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The global shape prior knowledge has been exploited by many image segmentation approaches in order to improve segmentation results when there are such problems as occlusion, cluttering, low contrast edges, etc. We propose a global shape prior representation and incorporate it into a level set based segmentation framework. This global shape prior can effectively help remove the cluttered elongate structures...
A new image representation method is proposed for face recognition in this paper, called local Gabor phase difference pattern (LGPDP). Unlike the Histogram of Gabor Phase Patterns (HGPP) that exploits the relationships of Gabor phase between neighborhood pixels, the LGPDP captures the Gabor phase difference relationships to represent the image. In order to avoid the sensitivity of the Gabor phase...
We introduce a new shape normalization method based on implicit shape representations. The proposed method is robust with respect to deformations and invariant to similarity transformations (translation, isotropic scaling and rotation). The new method has been tested and compared to the classical shape normalization method and previous work in terms of aligning groups of shapes with deformations.
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