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Proceedings Paper

Segmentation of thin networks using perceptual organization with active contour functions
Author(s): Laurent Alquier; Phillipe Montesinos
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Paper Abstract

This paper describes a new method of perceptual organization of thin networks using geometric properties. The key point of our approach is to consider perceptual organization as a problem of optimization: solutions to this problem are the best matchings between continuous curves and the low level primitives. First the quality of a grouping is defined with a class of functions related to the energy functions of active contours optimization. Such functions are computed recursively, and optimized from a local to a global level with an algorithm related to dynamic programming. This is followed by a selection procedure which rates and extracts principal groupings automatically and gives a new segmentation of image primitives, based on smoothed continuation. This segmentation is used to initialize a high level interpretation process involving projective reconstruction of 3D contours in sequences of images. The adaptability and robustness of this method have been tested on various situations, such as the extraction of ellipses from indoor scenes, roads from satellite pictures or blood vessels from medical images.

Paper Details

Date Published: 30 September 1996
PDF: 11 pages
Proc. SPIE 2898, Electronic Imaging and Multimedia Systems, (30 September 1996); doi: 10.1117/12.253381
Show Author Affiliations
Laurent Alquier, LGI2P (France)
Phillipe Montesinos, LGI2P (France)


Published in SPIE Proceedings Vol. 2898:
Electronic Imaging and Multimedia Systems
Chung-Sheng Li; Robert L. Stevenson; LiWei Zhou, Editor(s)

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