• 전기학회논문지
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• 제57권11호
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• pp.2086-2094
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• 2008

Finding a planar surface on 3D space is very important for efficient and safe operation of a mobile robot. In this paper, we propose a method using a plane detection cell (PDC) and iterative randomized Hough transform (IRHT) for finding the planar region from a 3D range image. First, the local planar region is detected by a PDC from the target area of the range image. Each plane is then segmented by analyzing the accumulated peaks from voting the local direction and position information of the local PDC in Hough space to reduce effect of noises and outliers and improve the efficiency of the HT. When segmenting each plane region, the IRHT repeatedly decreases the size of the planar region used for voting in the Hough parameter space in order to reduce the effect of noise and solve the local maxima problem in the parameter space. In general, range images have many planes of different normal directions. Hence, we first detected the largest plane region and then the remained region is again processed. Through this procedure, we can segment all planar regions of interest in the range image.

• 한국멀티미디어학회논문지
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• 제19권6호
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• pp.1003-1013
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• 2016

This paper proposes a framework of superpixel-based vehicle detection method using plane normal vector in disparity space. We utilize two common factors for detecting vehicles: Hypothesis Generation (HG) and Hypothesis Verification (HV). At the stage of HG, we set the regions of interest (ROI) by estimating the lane, and track them to reduce computational cost of the overall processes. The image is then divided into compact superpixels, each of which is viewed as a plane composed of the normal vector in disparity space. After that, the representative normal vector is computed at a superpixel-level, which alleviates the well-known problems of conventional color-based and depth-based approaches. Based on the assumption that the central-bottom of the input image is always on the navigable region, the road and obstacle candidates are simultaneously extracted by the plane normal vectors obtained from K-means algorithm. At the stage of HV, the separated obstacle candidates are verified by employing HOG and SVM as for a feature and classifying function, respectively. To achieve this, we trained SVM classifier by HOG features of KITTI training dataset. The experimental results demonstrate that the proposed vehicle detection system outperforms the conventional HOG-based methods qualitatively and quantitatively.

• 천문학회보
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• 제25권1호
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• pp.53-53
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• 2000

• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2008년도 공동추계학술대회
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• pp.297-302
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• 2008

The positioning technology for a moving object is an important and essential component of ubiquitous computing environment and applications, for which Radio Frequency Identification(RFID) has been considered as a core technology. RFID-based positioning system calculates the position of moving object based on k-nearest neighbor(k-nn) algorithm using detected k-tags which have known coordinates and kcan be determined according to the detection range of RFID system. In this paper, RFID-based positioning system determines the position of moving object not using weight factor which depends on received signal strength but assuming that tags within the detection range always operate and have same weight value. Because the latter system is much more economical than the former one. The geometries of tags were determined with considerations in huge buildings like office buildings, shopping malls and warehouses, so they were determined as the line in I-Dimensional space, the square in 2-Dimensional space. In 1-Dimensional space, the optimal detection range is determined as 125% of the tag spacing distance through the analytical and numerical approach. Here, the analytical approach means a mathematical proof and the numerical approach means a simulation using matlab. But the analytical approach is very difficult in 2-Dimensional space, so through the numerical approach, the optimal detection range is determined as 134% of the tag spacing distance in 2-Dimensional space. This result can be used as a fundamental study for designing RFID-based positioning system.

• 한국멀티미디어학회논문지
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• 제17권1호
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• pp.8-14
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• 2014

본 논문에서는 비디오 영상에서 화염의 칼라와 움직임 특징을 이용한 새로운 화재 감지 방법을 제안한다. 색차로부터 휘도를 효율적으로 분리하기 위하여 RGB 칼라를 YCbCr 성분으로 변환한다. 제안한 방법은 인접 영상들 간의 휘도의 차를 누적하여 화염의 움직임 영역을 검출하고, 화염의 색을 이용하여 화염 후보 영역을 생성한다. 최종적으로, 화염 후보 영역의 면적에 대한 시간적 변화를 이용하여 화염 영역을 결정한다. 실험 결과를 통하여 제안한 방법이 기존의 비디오 영상에서의 화재 감지 방법보다 화재 영역의 분류에 우수한 성능을 나타내는 것을 확인하였다.

• Journal of Information Technology Applications and Management
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• 제12권1호
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• pp.231-239
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• 2005

This paper describes a new algorithm for pixel-based skin color detection to differentiate human form in color images by the ratio of R to H. In order to detect skin color efficiently, we examine the distribution of the R, G and B color elements combining to constitute the skin color in various color images. It shows that R is located in a narrower area than G and B on the RGB color space. And skin color is more related to R than G and B. Meanwhile, when the color image is transformed to the HSI color space, the S is variously changed in accordance with skin colors. The I is changed in accordance with the quantity and angle of light. But the H is less influenced by other conditions except for color. On the basis of the aforementioned study, we propose that the threshold for skin color detection is decided by the ratio of R to H. The proposed method narrows down the range of threshold, detects more skin color and reduces mis-detection of skin color in comparison to detection by R or H. In experimentation. it shows that the proposed algorithm overcomes changes of brightness and color to detect skin color in color images.

• 한국콘텐츠학회논문지
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• 제7권12호
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• pp.311-321
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• 2007

본 논문은 영상에 포함된 얼굴을 보다 빠르고 강건하게 검출하기 위해서 이질적 템플릿 매칭의 결과들을 융합하여 얼굴을 검출하는 방법을 제안한다. 먼저 광범위한 조명 환경과 인종을 포괄하는 피부색 모델을 이용해 피부 영역을 검출한다. 그리고 영역 라벨링과 필터링으로 매칭에 필요한 검색 범위를 줄인 후, 피부색과 에지를 이용한 템플릿 매칭을 검출된 영역에 적용한다. 이들 매칭 결과가 융합되어 두 매칭 결과를 동시에 최적으로 만족하는 얼굴이 검출된다. 실험 결과는 제안된 방법이 단일 템플릿을 적용할 때보다 얼굴색과 유사한 배경에서 얼굴을 강건하게 검출하며, 얼굴 후보 영역으로 검색 범위를 줄여 검출 시간을 줄였음을 보여준다. 또한 전역 누산기를 사용하여 템플릿 매칭의 과도한 공간 요구의 문제점을 해결할 수 있었다.

• 한국항해항만학회지
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• 제30권2호
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• pp.167-172
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• 2006

In this paper, the issue of blind detection of Alamouti-type differential space-time (ST) ${\pi}/2$-shifted BPSK modulation in static Rayleigh fading channels is considered. We introduce a novel transformation to the received signal from each receiver antenna such that this binary ST modulation, which has a second-order transmit-diversity, is equivalent to QPSK modulation with second-order receive-diversity. The pre-detection combining of the result of transformation allows us to apply a low complexity detection technique specifically designed for receive-diversity, namely, scalar multiple-symbol differential detection (MSDD). With receiver complexity proportional to the observation window length, our receiver can achieve the performance 1.5dB better than that of conventional differential detection ST and 0.5dB worse than that qf a coherent maximum ratio combining receiver (with differential decoding) approximately.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 추계종합학술대회
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• pp.83-86
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• 2007

In the blind Maximum-likelihood (ML) detection for Orthogonal Space-Time Block Codes (OSTBC), the problem of ambiguity in determining the symbols has been a great concern. A solution to this problem is to apply semi-blind ML detection, i.e., the blind ML decoding with pilot symbols or training sequence. In order to increase the performance, the number of pilot symbols or length of training sequence should be increased. Unfortunately, this leads to a significant decrease in system spectral efficiency. This work presents an approach to resolve the aforementioned issue by introducing a new method for constructing transmitted information symbol. Thus, by transmitting information symbols drawn from different modulation constellation, the ambiguity can be easily eliminated in blind detection. Also, computer simulations are implemented to verify the performance of the proposed approach.

• Journal of Astronomy and Space Sciences
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• 제27권3호
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• pp.245-252
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• 2010

Korea Astronomy and Space Science Institute (KASI) has developed a mobile satellite laser ranging (SLR) system called ARGO-M since 2008 for space geodesy research and precise orbit determination technologies using SLR with mm level accuracy. ARGO-M is capable of night tracking and daylight tracking for which requires spatial, spectral and time filters due to high background noises. In this study, characteristics and specifications of ARGO-M are discussed and its tracking capabilities of night and daylight tracking are analyzed for STSAT-2B and KOMPSAT-5 through link budget. Additionally false alarm and signal detection probabilities are also analyzed depending on spectral and time filters for daylight tracking for these satellites.