• 대한전자공학회논문지SP
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• 제43권2호
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• pp.65-72
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• 2006

교통신호등 검출과 인식 시스템은 운전자에게 경고와 보조시스템으로 필요한 장치이다. 본 논문에서는 칼라 비젼시스템을 이용한 주행중 실시간 교통신호등의 검출과 인식법에 대해 제안하고 있다. 제안하는 방법은 크게 네 가지로 구분된다 유사색 환경에서도 신호등 빛 검출이 용이하도록 HSI 색 공간에서 채도와 밝기값의 차를 이용하여 신호등의 빛을 검출하는 신호등 검출, 신호등 외곽검출과 검출된 신호 빛을 바탕으로 교통신호등 외곽 후보영역 설정과 세 검출 결과를 토대로 교통신호등을 인식하는 부분이다. 주행중 영상을 비디오 카메라로 녹화하여 제안하는 방법에 적용하여 결과를 제시하였다. 녹화시 카메라의 줌기능을 이용하여 줌에 의한 입력 영상변화시에도 신호등을 검출 및 인식한 결과를 제시하였다.

• Journal of Biosystems Engineering
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• 제20권4호
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• pp.368-375
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• 1995

A computer vision system was built to generate images of a stationary egg. This system includes a. CCD camera, a frame grabber, and an incandescent back lighting system An image processing algorithm was developed to accurately detect surface holes and surface cracks on eggs. With 20W of incandescent back light, the detection rate was shown to be the highest. The Sobel operator was found to be the best among various enhancing filters examined. The threshold value to distinguish between the crack and the translucent spots was found to be linear with the average gray level of a whole egg image. Those values of both gray level and area were used as criteria to detect holes in egg and those values of both area and roundness were used to detect cracks in egg. For a sample of 300 eggs, this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. On the average, it took 59.5 seconds to analyze an egg image and determine whether or not it was defected.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권10호
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• pp.5095-5111
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• 2019

A multi-rotor Unmanned Aerial Vehicle (UAV) system is developed to solve the manhole cover detection problem for the infrastructure maintenance in the suburbs of big city. The visible light sensor is employed to collect the ground image data and a series of image processing and machine learning methods are used to detect the manhole cover. First, the image enhancement technique is employed to improve the imaging effect of visible light camera. An imaging environment perception method is used to increase the computation robustness: the blind Image Quality Evaluation Metrics (IQEMs) are used to percept the imaging environment and select the images which have a high imaging definition for the following computation. Because of its excellent processing effect the adaptive Multiple Scale Retinex (MSR) is used to enhance the imaging quality. Second, the Single Shot multi-box Detector (SSD) method is utilized to identify the manhole cover for its stable processing effect. Third, the spatial coordinate of manhole cover is also estimated from the ground image. The practical applications have verified the outdoor environment adaptability of proposed algorithm and the target detection correctness of proposed system. The detection accuracy can reach 99% and the positioning accuracy is about 0.7 meters.

• 한국생산제조학회지
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• 제5권2호
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• pp.57-62
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• 1996

Basically, the idea underlying most edge-detection technique is the computation of a local derivative operator used for edge detection in gray level image. This concept can be easily illustrated with the aid of object which shows an image of a simple lilght on a dark background, Using the gray level profile along a horizontal scan line of the image. the first and second derivatives of it were acquired. This study is to develop an automatic measuring system based on the digital image processing which can be applied to the real time measurement of the characteristics of the ultra-thin thickness. The experimental results indicate that the developed automatic inspection can be applied in real situation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅲ
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• pp.1545-1548
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• 2003

This paper presents a method for detecting skin tumors on chicken carcasses using hyperspectral images. It utilizes both fluorescence and reflectance image information in hyperspectral images. A detection system that is built on this concept can increase detection rate and reduce processing time. Chicken carcasses are examined first using band ratio FCM information of fluorescence image and it results in candidate regions for skin tumor. Next classifier selects the real tumor spots using PCA components information of reflectance image from the candidate regions.

• 반도체디스플레이기술학회지
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• 제15권3호
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• pp.51-56
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• 2016

This paper proposes a new image enhancement method for an infrared thermal image. The proposed method uses both Laplacian and Prewitt edge detectors. Without a visible light, it uses an infrared image for the edge detection. The method subtracts contour images from the infrared thermal image. It results black contours of objects in the infrared thermal image. That makes the objects in the infrared thermal image distinguished clearly. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using various infrared thermal images. The results show that the proposed method is successful for image enhancement of an infrared thermal image.

• 한국컴퓨터산업학회논문지
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• 제9권3호
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• pp.129-136
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• 2008

본 논문은 NTSC 카메라로 부터 획득한 컬러 이미지를 흑백 이미지로 변환하여 영상 경계선 검출 후 Hough 변환을 통하여 영상 기울기를 검출하는 시스템을 고성능 DSP를 이용하여 구현하였다. 검출된 영상 기울기는 서보모터를 제어하여 카메라 지지대를 기울여도 카메라를 반대로 기울여 항상 기울어지지 않는 영상이 얻어지는 시스템을 구현 하였다.

• Journal of information and communication convergence engineering
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• 제18권4호
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• pp.267-277
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• 2020

It is important to understand the exact habitat distribution of endangered species because of their decreasing numbers. In this study, we build a system with a deep learning module that collects the image data of endangered animals, processes the data, and saves the data automatically. The system provides a more efficient way than human effort for classifying images and addresses two problems faced in previous studies. First, specious answers were suggested in those studies because the probability distributions of answer candidates were calculated even if the actual answer did not exist within the group. Second, when there were more than two entities in an image, only a single entity was focused on. We applied an object detection algorithm (YOLO) to resolve these problems. Our system has an average precision of 86.79%, a mean recall rate of 93.23%, and a processing speed of 13 frames per second.

• 한국항공우주학회지
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• 제46권5호
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• pp.427-435
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• 2018

국토 방위를 위해 국가들은 자국 상공을 지나가는 위성 감시 시스템을 구축하고 있으며 이 시스템들 중 하나는 광학계를 이용한 위성 감시 시스템이다. 광학계를 이용할 경우, 획득한 영상 내에 존재하는 위성 광원을 제한된 시간 내에 검출하여 그 위치를 추적 시스템에 전달하여야 한다. 제안하는 방법은 광학계를 이용한 위성 감시 시스템을 이용해 획득한 고해상도 상공 촬영 영상을 고속으로 영상 처리하여 위성 광원을 검출한다. 이를 위해 고해상도 영상 처리에 앞서 영상을 축소하여 저해상도 영상을 생성하여 위성의 궤적을 추정하고 고해상도 원본 영상에서는 궤적 근방 영역에서만 영상 처리 방법들이 적용되도록 하였다. 제안하는 방법은 기존에 위성 검출을 위해 사용되는 방법과 유사한 위성 검출 정확도를 보이면서 검출을 더 빠르게 수행하였다.

• 전기학회논문지
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• 제65권4호
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• pp.704-710
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• 2016

In this paper, we proposed pole position detection system for providing exact location information to users. The proposed system consists of pole recognition part and pole number recognition part. Above all, exact pole recognition is carried out by PDD(Pole Detection Device). And recognition of pole number is performed by PID(Pole Inspection Device). Acquired image by using line scan camera is judged whether it is free bracket or not through image processing. When it is judged as free bracket, pole number image is acquired by OCR camera and recognized by OCR. By recognizing pole number, exact location information is provided to user.