Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/188

Deformable contours : modeling and extraction

Authors Lai, Kok F.
Chin, Roland T.
Issue Date 1995
Source IEEE transactions on pattern analysis and machine intelligence, v. 17, (11), Nov. 1995, p. 1084-1090
Summary This paper considers the problem of modeling and extracting arbitrary deformable contours from noisy images. We propose a global contour model based on a stable and regenerative shape matrix, which is invariant and unique under rigid motions. Combined with Markov random field to model local deformations, this yields prior distribution that exerts influence over a global model while allowing for deformations. We then cast the problem of extraction into posterior estimation and show its equivalence to energy minimization of a generalized active contour model. We discuss pertinent issues in shape training, energy minimization, line search strategies minimax regularization and initialization by generalized Hough transform. Finally, we present experimental results and compare its performance to rigid template matching.
Subjects
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Language English
Format Article
Access Find@HKUST
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