Automatic Moving Object Segmentation Based on Edge Features

Zhang Xiao-yan; Zhao Rong-chun; Ma Zhi-qiang; Qian Yuan

doi:10.3724/SP.J.1146.2006.00196

Volume 29 Issue 2

Jan. 2011

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Article Navigation > Journal of Electronics & Information Technology > 2007 > 29(2): 460-464

Zhang Xiao-yan, Zhao Rong-chun, Ma Zhi-qiang, Qian Yuan. Automatic Moving Object Segmentation Based on Edge Features[J]. Journal of Electronics & Information Technology, 2007, 29(2): 460-464. doi: 10.3724/SP.J.1146.2006.00196

Citation:

Zhang Xiao-yan, Zhao Rong-chun, Ma Zhi-qiang, Qian Yuan. Automatic Moving Object Segmentation Based on Edge Features[J]. Journal of Electronics & Information Technology, 2007, 29(2): 460-464. doi: 10.3724/SP.J.1146.2006.00196

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Automatic Moving Object Segmentation Based on Edge Features

doi: 10.3724/SP.J.1146.2006.00196

Received Date: 2006-02-24
Rev Recd Date: 2006-09-18
Publish Date: 2007-02-19

Abstract

Abstract

In order to segment the moving objects accurately, an edge based moving objects segmentation algorithm is proposed in this paper. First of all, the initial edge model of the moving object is obtained on the basis of the adaptive change detection method and Canny edge detection. Secondly, the binary edge model is tracked and updated to accommodate rotation and changes in shape of the tracked object. Finally, the outer contour of the moving object is determined based on the mathematical morphological operation and an improved active contour which uses the gradient vector as the external force guides the initial outer contour moving to the actual contour. The proposed algorithm is robust to the entire motion and local deformation of object, adaptable to the complex background and can obtain the accurate moving object contour.

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References

[1] Kim M and Choi J G. A VOP generation tool: Automatic segmentation of moving objects in image sequences based on spatio-temporal information [J].IEEE Trans. on Circuits and Systems Video Technology.1999, 9(8):1216-1226 [2] 刘志, 杨杰, 彭宁嵩. 基于假设检验和区域合并的视频对象分割[J]. 数据采集与处理, 2004, 19(2): 124-129. [3] Meier T and Ngan K N. Automatic segmentation of moving objects for Video Object Plane Generation [J].IEEE Trans. on Circuits and Systems for Video Technology.1998, 8(5):525-538 [4] Kim C and Hwang J N. Fast and automatic video object segmentation and tracking for content-based application [J].IEEE Trans. on Circuits and Systems for Video Technology.2002, 12(2):122-129 [5] Rousseeuw P J and Leroy A M. Robust Regression and Outlier Detection [M]. New York .[J].John Wiley Sons.1987,:- [6] Canny J F. A computational approach to edge detection [J]. IEEE Trans. on Pattern Analysis and Machine Intelligent, 1986, 11(6): 679-698. [7] Kass M, Witkin A, and terzopoulos D. Snakes: active contour models [J].International Journal Computer Vision.1988, 1(4):321-331 [8] Xu C Y and Prince J L. Snake, shapes and gradient vector flow [J].IEEE Trans. on Image Processing.1998, 7(3):359-

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