Segmentation of thin networks using perceptual organization with active contour functions

Laurent Alquier; Phillipe Montesinos

doi:10.1117/12.253381

30 September 1996 Segmentation of thin networks using perceptual organization with active contour functions

Laurent Alquier, Phillipe Montesinos

Proceedings Volume 2898, Electronic Imaging and Multimedia Systems; (1996) https://doi.org/10.1117/12.253381
Event: Photonics China '96, 1996, Beijing, China

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.

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Laurent Alquier and Phillipe Montesinos "Segmentation of thin networks using perceptual organization with active contour functions", Proc. SPIE 2898, Electronic Imaging and Multimedia Systems, (30 September 1996); https://doi.org/10.1117/12.253381

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KEYWORDS

Image segmentation

Medical imaging

Signal to noise ratio

Image processing

Optimization (mathematics)

Image quality

Satellites

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