Robust Object Segmentation with Constrained Curve Embedding Potential Field

  • Gary H. P. Ho
  • Pengcheng Shi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3150)


We have earlier introduced an implicit vector field representation for arbitrary number of curves in space, the curve embedding potential field (CEPF), and a general image segmentation strategy based on the detection of the CEPF distortion under the influence of vector-form image data [3]. In this paper, we present an improved CEPF framework which incorporates prior knowledge of the object boundary and has consistent object definition through a region growing process. The embedded implicit curves deform through the image- and model-induced changes of the CEPF, which evidently improves the segmentation accuracy under noisy and broken-edge situations. Further, the closure enforcement and the natural advection on the curves enhance the stability of CEPF evolution and the implementation is straightforward. Robust experimental results on cardiac and brain images are presented.


Object Boundary Active Contour Model Curve Point Segmentation Accuracy Curve Element 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Gary H. P. Ho
    • 1
  • Pengcheng Shi
    • 1
  1. 1.Biomedical Research Laboratory, Department of Electrical and Electronic EngineeringHong Kong University of Science and TechnologyKowloon, Hong Kong

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