A Hybrid Method for Automatic and Highly Precise VHD Background Removal

  • Authors:

  • Chen Ding;Yankui Sun;Xiaolin Tian;Zesheng Tang

  • Affiliations:

  • Department of Computer Science and Technology, Tsinghua University, Beijing, China 100084;Department of Computer Science and Technology, Tsinghua University, Beijing, China 100084;Faculty of Information Technology, Macao University of Science and Technology, Macao, China;Department of Computer Science and Technology, Tsinghua University, Beijing, China 100084 and Faculty of Information Technology, Macao University of Science and Technology, Macao, China

  • Venue:
  • Medical Imaging and Informatics
  • Year:
  • 2008

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Abstract

Background removal is a critical step in Visible Human Data (VHD) processing, which is the basic of all other researches. In this paper, a new segmentation algorithm based on the hybrid method for VHD background removal has been proposed, which combines a feature based segmentation method with a contour based one. The algorithm first determines the background part and the interested parts of an image at a coarse level by using its colour features, and then obtains a fine segmentation by using a Gradient Vector Flow (GVF) Snake model on the previous initial contour. Our test results on Chinese VHD show that the new algorithm is more robust and accurate than the previous methods.