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Accurate Contour Detection Based on Snakes for Objects with Boundary Concavities

  • Shin-Hyoung Kim
  • Ashraf Alattar
  • Jong Whan Jang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4141)

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.

Keywords

Active Contour Object Segmentation Gradient Vector Flow Snake Model Snake Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shin-Hyoung Kim
    • 1
  • Ashraf Alattar
    • 1
  • Jong Whan Jang
    • 1
  1. 1.PaiChai UniversityDaejeonThe Republic of Korea

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