Completely Convex Formulation of the Chan-Vese Image Segmentation Model

The active contours without edges model of Chan and Vese (IEEE Transactions on Image Processing 10(2):266–277, 2001 ) is a popular method for computing the segmentation of an image into two phases, based on the piecewise constant Mumford-Shah model. The minimization problem is non-convex even when t...

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Bibliographic Details
Published in:	International journal of computer vision Vol. 98; no. 1; pp. 103 - 121
Main Authors:	Brown, Ethan S., Chan, Tony F., Bresson, Xavier
Format:	Journal Article
Language:	English
Published:	Boston Springer US 01.05.2012 Springer Springer Nature B.V
Subjects:	Algorithms Analysis Applied mathematics Applied sciences Approximation Artificial Intelligence Computer aided manufacturing Computer Imaging Computer Science Computer science; control theory; systems Data processing. List processing. Character string processing Exact sciences and technology Experiments Image processing Image Processing and Computer Vision Image processing equipment industry Image processing systems Mathematical analysis Mathematical models Memory organisation. Data processing Methods Optimization Optimization techniques Partial differential equations Pattern Recognition Pattern Recognition and Graphics Pattern recognition. Digital image processing. Computational geometry Relaxation Segmentation Software Studies Two phase Vision Vision systems Convex relaxation Image segmentation means Chan-Vese model Vector-valued functional lifting Level set method K-means Computer vision Initial condition Computer aided manufacturing Image processing CAML language Contour line Minimization K means algorithm Transaction processing Modeling Applied mathematics Optimal solution Classification Optimal approximation Edge detection Non convex analysis
ISSN:	0920-5691, 1573-1405
Online Access:	Get full text
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