Curvelet-based geodesic snakes for image segmentation with multiple objects

نویسندگان

  • Hao Shan
  • Jianwei Ma
چکیده

0167-8655/$ see front matter 2009 Elsevier B.V. A doi:10.1016/j.patrec.2009.10.018 * Corresponding author. Address: School of Aero Beijing 100084, China. Tel.: +86 10 62781824. E-mail address: [email protected] (J. Ma). Curvelet transform is a multiscale and multidirectional geometric wavelet transform, which is an optimal sparse representation of edges and contours of objects. In this paper, a curvelet-based geodesic snake (CGS) is proposed for image segmentation of multiple objects. By producing the edge map of objects by curvelet thresholding instead of simple gradient methods, the proposed method shows great promises to recognize edges of multiple objects with weak edges and strong noises. In addition, we design several rules to quantitatively compare the segmentation accuracy. 2009 Elsevier B.V. All rights reserved.

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عنوان ژورنال:
  • Pattern Recognition Letters

دوره 31  شماره 

صفحات  -

تاریخ انتشار 2010