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Level Set Segmentation with Robust Image Gradient Energy and Statistical Shape Prior

2011

Conference Paper

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We propose a new level set segmentation method with statistical shape prior using a variational approach. The image energy is derived from a robust image gradient feature. This gives the active contour a global representation of the geometric configuration, making it more robust to image noise, weak edges and initial configurations. Statistical shape information is incorporated using nonparametric shape density distribution, which allows the model to handle relatively large shape variations. Comparative examples using both synthetic and real images show the robustness and efficiency of the proposed method.

Author(s): Si Yong Yeo and Xianghua Xie and Igor Sazonov and Perumal Nithiarasu
Book Title: IEEE International Conference on Image Processing
Pages: 3397 - 3400
Year: 2011

Department(s): Perceiving Systems
Bibtex Type: Conference Paper (inproceedings)
Paper Type: Conference

URL: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6116439&tag=1

BibTex

@inproceedings{Yeo:ICIP:2011,
  title = {Level Set Segmentation with Robust Image Gradient Energy and Statistical Shape Prior},
  author = {Yeo, Si Yong and Xie, Xianghua and Sazonov, Igor and Nithiarasu, Perumal},
  booktitle = {IEEE International Conference on Image Processing},
  pages = {3397 - 3400},
  year = {2011},
  url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6116439&tag=1}
}