Gradient vector flow active contours with prior directional information

  • Authors:

  • Guopu Zhu;Shuqun Zhang;Qingshuang Zeng;Changhong Wang

  • Affiliations:

  • GuangDong Key Lab. of Information Security, Sun Yat-Sen University, Guangzhou 510006, China;Department of Computer Science, College of Staten Island, City University of New York, Staten Island, NY 10314, USA;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, China;Space Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, China

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2010

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Abstract

Active contours, or snakes, have been widely used in image processing and computer vision for image segmentation and object tracking. However, they usually have poor performance in segmenting images with complex object shape and complex background, and also in dealing with the issue of weak-edge-leakage. To guide the front of active contour toward the desired object boundary and prevent it from moving over the weak edges with strong neighbors, we present a novel external force field, referred to as gradient and direction vector flow (G&DVF), which integrates the gradient vector flow (GVF) and the prior directional information provided by a user. The proposed method is sufficiently general and simple to implement. The experiments conducted on image segmentation demonstrate that the proposed method is insensitive to image clutters/noise and capable of driving the fronts of active contours to conform to complex shapes and addressing the issue of weak-edge-leakage in some cases.