• Title/Summary/Keyword: Object Boundary Point

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Incremental Circle Transform Theory and Its Application for Orientation Detection of Two-Dimensional Objects (증분원변환 이론 및 이차원 물체의 자세인식에의 응용)

  • ;;Zeung Nam Bien
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.28B no.7
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    • pp.578-589
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    • 1991
  • In this paper, there is proposed a novel concept of Incremintal Circle Transform which can describe the boundary contour of a two-dimensional object without object without occlusions. And a pattern recognition algorithm to determine the posture of an object is developed with the aid of line integral and similarity transform. Also, It is confirmed via experiments that the algorithm can find the posture of an object in a very fast manner independent of the starting point for boundary coding and the position of the object.

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A Study on Motion Detection of Object Using Active Block Matching Algorithm (능동적 블록정합기법을 이용한 객체의 움직임 검출에 관한 연구)

  • Lee Chang-Soo;Park Mi-Og;Lee Kyung-Seok
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.4C
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    • pp.407-416
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    • 2006
  • It is difficult for the movement detection of an object through a camera to detect exact movement because of unnecessary noises and changes of the light. It can be recognized as a background, when there is no movement after the inflow of an object. Therefore, It is necessary to fast search algorithm for tracking and extract of object that is realtime image. In this thesis, we evaluate the difference of the input vision based on initial image and replace some pixels in process of time. When there is a big difference between background image and input image, we decide it is the point of the time of the object input and then extract boundary point of it. The extracted boundary point detects precise movement of the object by creating minimum block of it and searching block that maintaining distance. The designed and embodied system shows more than 95% accuracy in the performance test.

A new pattern classification algorithm for two-dimensional objects

  • You, Bum-Jae;Bien, Zeungnam
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.917-922
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    • 1990
  • Pattern classification is an essential step in automatic robotic assembly which joins together finite number of seperated industrial parts. In this paper, a fast and systematic algorithm for classifying occlusion-free objects is proposed, using the notion of incremental circle transform which describes the boundary contour of an object as a parametric vector function of incremental elements. With similarity transform and line integral, normalized determinant curve of an object classifies each object, independent of position, orientation, scaling of an object and cyclic shift of the stating point for the boundary description.

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Extraction of Simplified Boundary In Binary Image (이진 영상에서의 단순화된 윤곽선 추출 방법)

  • 김성영
    • Journal of the Korea Society of Computer and Information
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    • v.4 no.4
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    • pp.34-39
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    • 1999
  • In this paper, boundary extraction algorithm is suggested by removing boundary noises efficiently and simplifying object shape in binary image. To remove boundary noises, $2{times}2$ mask boundary extraction algorithm is modified . Proposed method is designed to generate a symmetric path for the parasitic branch noise and to analysis traced features on end point of noise. It can extract more simplified object boundary but preserve original object shape by combining white background color extraction result with foreground extraction result. The usefulness of the proposed method was proved through experiments with various binary images.

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Enhanced Boundary Partition Color Descriptor for Deformable Object Retrieval (비정형객체 검색을 위한 향상된 분할영역 색 기술자)

  • Jung, Hyun-il;Kim, Hae-kwang
    • Journal of Broadcast Engineering
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    • v.20 no.5
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    • pp.778-781
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    • 2015
  • The paper presents a new way of visual descriptor for deformable object retrieval on the basis of partition based description. The proposed descriptor technology partitions a given object into boundary area and interior area and extracts a descriptor from each area. The final descriptor combines these descriptors. From a given image, deformable object is segmented. The center position of the deformable object is calculated. The object is partitioned into N × N blocks on the basis of the given center position. Blocks are classified as boundary area and interior area depending on the pixels in the block. The proposed descriptor consists of extracted MPEG-7 dominant descriptors from both the boundary and interior area. The performance of proposed method is tested on a database of 1,973 handbag images constructed with view point changes. ARR (Average Retrieval Rate) is used for the retrieval accuracy of the proposed algorithm, compared with MPEG-7 dominant color descriptor.

The Image Segmentation Method using Adaptive Watershed Algorithm for Region Boundary Preservation

  • Kwon, Dong-Jin
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.1
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    • pp.39-46
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    • 2019
  • This paper proposes an adaptive threshold watershed algorithm, which is the method used for image segmentation and boundary detection, which extends the region on the basis of regional minimum point. First, apply adaptive thresholds to determine regional minimum points. Second, it extends the region by applying adaptive thresholds based on determined regional minimum points. Traditional watershed algorithms create over-segmentation, resulting in the disadvantages of breaking boundaries between regions. These segmentation results mainly from the boundary of the object, creating an inaccurate region. To solve these problems, this paper applies an improved watershed algorithm applied with adaptive threshold in regional minimum point search and region expansion in order to reduce over-segmentation and breaking the boundary of region. This resulted in over-segmentation suppression and the result of having the boundary of precisely divided regions. The experimental results show that the proposed algorithm can apply adaptive thresholds to reduce the number of segmented regions and see that the segmented boundary parts are correct.

Problematized obesity and standardization of treatment: Multiple translation in lapband surgery network (문제화된 비만과 치료의 표준화 과정: 랩밴드 수술 연결망에서의 다중번역)

  • Han, Gwang Hee;Kim, Byoung Soo
    • Journal of Science and Technology Studies
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    • v.13 no.2
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    • pp.137-172
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    • 2013
  • Globally, awareness about obesity is increasing rapidly. In Korea, obesity is recognized as a disease and steps are being taken to treat it. From the health governance point of view, such standardized measures amplify the risk of obesity and thus play an important part in the prevention of the disease. In this context, various obesity treatments act as a medium for the problem-solving process. In recent years, obesity surgery has been viewed as a rational solution to the problem of obesity. In the context of standardization of treatment, Callon's "Process of Translation" in STS theories highlights the importance of the central actor (Obligatory Passage Point; OPP). However, in the case of obesity, it is difficult to identify a single OPP to project different perspectives of an actor's needs. "Lapband surgery" often acts as a "boundary object" in this context. This article assesses this absence of central actors in the process of problem solving through a case study of adoption of Lapband surgery in Korea. Further, we attempt to suggest an analytical framework with a boundary object and multiple translation concepts to aid solving the problem of obesity.

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A Comparison of the Algorithm between Korea and Japan in Maritime Boundary Delimitation (해양경계획선 알고리즘에 관한 연구)

  • Kim Byung-Guk;Jin Hai-Ming;Kim Hyung-Su
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.23 no.2
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    • pp.211-217
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    • 2005
  • The general rule of boundary delimitation is the principle of equidistance. The principle of equidistance is a method that determine boundary delimitation from the fixed distant of baseline or basepoint. But there is no artificial and natural object in the sea to determine boundary. And the principle of equidistant can't be applied in every cases, because of the local characteristic of ground. In this paper, we suggest Three-Point Algorithm which is effective algorithm for maritime boundary delimitation. And the main objective of this study is to get capability of maritime boundary delimitation technique.

Accuracy of Mid Point Computation for Boundary Delimitation on Ellipsoid (타원체상에서 경계획선을 위한 중간점계산의 정확도)

  • 김병국;이종기;김정기
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.19 no.4
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    • pp.365-372
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    • 2001
  • The general rule of boundary delimitation is a the principle of equidistant. The principle of equidistant is a method that determine boundary delimitation from fixed distant of baseline or basepoint. In this paper, study Two-Point Algorithm and Three-Point Algorithm that are widely used. and developed the Boundary Delimitation Program to verify the result and error. This program is specially useful for maritime boundary delimitation problem because there is no artificial and natural object in sea to determine boundary. As a result The mid-points computed on Ellipsoid have small error rather than mid-points on plane or sphere without any distortion by map projection. Through developing boundary delimitation program, can eliminate the various manipulation error using paper map, and quickly cope with maritime boundary delimitation negotiation. Also, verify that the error of basepoint in baseline is propagate the mid-point in mid-line, and determine suitable reference plane.

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An Automatic Extraction Algorithm of Structure Boundary from Terrestrial LIDAR Data (지상라이다 데이터를 이용한 구조물 윤곽선 자동 추출 알고리즘 연구)

  • Roh, Yi-Ju;Kim, Nam-Woon;Yun, Kee-Bang;Jung, Kyeong-Hoon;Kang, Dong-Wook;Kim, Ki-Doo
    • 전자공학회논문지 IE
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    • v.46 no.1
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    • pp.7-15
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    • 2009
  • In this paper, automatic structure boundary extraction is proposed using terrestrial LIDAR (Light Detection And Ranging) in 3-dimensional data. This paper describes an algorithm which does not use pictures and pre-processing. In this algorithm, an efficient decimation method is proposed, considering the size of object, the amount of LIDAR data, etc. From these decimated data, object points and non-object points are distinguished using distance information which is a major features of LIDAR. After that, large and small values are extracted using local variations, which can be candidate for boundary. Finally, a boundary line is drawn based on the boundary point candidates. In this way, the approximate boundary of the object is extracted.