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[Author] Guoqi LIU(1hit)

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  • Dynamically Constrained Vector Field Convolution for Active Contour Model

    Guoqi LIU  Zhiheng ZHOU  Shengli XIE  Dongcheng WU  

     
    LETTER-Image Recognition, Computer Vision

      Vol:
    E96-D No:11
      Page(s):
    2500-2503

    Vector field convolution (VFC) provides a successful external force for an active contour model. However, it fails to extract the complex geometries, especially the deep concavity when the initial contour is set outside the object or the concave region. In this letter, dynamically constrained vector field convolution (DCVFC) external force is proposed to solve this problem. In DCVFC, the indicator function with respect to the evolving contour is introduced to restrain the correlation of external forces generated by different edges, and the forces dynamically generated by complex concave edges gradually make the contour move to the object. On the other hand, traditional vector field, a component of the proposed DCVFC, makes the evolving contour stop at the object boundary. The connections between VFC and DCVFC are also analyzed. DCVFC maintains desirable properties of VFC, such as robustness to initialization. Experimental results demonstrate that DCVFC snake provides a much better segmentation than VFC snake.