• Title/Summary/Keyword: Active contour model

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Improvement of Active Contour Model for Detection of Pulmonary Region in Medical Image (의학 영상에서 폐 영역 검출을 위한 Active Contour 모델 개선)

  • Kwon Y. J.;Won C. H.;Park H. J.;Lee J. H.;Lee S. H.;Cho J. H.
    • Journal of Korea Multimedia Society
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    • v.8 no.3
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    • pp.336-344
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    • 2005
  • In this paper, we extracted the contour of lung parenchyma on EBT images with the improved active contour model. The objects boundary in conventional active contour model can be extracted by controlling internal energy and external energy as energy minimizing form. However, there are a number of problems such as initialization and the poor convergence about concave part. Expecially, contour can not enter the concave region by discouraging characteristic about stretching and bending in internal energy. We controlled internal energy by moving local perpendicular bisector point of each control point in the contour and implemented the object boundary by minimizing energy with external energy The convergence of concave part could be efficiently implemented toward lung parenchyma region by this internal energy and both lung images for initial contour could also be detected by multi-detection method. We were sure this method could be applied detection of lung parenchyma region in medical image.

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Tracking a Moving Object Using an Active Contour Model Based on a Frame Difference Map (차 영상 맵 기반의 능동 윤곽선 모델을 이용한 이동 물체 추적)

  • 이부환;김도종;최일;전기준
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.153-163
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    • 2004
  • This paper presents a video tracking method for a deformable moving object using an active contour model in the image sequences. It is quite important to decide the local convergence directions of the contour points for correctly extracting the boundary of the moving object with deformable shape. For this purpose, an energy function for the active contour model is newly proposed by adding a directional energy term using a frame difference map to tile Greedy algorithm. In addition, an updating rule of tile frame difference map is developed to encourage the stable convergence of the contour points. Experimental results on a set of synthetic and real image sequences showed that the proposed method can fully track the deformable object while extracting the boundary of the object elaborately in every frame.

Vehicle Tracking using Parametric Active Contour (Parametric Active Contour를 이용한 Vehicle Tracking)

  • 나상일;이웅희;조익환;정동석
    • Proceedings of the IEEK Conference
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    • 2003.07d
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    • pp.1411-1414
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    • 2003
  • In this paper, vehicle tracking is implemented using parametric active contour. Extract objects from the background area is the essential step in vehicle tracking. We focus our algorithm on the situations such that the camera is fixed. However, if a simple and ordinary algorithm is adapted to achieve real-time processing, it produces much noise and the vehicle tracking results is poor. For this reason, in this paper, we propose a parametric active contour model algorithm to achieve better vehicle tracking. Experimental results show that the performance of the proposed algorithm is satisfactory.

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Research on the Tracking Algorithm applied by Active Contour Models (Active Contour Model을 응용한 추적 알고리즘에 관한 연구)

  • 장재혁;한성현;이만형
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.295-298
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    • 1995
  • We performed a research to improve the performance of active bar model which is used in tracking algorithm. Active bar model is a simplified model of snake model. If we used the sctive bar model, the numerical procedure for real time tracking problem can be carried out faster than snake model. However the demerit of active bar algorithms is that we can't used the provious image data because each time it has to reconstruct the active bar. In this paper we proposed advanced algorithm for active bar model. The proposed model can improve tracking abilities by preserving the active bar during the process and changing the energy functional.

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Moving Object Tracking Using Active Contour Model (동적 윤곽 모델을 이용한 이동 물체 추적)

  • Han, Kyu-Bum;Baek, Yoon-Su
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.5
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    • pp.697-704
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    • 2003
  • In this paper, the visual tracking system for arbitrary shaped moving object is proposed. The established tracking system can be divided into model based method that needs previous model for target object and image based method that uses image feature. In the model based method, the reliable tracking is possible, but simplification of the shape is necessary and the application is restricted to definite target mod el. On the other hand, in the image based method, the process speed can be increased, but the shape information is lost and the tracking system is sensitive to image noise. The proposed tracking system is composed of the extraction process that recognizes the existence of moving object and tracking process that extracts dynamic characteristics and shape information of the target objects. Specially, active contour model is used to effectively track the object that is undergoing shape change. In initializatio n process of the contour model, the semi-automatic operation can be avoided and the convergence speed of the contour can be increased by the proposed effective initialization method. Also, for the efficient solution of the correspondence problem in multiple objects tracking, the variation function that uses the variation of position structure in image frame and snake energy level is proposed. In order to verify the validity and effectiveness of the proposed tracking system, real time tracking experiment for multiple moving objects is implemented.

Stereovision by Active Surface Model

  • Yokomichi, M.;Sugiyama, H.;Kono, M.
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1990-1993
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    • 2005
  • Stereovision is known to be one of the most important tools for robot vision systems. Previously, 2D active contour model has been applied to stereovision by defining the contour on the 3D space instead of image plane. However, the proposed model is still that of curve so that some complex shapes such as surfaces with high curvature can not be properly estimated because of occlusion phenomena. In this paper, the authors extend the curve model to the surface model. The surface is approximated by polygons and new energy function and its optimization method for surface estimation is proposed. Its effectiveness is examined by experiments with real stereo images.

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Adaptive Active Contour Model: a Localized Mutual Information Approach for Medical Image Segmentation

  • Dai, Shuanglu;Zhan, Shu;Song, Ning
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.5
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    • pp.1840-1855
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    • 2015
  • Troubles are often met when traditional active contours extract boundaries of medical images with inhomogeneous bias and various noises. Focusing on such a circumstance, a localized mutual information active contour model is discussed in the paper. By defining neighborhood of each point on the level set, mutual information is introduced to describe the relationship between the zero level set and image field. A driving energy term is then generated by integrating all the information. In addition, an expanding energy and internal energy are designed to regularize the driving energy. Contrary to piecewise constant model, new model has a better command of driving the contours without initialization.

Energy Minimization Model for Pattern Classification of the Movement Tracks (행동궤적의 패턴 분류를 위한 에너지 최소화 모델)

  • Kang, Jin-Sook;Kim, Jin-Sook;Cha, Eul-Young
    • The KIPS Transactions:PartB
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    • v.11B no.3
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    • pp.281-288
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    • 2004
  • In order to extract and analyze complex features of the behavior of animals in response to external stimuli such as toxic chemicals, we implemented an adaptive computational method to characterize changes in the behavior of chironomids in response to treatment with the insecticide, diazinon. In this paper, we propose an energy minimization model to extract the features of response behavior of chironomids under toxic treatment, which is applied on the image of velocity vectors. It is based on the improved active contour model and the variations of the energy functional, which are produced by the evolving active contour. The movement tracks of individual chironomid larvae were continuously measured in 0.25 second intervals during the survey period of 4 days before and after the treatment. Velocity on each sample track at 0.25 second intervals was collected in 15-20 minute periods and was subsequently checked to effectively reveal behavioral states of the specimens tested. Active contour was formed around each collection of velocities to gradually evolve to find the optimal boundaries of velocity collections through processes of energy minimization. The active contour which is improved by T. Chan and L. Vese is used in this paper. The energy minimization model effectively revealed characteristic patterns of behavior for the treatment versus no treatment, and identified changes in behavioral states .is the time progressed.

Active Contour Model Based Object Contour Detection Using Genetic Algorithm with Wavelet Based Image Preprocessing

  • Mun, Kyeong-Jun;Kang, Hyeon-Tae;Lee, Hwa-Seok;Yoon, Yoo-Sool;Lee, Chang-Moon;Park, June-Ho
    • International Journal of Control, Automation, and Systems
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    • v.2 no.1
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    • pp.100-106
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    • 2004
  • In this paper, we present a novel, rapid approach for the detection of brain tumors and deformity boundaries in medical images using a genetic algorithm with wavelet based preprocessing. The contour detection problem is formulated as an optimization process that seeks the contour of the object in a manner of minimizing an energy function based on an active contour model. The brain tumor segmentation contour, however, cannot be detected in case that a higher gradient intensity exists other than the interested brain tumor and deformities. Our method for discerning brain tumors and deformities from unwanted adjacent tissues is proposed. The proposed method can be used in medical image analysis because the exact contour of the brain tumor and deformities is followed by precise diagnosis of the deformities.

Comparison of Genetic Algorithm and Simulated Annealing Optimization Technique to Minimize the Energy of Active Contour Model (유전자 알고리즘과 시뮬레이티드 어닐링을 이용한 활성외곽선모델의 에너지 최소화 기법 비교)

  • Park, Sun-Young;Park, Joo-Young;Kim, Myoung-Hee
    • Journal of the Korea Computer Graphics Society
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    • v.4 no.1
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    • pp.31-40
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    • 1998
  • Active Contour Model(ACM) is an efficient method for segmenting an object. The main shortcoming of ACM is that its result is very dependent on the shape and location of an initial contour. To overcome this shortcoming, a new segmentation algorithm is proposed in this paper. The proposed algorithm uses B-splines to describe the active contour and applies Simulated Annealing (SA) and Genetic Algorithm(GA) as energy minimization techniques. We tried to overcome the initialization problem of traditional ACM and compared the result of ACM using GA and that using SA with 2D synthetic binary images. CT and MR images.

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