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Proceedings Paper

Application of graph cut based active contour algorithm for contour extraction
Author(s): Hongwei Yue; Keqiang Wang; Chaojun Dong; Hong Man; Lu Cao
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Paper Abstract

With the wide application of machine vision technology in agricultural fields, the image-based pests diagnosis of rice planthoppers becomes a fast and effective approach. Although the effective automatic segmentation is a very important pretreatment technology for the analysis of rice planthopper images, the traditional graph cuts based active contour method has the shrinking bias problem during segmentation. This paper proposes an innovative approach to overcome that problem. By changing bidirection dilation of the contours to inside direction dilation to improve the overlap of adjacent contour neighborhoods and reduce the computation scale, the shrinking bias problem is improved effectively. The result shows that the approach adopted in this paper can clearly segment the contour of rice planthoppers.

Paper Details

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100331K (29 August 2016); doi: 10.1117/12.2243762
Show Author Affiliations
Hongwei Yue, Wuyi Univ. (China)
Keqiang Wang, Zhongkai Univ. of Agriculture and Engineering (China)
Chaojun Dong, Wuyi Univ. (China)
Hong Man, Wuyi Univ. (China)
Lu Cao, Wuyi Univ. (China)

Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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