Accurate contour detection based on snakes for objects with boundary concavities

Authors:
Shin-Hyoung Kim;Ashraf Alattar;Jong Whan Jang
Affiliations:
PaiChai University, Daejeon, The Republic of Korea;PaiChai University, Daejeon, The Republic of Korea;PaiChai University, Daejeon, The Republic of Korea
Venue:
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Year:
2006

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Abstract

In this paper we present a snake-based scheme for efficiently detecting contours of objects with boundary concavities. The proposed method is composed of two steps. First, the object’s boundary is detected using the proposed snake model. Second, snake points are optimized by inserting new points and deleting unnecessary points to better describe the object’s boundary. The proposed algorithm can successfully extract objects with boundary concavities. Experimental results have shown that our algorithm produces more accurate segmentation results than the conventional algorithm.