29 August 2016 Application of graph cut based active contour algorithm for contour extraction
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Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100331K (2016) https://doi.org/10.1117/12.2243762
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China
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.
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Hongwei Yue, Hongwei Yue, Keqiang Wang, Keqiang Wang, Chaojun Dong, Chaojun Dong, Hong Man, Hong Man, Lu Cao, Lu Cao, } "Application of graph cut based active contour algorithm for contour extraction", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100331K (29 August 2016); doi: 10.1117/12.2243762; https://doi.org/10.1117/12.2243762
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