NDLI: Vector (self) snakes: a geometric framework for color, texture, and multiscale image segmentation

Content Provider	IEEE Xplore Digital Library
Author	Sapiro, G.
Copyright Year	1996
Description	Author affiliation: Hewlett-Packard Co., Palo Alto, CA, USA (Sapiro, G.)
Abstract	A partial differential equations (PDEs) based geometric framework for segmentation of vector-valued images is described. The first component of this approach is based on two dimensional geometric active contours deforming from their initial position towards objects in the image. The boundaries of these objects are then obtained as geodesics or minimal weighted distance curves in a Riemannian space. The metric in this space is given by a definition of edges in vector-valued images, incorporating information from all the image components. The curve flow corresponding to these active contours holds formal existence, uniqueness, stability, and correctness results. Then, embedding the deforming curve as the level-set of the image, that is, deforming each one of the image components level-sets according to these active contours, a system of coupled PDEs is obtained. This system deforms the image towards uniform regions, obtaining a simplified (or segmented) image. The flow is related to a number of PDEs based image processing algorithms as anisotropic diffusion and shock filters. The technique is applicable to color and texture images, as well as to vector data obtained from general image decompositions.
Starting Page	817
Ending Page	820
File Size	518052
Page Count	4
File Format	PDF
ISBN	0780332598
DOI	10.1109/ICIP.1996.559624
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-09-19
Publisher Place	Switzerland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Active contours Image segmentation Partial differential equations Extraterrestrial measurements Stability Image processing Anisotropic magnetoresistance Electric shock Filters Image decomposition
Content Type	Text
Resource Type	Article

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