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Proceedings Paper

Rectification-adapted snake for complex-boundary segmentation in noisy images
Author(s): Din-Yuen Chan; Roy Chaoming Hsu; Pang-Hao Wu; Cheng-Ting Liu
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Paper Abstract

In this paper, a contour-fitness improved adaptive snake, namely, edge-conducted rectification-adapted snake (ECRA-snake) is proposed for segmenting complex-boundary objects in the noisy image. The ECRA-snake includes a main ingredient called edge-conducted evolution (ECE), where the adaptations of model coefficients can accommodate ECE itself to the characteristics of salient edges for better curve fitting in tracking. Following ECE, a direction-induced rectification evolution (DIRE) will correct boundary-unmatched snake fragments by handling the initial direction and the tensile-force weighting of unqualified snaxels in this snake re-evolution. Simulation results demonstrate that the proposed ECRA-snake can obtain better object-boundary coincidence than the Gradient Vector Flow (GVF) model in segmenting the complex-boundary object from noisy images.

Paper Details

Date Published: 14 March 2013
PDF: 6 pages
Proc. SPIE 8768, International Conference on Graphic and Image Processing (ICGIP 2012), 87687H (14 March 2013); doi: 10.1117/12.2010100
Show Author Affiliations
Din-Yuen Chan, National Chiayi Univ. (Taiwan)
Roy Chaoming Hsu, National Chiayi Univ. (Taiwan)
Pang-Hao Wu, National Chiayi Univ. (Taiwan)
Cheng-Ting Liu, National Chiayi Univ. (Taiwan)


Published in SPIE Proceedings Vol. 8768:
International Conference on Graphic and Image Processing (ICGIP 2012)
Zeng Zhu, Editor(s)

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