• International Journal of Contents
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• 제12권2호
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• pp.42-48
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• 2016

We present efficient algorithms for computing centroid directions for each of the three types of monotonicity in a polyhedron: strong, weak, and directional monotonicity, which can be used for optimizing directions in many 3D manufacturing processes. Strongly- and directionally-monotone directions are the poles of great circles separating a set of spherical polygons on the unit sphere, the centroids of which are shown to be obtained by applying the previous result for determining the maximum intersection of the set of their dual spherical polygons. Especially in this paper, we focus on developing an efficient method for approximating the weakly-monotone centroid, which is the pole of one of the great circles intersecting a set of spherical polygons on the unit sphere. The original problem is approximately reduced into computing the intersection of great bands for avoiding complicated computational complexity of non-convex objects on the unit sphere, which can be realized with practical linear-time operations.

• 한국지능시스템학회논문지
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• 제18권5호
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• pp.617-623
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• 2008

본 논문에서는 중심이동과 국부기저영상을 이용한 동작인식 기법을 제안하였다. 여기서 중심이동은 1차 모멘트 평형에 기반을 둔 것으로 위치나 크기 변화에 강건한 동작영상을 얻기 위함이고, 국부기저영상의 추출은 독립성분분석 기법에 기반을 둔 것으로 각 동작들마다에 포함된 통계적으로 독립인 동작특징들의 집합을 얻기 위함이다. 특히 국부기저영상을 빠르게 추출하기 위해 뉴우턴(Newton)법의 고정점 알고리즘에 기반을 둔 독립성분분석을 이용하였다. 제안된 기법을 240*215 픽셀의 160(1명*10종류*16동작)개 동물표현의 수화 동작영상을 대상으로 city-block, Euclidean, 그리고 negative angle의 척도들을 분류척도로 이용하여 실험하였다. 실험결과, 제안된 기법은 국부고유영상을 이용한 방법과 중심이동을 거치지 않는 국부기저영상을 이용하는 기법보다 각각 우수한 인식성능이 있음을 확인하였다.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2001년도 하계 학술대회 논문집(KISPS SUMMER CONFERENCE 2001
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• pp.113-116
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• 2001

The conventional K-means algorithm is widely used in vector quantizer design and clustering analysis. Recently modified K-means algorithm has been proposed where the codevector updating step is as fallows: new codevector = current codevector + scale factor (new centroid - current codevector). This algorithm uses a fixed value for the scale factor. In this paper, we propose a new algorithm for the enhancement of learning time in fuzzy c-means a1gorithm. Experimental results show that the proposed method produces codebooks about 5 to 6 times faster than the conventional K-means algorithm with almost the same Performance.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
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• pp.119-122
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• 2002

The research Interest of this paper is focused on the efficient clustering task for an arbitrary color data. In order to tackle this problem, we have tiled to model the inherent uncertainty and vagueness of color data using fuzzy color model. By laking a fuzzy approach to color modeling, we could make a soft decision for the vague regions between neighboring colors. The proposed fuzzy color model defined a three dimensional fuzzy color ball and color membership computation method with the two inter-color distance measures. With the fuzzy color model, we developed a new fuzzy clustering algorithm for an efficient partition of color data. Each fuzzy cluster set has a cluster prototype which is represented by fuzzy color centroid.

• International Journal of Aeronautical and Space Sciences
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• 제13권2호
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• pp.260-265
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• 2012

Satellite devices for fine attitude control of the Science & Technology Satellite-2 (STSAT-2). Based on the mission requirements of STSAT-2, the conventional analog-type sun sensors were found to be inadequate, motivating the development of a compact, fast and fine digital sun sensor (FDSS). The FDSS uses a CMOS image sensor and has an accuracy of less than 0.03degrees, an update rate of 5Hz and a weight of less than 800g. A pinhole-type aperture is substituted for the optical lens to minimize its weight. The target process speed is obtained by utilizing the Field Programmable Gate Array (FPGA), which acquires images from the CMOS sensor, and stores and processes the image data. The sensor accuracy is maintained by a rigorous centroid algorithm. This paper describes the FDSS designs, realizations, tests and calibration results.

• 한국항공우주학회지
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• 제35권11호
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• pp.1043-1051
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• 2007

디지털 태양센서는 CMOS 이미지 센서에 맺힌 태양광 이미지를 이용하여 태양광의 입사 각도를 계산한다. 이를 위해서는 태양광 이미지의 정확한 중심점을 찾아야하며 따라서 정밀한 중심점 추정은 디지털 태양센서 개발에서 가장 중요한 요소가 된다. 중심점을 찾기 위해서 가장 일반적으로 쓰이는 중심 알고리즘은 thresholding 방법이며 가장 단순하고 구현하기 쉽다. 또 다른 알고리즘으로는 이미지 처리를 이용하는 image filtering 방법이 있다. 하지만 이러한 방법들은 태양센서 정밀도가 이미지 센서에서 획득한 태양광 강도(intensity) 데이터의 노이즈에 영향을 많이 받으며, 특히 thresholding 방법의 경우 threshold 값에 따라 정밀도가 바뀌기 때문에 효과적인 threshold 값을 정하기 어려운 단점이 있다. 따라서 본 논문에서는 태양광 이미지의 중심점을 구하기 위해서 태양광 이미지 모델을 이용하는 template 방법을 제시하고 성능을 비교 분석하였다. 제안한 template 방법은 thereshold, image filtering 방법과 달리 비교적 높은 정밀도를 가지며, 특히 노이즈 수준에 관계없이 거의 일정한 수준의 정밀도를 가지는 장점이 있어 신뢰성이 높다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1724-1729
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• 1991

This paper gives an overview of HIGIPS design concepts and prototype HIGIPS configuration, and discusses its application to recognition of the 3-D motion of a human arm. HIGIPS which employs the combination of pipeline architecture and multiprocessor architecture, is a high-speed, high-performance and low cost N * M multimicroprocessor parallel machine, where N is the number of pipeline stages and M is the number of processors in each stage. The algorithm to recognize the motion of a human arm with a single TV camera was developed on personal computer (NEC PC9801 series). As a constraint condition, some simple ring marks are used. Each joint of the arm is attached with a ring mark to obtain its centroid position when the arm moves. These centroid positions in the three-dimensional space are linked at each of the successive pictures of the moving arm to recover its overall motion. This algorithm takes about 2 seconds to process one image frame on the general-purpose personal computer. This paper mainly discuses how to partition this algorithm and execute on HIGIPS, and shows the speed up. From this application, it is clear that HIGIPS is an efficient machine for image processing and recognizing.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1936-1939
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• 2002

Much recent attention on wireless technologies s put on topology-less wireless network, in which all nodes an be mobile and can communicate over wireless links, due to its ease of deployment, high flexibility and low expenses. One key in topology-less wireless network is mobile base stations (MBSs), which provides access points or mobile terminals (MTs) to wireless backbone network. MBSs can move to anywhere in accordance with changes in geographical distribution of MTs. They serve as dynamic odes. However, in order to utilize network resources and take full advantage of this topology-less network, MBSs must move to suitable position according to the current tate of network use. Moreover, MBSs have to consider the distance among them to avoid the crash and gap area of MBSs. Therefore, this paper proposes MBS movement algorithm by implementing push-pull method to fulfill the corporation of MBSs and considering the center of covered MTs or centroid to satisfy the MT coverage. From the simulation results, the proposed algorithm increases the performance of system when comparing with the centroid-based algoriom〔7〕, such as coverage area, MT coverage and call drops rate.

• 대한전자공학회논문지
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• 제26권11호
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• pp.1857-1866
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• 1989

In this paper, an algorithm to update a codebook using a neural network in consecutive images, is proposed. With the Kohonen's self-organizing feature map, we adopt the iterative technique to update a centroid of each cluster instead of the unsupervised learning technique. Because the performance of this neural model is comparable to that of the LBG algorithm, it is possible to update the codebooks of consecutive frames sequentially in TV and to realize the hardwadre on the real-time implementation basis.

• Journal of Astronomy and Space Sciences
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• 제22권3호
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• pp.273-282
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• 2005

주간에 활용될 수 있는 별 센서의 성능을 알아보기 위해, 주간 별 센서 관측 모델을 개발하였다. 주간 동안 별 센서가 감지하게 될 별들에 대한 중심찾기 오차는 그 모델을 사용해서 계산되었다. 별 센서가 운용되는 주간 환경의 대기 물리량을 계산하기 위해 표준 대기 모델(LOWTRAN7)이 사용되었다. 주간 별 센서 관측 모델에는 별과 태양 사이의 다양한 분리각, 중심찾기 알고리즘, 그리고 별 센서의 다양한 시스템 특성이 고려되었다. 개발된 별 센서 모델은 벡터 관측을 통한 자세결정 성능의 예측에 있어서 보다 현실적인 오차 정보를 제공하게 될 것이다.