• Title/Summary/Keyword: 윤곽추적

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An Enhancement of Removing Noise Branches by Detecting Noise Blobs (잡영블랍 검출에 의한 잡영가지 제거 방법의 개선)

  • 김성옥;임은경;김민환
    • Journal of Korea Multimedia Society
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    • v.6 no.3
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    • pp.419-428
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    • 2003
  • Several methods have been studied to prune the parasitic branches that cause unfortunately from thinning a shape to get its skeleton. We found that the symmetric path finding method was most efficient because it followed the boundary pixels of the shape just once. In this paper, its extended method is proposed to apply to removing the noise branches that protrude out of the boundary of a segmented or extracted shape in a given image. The proposed method can remove a noise branch with one-pixel width and also remove the noise branch that includes a round shape called a noise blob. The method uses a 4-8-directional boundary-following technique to determine symmetric paths and finds noise branches with noise blobs by detecting quasi-symmetric paths. Its time complexity is a linear function of the number of boundary pixels. Interactively selectable parameters are used to define various types of noise branches flexibly, which are the branch - size parameter and the blob-size parameter. Experimental results for a practical shape and various artificial shapes showed that the proposed method was very useful for simplifying the shapes.

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A Study on Auto Inspection System of Cross Coil Movement Using Machine Vision (머신비젼을 이용한 Cross Coil Movement 자동검사 시스템에 관한 연구)

  • Lee, Chul-Hun;Seol, Sung-Wook;Joo, Jae-Heum;Lee, Sang-Chan;Nam, Ki-Gon
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.11
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    • pp.79-88
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    • 1999
  • In this paper we address the tracking method which tracks only target object in image sequence including moving object. We use a contour tracking algorithm based on intensity and motion boundaries. The motion of the moving object contour in the image is assumed to be well describable by an affine motion model with a translation, a change in scale and a rotation. The moving object contour is represented by B-spline, the position and motion of which is estimated along the image sequence. we use pattern recognition to identify target object. In order to use linear Kalman Filters we decompose the estimation process into two filters. One is estimating the affine motion parameters and the other the shape of moving object contour. In some experiments with dial plate we show that this method enables us to obtain the robust motion estimates and tracking trajectories even in case of including obstructive object.

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Recognition of Container Identifier using Color Information and Contour Following (컬러 정보와 윤곽선 추적을 이용한 컨테이너 식별자 인식)

  • Kim Pyeoung-Kee
    • Journal of Korea Society of Industrial Information Systems
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    • v.11 no.3
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    • pp.40-46
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    • 2006
  • Automatic recognition of container identifier is one of key factor to implement port automation and increase distribution throughput. In this paper, I propose a method of container identifier recognition on various input images using color based edge detection and character verification algorithm, I tested the proposed method on 350 container images and it showed good results.

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Object boundary tracking using modified boundary tracking algorithm (개선된 체인코드틀 이용한 물체 윤곽선 추척)

  • Kim, Yuk;Kwon, Woo-Hyen;Koo, Bon-Ho;Youn, Kyung-Sup
    • Proceedings of the KIEE Conference
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    • 2007.10a
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    • pp.411-412
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    • 2007
  • 본 논문에서는 경계선 추적에 널리 사용되고 있는 체인코드를 개선하여 윤곽선 추적 시 시간과 메모리 효율을 개선하였다. 일반적으로 정형화된 물체는 윤곽선의 동선이 대부분 이전 검색동선과 같은 방향으로 움직인다. 기존의 8방향 체인코드에는 같은 동선에 있는 경계선이라도 픽셀하나당 한번 씩 검사를 한다. 개선된 체인코드는 확인된 경계영역에서 상하좌우, 대각선 방향으로 한 픽셀씩 더 확인하여 기존 체인코드보다 시간과 메모리 효율을 개선할 수 있다.

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Motion-Estimated Active Rays-Based Fast Moving Object Tracking (움직임 추정 능동 방사선 기반 고속 객체 추적)

  • Ra Jeong-Jung;Seo Kyung-Seok;Choi Hung-Moon
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.3 s.303
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    • pp.15-22
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    • 2005
  • This paper proposed a object tracking algorithm which can track contour of fast moving object through motion estimation. Since the proposed tracking algorithm is based on the radial representation, the motion estimation of object can be accomplished at the center of object with the low computation complexity. The motion estimation of object makes it possible to track object which move fast more than distance from center point to contour point for each frame. In addition, by introducing both gradient image and difference image into energy functions in the process of energy convergence, object tracking is more robust to the complex background. The results of experiment show that the proposed algorithm can track fast moving object in real-time and is robust under the complex background.

Mobile Robot Control using Hand Shape Recognition (손 모양 인식을 이용한 모바일 로봇제어)

  • Kim, Young-Rae;Kim, Eun-Yi;Chang, Jae-Sik;Park, Se-Hyun
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.4
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    • pp.34-40
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    • 2008
  • This paper presents a vision based walking robot control system using hand shape recognition. To recognize hand shapes, the accurate hand boundary needs to be tracked in image obtained from moving camera. For this, we use an active contour model-based tracking approach with mean shift which reduces dependency of the active contour model to location of initial curve. The proposed system is composed of four modules: a hand detector, a hand tracker, a hand shape recognizer and a robot controller. The hand detector detects a skin color region, which has a specific shape, as hand in an image. Then, the hand tracking is performed using an active contour model with mean shift. Thereafter the hand shape recognition is performed using Hue moments. To assess the validity of the proposed system we tested the proposed system to a walking robot, RCB-1. The experimental results show the effectiveness of the proposed system.

Combined Active Contour Model and Motion Estimation for Real-Time Object Tracking (능동윤곽모델과 움직임 추정을 결합한 실시간 객체 추적 기술)

  • Kim, Dae-Hee;Lee, Dong-Eun;Paik, Joon-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.5
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    • pp.64-72
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    • 2007
  • In this paper we proposed a combined active contour model and motion estimation-based object tracking technique. After assigning the initial contour, we find the object's boundary and update the initial contour by using object's motion information. In the following frames, similar snake algorithm is repeated to make continuously estimated object's region. The snake algerian plays a role in separating the object from background, while motion estimation provides object's moving direction and displacement. The proposed algorithm provides equivalently stable, robust, tracking performance with significantly reduced amount of computation, compared with the existing shape model-based algorithms.

Modeling of compensator fabrication for missing tissue using RFID Tag in U-Health (U-Health 환경에서 RFID Tag를 이용한 결손조직보상체 모델링)

  • Choi O-Hoon;Kim Young-Bum;Lim Jung-Eun;Na Hong-Seok;Baek Du-Gwon
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06a
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    • pp.10-12
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    • 2006
  • U-Health에 대한 연구는 환자, 의료장비에 대한 위치 추적을 통한 의료업무 지원관리 분야로 집중되고 있다. 본 논문에서는 RFID Tag를 의료 측정에 적용한다. 즉, RFID Tag를 이용하여 방사선치료에서 사용되는 결손조직 보상체의 체표 윤곽을 모델링하는 방법을 제안한다. 기존의 모델링 방법은 환자의 체표 윤곽을 컴퓨터단층촬영이나 자기공명촬영을 사용한 의료영상을 이용해왔다. 이러한 방법은 고가의 비용이 소요되고 방사선치료에 따른 체표윤곽의 변화에 대응하지 못한다. 본 연구에서는 U-Health에서 기본적으로 사용하는 RFID Tag를 환자의 체표윤각에 고정하여 3차원 위치정보를 획득한다. 체표윤곽에 위치한 RFID의 상대적 위치를 통해 결손조직 보상체를 제작하고 이의 유용성 평가를 위해 기하학적, 선량학적 평가를 수행하였다.

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A Semantic Video Object Tracking Algorithm Using Contour Refinement (윤곽선 재조정을 통한 의미 있는 객체 추적 알고리즘)

  • Lim, Jung-Eun;Yi, Jae-Youn;Ra, Jong-Beom
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.6
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    • pp.1-8
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    • 2000
  • This paper describes an algorithm for semantic video object tracking using semi automatic method. In the semi automatic method, a user specifies an object of interest at the first frame and then the specified object is to be tracked in the remaining frames. The proposed algorithm consists of three steps: object boundary projection, uncertain area extraction, and boundary refinement. The object boundary is projected from the previous frame to the current frame using the motion estimation. And uncertain areas are extracted via two modules: Me error-test and color similarity test. Then, from extracted uncertain areas, the exact object boundary is obtained by boundary refinement. The simulation results show that the proposed video object extraction method provides efficient tracking results for various video sequences compared to the previous methods.

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