• Title/Summary/Keyword: active contour model

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Adaptive prototype generating technique for improving performance of a p-Snake (p-Snake의 성능 향상을 위한 적응 원형 생성 기법)

  • Oh, Seung-Taek;Jun, Byung-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.4
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    • pp.2757-2763
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    • 2015
  • p-Snake is an energy minimizing algorithm that applies an additional prototype energy to the existing Active Contour Model and is used to extract the contour line in the area where the edge information is unclear. In this paper suggested the creation of a prototype energy field that applies a variable prototype expressed as a combination of circle and straight line primitives, and a fudge function, to improve p-Snake's contour extraction performance. The prototype was defined based on the parts codes entered and the appropriate initial contour was extracted in each primitive zones acquired from the pre-processing process. Then, the primitives variably adjusted to create the prototype and the contour probability based on the distance to the prototype was calculated through the fuzzy function to create the prototype energy field. This was applied to p-Snake to extract the contour from 100 images acquired from various small parts and compared its similarity with the prototype to find that p-Snake made with the adaptive prototype was about 4.6% more precise than the existing Snake method.

Performance evaluation of vessel extraction algorithm applied to Aortic root segmentation in CT Angiography (CT Angiography 영상에서 대동맥 추출을 위한 혈관 분할 알고리즘 성능 평가)

  • Kim, Tae-Hyong;Hwang, Young-sang;Shin, Ki-Young
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.2
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    • pp.196-204
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    • 2016
  • World Health Organization reported that heart-related diseases such as coronary artery stenoses show the highest occurrence rate which may cause heart attack. Using Computed Tomography angiography images will allow radiologists to detect and have intervention by creating 3D roadmapping of the vessels. However, it is often complex and difficult do reconstruct 3D vessel which causes very large amount of time and previous researches were studied to segment vessels more accurate automatically. Therefore, in this paper, Region Competition, Geodesic Active Contour (GAC), Multi-atlas based segmentation and Active Shape Model algorithms were applied to segment aortic root from CTA images and the results were analyzed by using mean Hausdorff distance, volume to volume measure, computational time, user-interaction and coronary ostium detection rate. As a result, Extracted 3D aortic model using GAC showed the highest accuracy but also showed highest user-interaction results. Therefore, it is important to improve automatic segmentation algorithm in future

Visual Tracking Technique Based on Projective Modular Active Shape Model (투영적 모듈화 능동 형태 모델에 기반한 영상 추적 기법)

  • Kim, Won
    • Journal of the Korea Society for Simulation
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    • v.18 no.2
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    • pp.77-89
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    • 2009
  • Visual tracking technique is one of the essential things which are very important in the major fields of modern society. While contour tracking is especially necessary technique in the aspect of its fast performance with target's external contour information, it sometimes fails to track target motion because it is affected by the surrounding edges around target and weak egdes on the target boundary. To overcome these weak points, in this research it is suggested that PDMs can be obtained by generating the virtual 6-DOF motions of the mobile robot with a CCD camera and the image tracking system which is robust to the local minima around the target can be configured by constructing Active Shape Model in modular base. To show the effectiveness of the proposed method, the experiment is performed on the image stream obtained by a real mobile robot and the better performance is confirmed by comparing the experimental results with the ones of other major tracking techniques.

Facial Contour Extraction in PC Camera Images using Active Contour Models (동적 윤곽선 모델을 이용한 PC 카메라 영상에서의 얼굴 윤곽선 추출)

  • Kim Young-Won;Jun Byung-Hwan
    • Proceedings of the Korea Contents Association Conference
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    • 2005.11a
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    • pp.633-638
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    • 2005
  • The extraction of a face is a very important part for human interface, biometrics and security. In this paper, we applies DCM(Dilation of Color and Motion) filter and Active Contour Models to extract facial outline. First, DCM filter is made by applying morphology dilation to the combination of facial color image and differential image applied by dilation previously. This filter is used to remove complex background and to detect facial outline. Because Active Contour Models receive a large effect according to initial curves, we calculate rotational degree using geometric ratio of face, eyes and mouth. We use edgeness and intensity as an image energy, in order to extract outline in the area of weak edge. We acquire various head-pose images with both eyes from five persons in inner space with complex background. As an experimental result with total 125 images gathered by 25 per person, it shows that average extraction rate of facial outline is 98.1% and average processing time is 0.2sec.

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Segmentation Algorithm for Wafer ID using Active Multiple Templates Model

  • Ahn, In-Mo;Kang, Dong-Joong;Chung, Yoon-Tack
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.839-844
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    • 2003
  • This paper presents a method to segment wafer ID marks on poor quality images under uncontrolled lighting conditions of the semiconductor process. The active multiple templates matching method is suggested to search ID areas on wafers and segment them into meaningful regions and it would have been impossible to recognize characters using general OCR algorithms. This active template model is designed by applying a snake model that is used for active contour tracking. Active multiple template model searches character areas and segments them into single characters optimally, tracking each character that can vary in a flexible manner according to string configurations. Applying active multiple templates, the optimization of the snake energy is done using Greedy algorithm, to maximize its efficiency by automatically controlling each template gap. These vary according to the configuration of character string. Experimental results using wafer images from real FA environment are presented.

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Hierarchical active shape model-based video object tracking using wavelet transform (웨이블릿을 이용한 계층적 능동형태모델 기반 비디오 추적기술)

  • ;Vivek Maik
    • Proceedings of the IEEK Conference
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    • 2003.11a
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    • pp.161-164
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    • 2003
  • This paper proposes a hierarchical approach to active shape model using wavelet transform. The proposed algorithm allows us to use both global shape characteristics and finer details for model deformation. The statistical properties of the wavelet transform of a deformable model are analyzed by principal component analysis and used as priors in the contour's deformation.

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Face Tracking System using Active Appearance Model (Active Appearance Model을 이용한 얼굴 추적 시스템)

  • Cho, Kyoung-Sic;Kim, Yong-Guk
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.1044-1049
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    • 2006
  • 얼굴 추적은 Vision base HCI의 핵심인 얼굴인식, 표정인식 그리고 Gesture recognition등의 다른 여러 기술을 지원하는 중요한 기술이다. 이런 얼굴 추적기술에는 영상(Image)의 Color또는 Contour등의 불변하는 특징들을 사용 하거나 템플릿(template)또는 형태(appearance)를 사용하는 방법 등이 있는데 이런 방법들은 조명환경이나 주위 배경등의 외부 환경에 민감하게 반응함으로 해서 다양한 환경에 사용할 수 없을 뿐더러 얼굴영상만을 정확하게 추출하기도 쉽지 않은 실정이다. 이에 본 논문에서는 deformable한 model을 사용하여 model과 유사한 shape과 appearance를 찾아 내는 AAM(Active Appearance Model)을 사용하는 얼굴 추적 시스템을 제안하고자 한다. 제안된 시스템에는 기존의 Combined AAM이 아닌 Independent AAM을 사용하였고 또한 Fitting Algorithm에 Inverse Compositional Image Alignment를 사용하여 Fitting 속도를 향상 시켰다. AAM Model을 만들기 위한 Train set은 150장의 4가지 형태에 얼굴을 담고 있는 Gray-scale 영상을 사용 하였다. Shape Model은 각 영상마다 직접 표기한 47개의 Vertex를 Trianglize함으로서 생성되는 71개의 Triangles을 하나의 Mesh로 구성하여 생성 하였고, Appearance Model은 Shape 안쪽의 모든 픽셀을 사용해서 생성하였다. 시스템의 성능 평가는 Fitting후 Shape 좌표의 정확도를 측정 함으로서 평가 하였다.

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The improved image filter for the purpose of controlling the image energy in the Active Contour Model (활성 윤곽선 모델의 영상 에너지 제어를 위한 개선된 영상 필터)

  • 강중욱;최경민;박용희;전병호;김태균
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10c
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    • pp.520-522
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    • 1998
  • 활성 윤곽선 모델(Active Contour Model : Snake)을 이용한 윤곽선 추출 방법에서는 물체를 검출하기 위해 잠재적 표면(potential surface) 위에서 지역 최소치를 향하여 다양한 힘을 가함으로써 물체의 윤곽선으로 활성 윤곽선 모델을 움직이게 한다. 활성 윤곽선 모델에서 영상의 관심있는 물체를 검출하기 위해서는 영상의 잠재적 표면 위에서 활성 윤곽선 모델이 지역 최소치를 향하여 활동적으로 움직이도록 다양한 힘을 효과적으로 제어해야 한다. 본 논문에서는 활성 윤곽선 모델이 적합한 지역 최소치를 향하여 적절하게 수렴하도록 활성 윤곽선 모델이 움직이는 잠재적 표면을 변형할 수 있는 영상 필터를 제안한다.

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A Geometric Active Contour Model Using Multi Resolution Level Set Methods (다중 해상도 레벨 세트 방식을 이용한 기하 활성 모델)

  • Kim, Seong-Gon;Kim, Du-Yeong
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.10
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    • pp.2809-2815
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    • 1999
  • Level set, and active contour(snakes) models are extensively used for image segmentation or shape extraction in computer vision. Snakes utilize the energy minimization concepts, and level set is based on the curve evolution in order to extract contours from image data. In general, these two models have their own drawbacks. For instance, snake acts pooly unless it is placed close to the wanted shape boundary, and it has difficult problem when image has multiple objects to be extracted. But, level set method is free of initial curve position problem, and has ability to handle topology of multiple objects. Nevertheless, level set method requires much more calculation time compared to snake model. In this paper, we use good points of two described models and also apply multi resolution algorithm in order to speed up the process without decreasing the performance of the shape extraction.

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A Study on the Object Segmentation Using Active Contour Model based MPEG-4 (MPEG-4 기반의 능동윤곽모델을 이용한 스테레오 영상에서의 객체분할에 관한 연구)

  • Kim, Shin-Hyoung;Chun, Byung-Tea;Park, Doo-Yeong;Jang, Jong-Whan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11a
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    • pp.57-60
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    • 2002
  • 본 논문에서는 능동윤곽모델(active contour model)의 잘 알려져 있는 스네이크(snake) 알고리즘을 스테레오영상에 적용하여 좌 우 영상의 disparity 정보를 이용 객체의 경계선을 찾는 알고리즘을 제안한다. 스네이크는 객체의 경계를 얻기 위해 에지정보를 사용하는데 실제 이미지에서 객체의 경계가 아닌 인접한 주위의 강한 애지(edge)에 대해서도 영향을 받게 되는 문제가 있다. 이러한 문제를 해결하기 위해 스테레오영상의 disparity 정보를 이용하여 이를 개선하고 disparity 측정에 사용되는 블록매칭(block matching)방법을 스네이크 알고리즘에 적용시켰다.

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