Variational shape prior segmentation with an initial curve based on image registration technique

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In general images, it is practically hard to distinguish only the desired object using the conventional image segmentation methods. In many cases, we can segment the desired object by using the shape information of the object in addition to the standard image segmentation. Chan and Zhu's model is not robust to the intensity changes of objects. In this paper, we propose a novel model for the shape prior segmentation that produces robust results using the hierarchical image segmentation and an attraction term. Moreover, we adopt an image registration technique and a multi-region image segmentation to get an initial for a given shape prior. Finally, we consider the free-form deformation in obtaining the shape function from the reference shape prior for real-world images. Numerical experiments demonstrate the results independent of intensities of objects and the location of the reference shape prior. All numerical calculations are automatic and progress without any user input.
Publisher
ELSEVIER
Issue Date
2020-02
Language
English
Article Type
Article
Citation

IMAGE AND VISION COMPUTING, v.94, pp.103865

ISSN
0262-8856
DOI
10.1016/j.imavis.2019.103865
URI
http://hdl.handle.net/10203/273841
Appears in Collection
MA-Journal Papers(저널논문)
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