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L. Zagorchev, A. Goshtasby and M. Satter, “R-Snakes,” Image and Vision Computing, Vol. 25, No. 6, 2007, pp. 945-959. doi:10.1016/j.imavis.2006.07.008

has been cited by the following article:

• TITLE: An Improved Algorithm Based on the GVF-Snake for Effective Concavity Edge Detection

  AUTHORS: Mengmeng Zhang, Qianqian Li, Lei Li, Peirui Bai

  KEYWORDS: Image Segmentation; the GVF-Snake; Boundary Concavities; Balloon Force; Tangential Force

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.6 No.4, April 25, 2013

  ABSTRACT: Image segmentation is an important research area in Computer Vision and the GVF-snake is an effective segmentation algorithm presented in recent years. Traditional GVF-snake algorithm has a large capture range and can deal with boundary concavities. However, when interesting object has deep concavities, traditional GVF-snake algorithm can’t converge to true boundaries exactly. In this paper, a novel improved scheme was proposed based on the GVF-snake. The central idea is introduce dynamic balloon force and tangential force to strengthen the static GVF force. Experimental results of synthetic image and real image all demonstrated that the improved algorithm can capture boundary concavities better and detect complex edges more accurately.