Novel Target Segmentation and Tracking Based on Fuzzy Membership Distribution for Vision-based Target Tracking SystemNovel Target Segmentation and Tracking Based on Fuzzy Membership Distribution for Vision-based Target Tracking System
- Other Titles
- Novel Target Segmentation and Tracking Based on Fuzzy Membership Distribution for Vision-based Target Tracking System
- Authors
- 김병규; Park, DJ (Park, Dong-Jo)
- Issue Date
- Dec-2006
- Publisher
- ELSEVIER LTD
- Keywords
- image segmentation; target detection; three-dimensional feature; fuzzy membership value; optimal membership value
- Citation
- IMAGE AND VISION COMPUTING, v.24, no.12, pp 1319 - 1331
- Pages
- 13
- Journal Title
- IMAGE AND VISION COMPUTING
- Volume
- 24
- Number
- 12
- Start Page
- 1319
- End Page
- 1331
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/148518
- DOI
- 10.1016/j.imavis.2006.04.008
- ISSN
- 0262-8856
1872-8138
- Abstract
- One of the basic processes of a vision-based target tracking system is the detection process that separates an object from the background in a given image. A novel target detection technique for suppression of the background clutter is presented that uses a predicted point that is estimated from a tracking filter. For every pixel, the three-dimensional feature that is composed of the x-position, the y-position and the gray level of its position is used for evaluating the membership value that describes the probability of whether the pixel belongs to the target or to the background. These membership values are transformed into the membership level histogram. We suggest an asymmetric Laplacian model for the membership distribution of the background pixel and determine the optimal membership value for detecting the target region using the likelihood criterion. The proposed technique is applied to several infra-red image sequences and CCD image sequences to test segmentation and tracking. The feasibility of the proposed method is verified through comparison of the experimental results with the other techniques. (c) 2006 Elsevier B.V. All rights reserved.
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