From stochastic completion fields to tensor voting

Authors:
Markus van Almsick;Remco Duits;Erik Franken;Bart ter Haar Romeny
Affiliations:
Technische Universiteit Eindhoven, Eindhoven, The Netherlands;Technische Universiteit Eindhoven, Eindhoven, The Netherlands;Technische Universiteit Eindhoven, Eindhoven, The Netherlands;Technische Universiteit Eindhoven, Eindhoven, The Netherlands
Venue:
DSSCV'05 Proceedings of the First international conference on Deep Structure, Singularities, and Computer Vision
Year:
2005

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Abstract

Several image processing algorithms imitate the lateral interaction of neurons in the visual striate cortex V1 to account for the correlations along contours and lines. Here we focus on two methodologies: tensor voting by Guy and Medioni, and stochastic completion fields by Mumford, Williams and Jacobs. The objective of this article is to compare these two methods and to place them into a common mathematical framework. As a consequence we obtain a sound stochastic foundation of tensor voting, a new tensor voting field, and an analytic approximation of the stochastic completion kernel.