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Journal Article Novel Target Segmentation and Tracking Based on Fuzzy Membership Distribution for Vision-based Target Tracking System
Cited 18 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Byung Gyu Kim, Dong Jo Park
Issue Date
2006-12
Citation
Image and Vision Computing, v.24, no.12, pp.1319-1331
ISSN
0262-8856
Publisher
Elsevier
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1016/j.imavis.2006.04.008
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. © 2006 Elsevier B.V. All rights reserved.