• Title/Summary/Keyword: Object Contour Extraction

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Object Contour Extraction Algorithm Combined Snake with Level Set (스네이크와 레벨 셋 방법을 결합한 개체 윤곽 추출 알고리즘)

  • Hwang, JaeYong;Wu, Yingjun;Jang, JongWhan
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.5
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    • pp.195-200
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    • 2014
  • Typical methods of active contour model for object contour extraction are snake and level. Snake is usually faster than level set, but has limitation to compute topology of objects. Level set on the other hand is slower but good at it. In this paper, a new object contour extraction algorithm to use advantage of each is proposed. The algorithm is composed of two main steps. In the first step, snake is used to extract the rough contour and then in the second step, level set is applied to extract the complex contour exactly. 5 binary images and 2 natural images with different contours are simulated by a proposed algorithm. It is shown that speed is reduced and contour is better extracted.

An Extraction of Moving Object Contour Using Active Contour Model (능동 윤곽선 모델을 이용한 이동 물체 윤곽선 추출)

  • 이상욱;권태하
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.4 no.1
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    • pp.123-130
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    • 2000
  • In this paper, we propose an extracting method of moving object contour using active contour model from image sequences acquired by fixed camera. We use an adaptive background model for robust processing in surrounding conditions. Object segmentation model detects pixels thresholded from local difference image between background and current image and extracts connected regions. Noises in boundary area of moving object we eliminated by morphological filter. The contour of segmented object is corrected by using active contour model for extracting accurate boundary of moving object. We apply the proposed method to highway image sequences and show the results of simulation.

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Occlusion Processing in Simulation using Improved Object Contour Extraction Algorithm by Neighboring edge Search and MER (이웃 에지 탐색에 의한 개선된 객체 윤곽선 추출 알고리즘과 MER을 이용한 모의훈련에서의 폐색처리)

  • Cha, Jeong-Hee;Kim, Gye-Young;Choi, Hyung-Il
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.2
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    • pp.206-211
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    • 2008
  • Trainee can enhance his perception of and interaction with the real world by displayed virtual objects in simulation using image processing technology. Therefore, it is essential for realistic simulation to determine the occlusion areas of the virtual object produces after registering real image and virtual object exactly. In this paper, we proposed the new method to solve occlusions which happens during virtual target moves according to the simulated route on real image using improved object contour extraction by neighboring edge search and picking algorithm. After we acquire the detailed contour of complex objects by proposed contour extraction algorithm, we extract the three dimensional information of the position happening occlusion by using MER for performance improvement. In the experiment, we compared proposed method with existed method and preyed the effectiveness in the environment which a partial occlusions happens.

Active Contour Model for Boundary Detection of Multiple Objects (복수 객체의 윤곽 검출 방법에 대한 능동윤곽모델)

  • Jang, Jong-Whan
    • The KIPS Transactions:PartB
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    • v.17B no.5
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    • pp.375-380
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    • 2010
  • Most of previous algorithms of object boundary extraction have been studied for extracting the boundary of single object. However, multiple objects are much common in the real image. The proposed algorithm of extracting the boundary of each of multiple objects has two steps. In the first step, we propose the fast method using the outer and inner products; the initial contour including multiple objects is split and connected and each of new contours includes only one object. In the second step, an improved active contour model is studied to extract the boundary of each object included each of contours. Experimental results with various test images have shown that our algorithm produces much better results than the previous algorithms.

Contour Extraction of Moving Object using Connectivity of Motion Block (움직임 블록간 연결정보를 이용한 움직임 객체의 윤곽선 추출)

  • 김진희;이주호;정승도;최병욱
    • Proceedings of the IEEK Conference
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    • 2002.06c
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    • pp.231-234
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    • 2002
  • This paper proposes a new approach to extract contour of moving object from compressed video stream. We segment the area of moving object by using motion vector and extract the motion object block from it. And then we describe the connectivity direction of outline moving block, detect the edge related to connectivity direction in the block and finally obtain the contour by connecting the edges. This can divide the moving object only with motion vector and detect the exact contour on the basis of the edge automatically. Also, we can reduce spending time using motion block and remove the noise with directional edge. The experimental results demonstrate the accurate and effective qualify of the proposed method.

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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.

Video Object Extraction Using Contour Information (윤곽선 정보를 이용한 동영상에서의 객체 추출)

  • Kim, Jae-Kwang;Lee, Jae-Ho;Kim, Chang-Ick
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.1
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    • pp.33-45
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    • 2011
  • In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.

Arbitrary Object Contour Extraction using Active Contour Model (Active Contour Model을 이용한 임의의 물체 윤곽선 추출)

  • 문창수;유봉길;오승재;정종필;전희정
    • Journal of the Korea Society of Computer and Information
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    • v.4 no.4
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    • pp.77-85
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    • 1999
  • In this paper. improved the formula of Kass. First of all, improved initial guess inside and outside of an object. So, prevent the of shrink, find more easily and faster the contour of object. Secondly, proposed the algorithm which moved to local minimum with the improvement of formula of the internal energy and $3{times}3$ matrix. Process the noise of local minimum with use of medial filtering. In third, process the phenomenon which edge points gather one point with imposing energy to the energy term. Improve the algorithm to find the contour precisely with the use of threshold. The result of these improvements, make an initial guess easily and find the contour of objects which have higher curvature. Improve the speed of process by reducing the repetition of feedback system.

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Automation of Snake for Extraction of Multi-Object Contours from a Natural Scene (자연배경에서 여러 객체 윤곽선의 추출을 위한 스네이크의 자동화)

  • 최재혁;서경석;김복만;최흥문
    • Journal of KIISE:Computing Practices and Letters
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    • v.9 no.6
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    • pp.712-717
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    • 2003
  • A novel multi-snake is proposed for efficient extraction of multi-object contours from a natural scene. An NTGST(noise-tolerant generalized symmetry transform) is used as a context-free attention operator to detect and locate multiple objects from a complex background and then the snake points are automatically initialized nearby the contour of each detected object using symmetry map of the NTGST before multiple snakes are introduced. These procedures solve the knotty subjects of automatic snake initialization and simultaneous extraction of multi-object contours in conventional snake algorithms. Because the snake points are initialized nearby the actual contour of each object, as close as possible, contours with high convexity and/or concavity can be easily extracted. The experimental results show that the proposed method can efficiently extract multi-object contours from a noisy and complex background of natural scenes.

Contour Extraction Method using p-Snake with Prototype Energy (원형에너지가 추가된 p-Snake를 이용한 윤곽선 추출 기법)

  • Oh, Seung-Taek;Jun, Byung-Hwan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.4
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    • pp.101-109
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    • 2014
  • It is an essential element for the establishment of image processing related systems to find the exact contour from the image of an arbitrary object. In particular, if a vision system is established to inspect the products in the automated production process, it is very important to detect the contours for standardized shapes such lines and curves. In this paper, we propose a prototype adaptive dynamic contour model, p-Snake with improved contour extraction algorithms by adding the prototype energy. The proposed method is to find the initial contour by applying the existing Snake algorithm after Sobel operation is performed for prototype analysis. Next, the final contour of the object is detected by analyzing prototypes such as lines and circles, defining prototype energy and using it as an additional energy item in the existing Snake function on the basis of information on initial contour. We performed experiments on 340 images obtained by using an environment that duplicated the background of an industrial site. It was found that even if objects are not clearly distinguished from the background due to noise and lighting or the edges being insufficiently visible in the images, the contour can be extracted. In addition, in the case of similarity which is the measure representing how much it matches the prototype, the prototype similarity of contour extracted from the proposed p-ACM is superior to that of ACM by 9.85%.