다. 이어서 MDLC 연산자를 이용하여 MDLC 영상을 얻고 역시 그 통계치를 계산하여 벡터화한다. 다음으로 시험 영상으로부터 GLCM을 계산하고 이를 이용하여 co-occurrence 특징을 계산한 다음 벡터화한다. 이들 Gabor, MDLC, co-occurrence 특징에 의한 벡터들은 벡터 융합에 의하여 특징 벡터로 사용된다. 분류 단계에서는 얼굴 인식에 주로 사용되는 WPCA를 분류기로 하여 시험 특징 벡터와 가장 유사한 학습 특징 벡터를 찾는다. 제안된 방법의 성능은 15개국 언어의 문서를 스캔하여 얻은 시험 문서 영상 DB에 대한 평균 인식률을 조사하여 알아본다. 실험 결과 제안된 방법은 시험 DB에 대하여 비교적 낮은 특징 벡터 차원으로 매우 우수한 언어 인식 성능을 보여준다.

• 한국멀티미디어학회논문지
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• 제13권2호
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• pp.171-178
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• 2010

무인감시시스템은 무선 칩 같은 기초적인 센서를 이용하는 분야는 많이 연구 되어 왔으며. 카메라를 주요 센서로 하는 영상감시체계 연구 분야가 활성화 되고 있다. 본 논문에서는 다양한 영상검지기법을 조사 분석한 결과를 토대로 영상 객체 인식 기법을 적용한 지능형 영상검지 시스템을 제안하였다. 이 지능형 영상검지 시스템은 사건 전후의 상황을 쉽게 추적 판단 할 수 있으며, 확실한 증거와 다양한 정보를 확보 할 수 있다. 따라서 본 논문에서 제안하는 지능형 영상 검지 시스템은 교통상황 관리, 재난 경보 등 다양한 무인감시시스템에 활용 될 것이다.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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• pp.300-306
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• 2000

This paper introduces a new concept of automation for bio-production with tele-operative system. The proposed system showed practical and feasible way of automation for the volatile bio-production process. Based on the proposition, recognition of the job environment with object identification was performed using computer vision system. A man-machine interactive hybrid decision-making, which utilized a concept of tele-operation was proposed to overcome limitations of the capability of computer in image processing and feature extraction from the complex environment image. Identifying watermelons from the outdoor scene of the cultivation field was selected to realize the proposed concept. Identifying watermelon from the camera image of the outdoor cultivation field is very difficult because of the ambiguity among stems, leaves, shades, and especially fruits covered partly by leaves or stems. The analog signal of the outdoor image was captured and transmitted wireless to the host computer by R.F module. The localized window was formed from the outdoor image by pointing to the touch screen. And then a sequence of algorithms to identify the location and size of the watermelon was performed with the local window image. The effect of the light reflectance of fruits, stems, ground, and leaves were also investigated.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(4)
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• pp.251-254
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• 2000

This paper proposes an enhanced algorithm for person identification system utilizing hand vein pattern. The conventional algorithm does not cope with distortion caused by image rotation caused by misplaced hands on the imaging device. A straightforward approach to consider the rotaional compensation required too much computational load, thus, we devised an approach to expect the rotation direction along with image translation, reducing the compuational requirement dramatically In this paper, we present the details of the algorithm with experimental results with the new algorithm.