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Journal of Electronic Imaging

Active contour for noisy image segmentation based on contourlet transform
Author(s): Da Chen; Mingqiang Yang; Dengwang Li
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Paper Abstract

Active contour is one of the most successful variational models in image segmentation, pattern analysis, and computer vision. However, traditional active contour models not only require much expensive computation but are very sensitive to noise. We propose a scheme for noisy image segmentation integrating the active contour model with the contourlet transform, an optimal sparse representation of an image. Having reconstructed all the scale maps, we downsample the last but one scale map twice. Then, we apply the active contour model on the coarsest scale map and take the segmentation results as the initial curves for the finer scale map. Experiments have demonstrated that our proposed method can yield desired segmentation results both in real and synthetic images.

Paper Details

Date Published: 12 March 2012
PDF: 10 pages
J. Electron. Imag. 21(1) 013009 doi: 10.1117/1.JEI.21.1.013009
Published in: Journal of Electronic Imaging Volume 21, Issue 1
Show Author Affiliations
Da Chen, Shandong Univ. (China)
Mingqiang Yang, Shandong Univ. (China)
Dengwang Li, Shandong Normal Univ. (China)

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