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.
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van Almsick, M., Duits, R., Franken, E., ter Haar Romeny, B. (2005). From Stochastic Completion Fields to Tensor Voting. In: Fogh Olsen, O., Florack, L., Kuijper, A. (eds) Deep Structure, Singularities, and Computer Vision. DSSCV 2005. Lecture Notes in Computer Science, vol 3753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11577812_11
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DOI: https://doi.org/10.1007/11577812_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29836-6
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