Abstract
We apply to edge detection a recently introduced method for computing geometric structures in a digital image, without any a priori information. According to a basic principle of perception due to Helmholtz, an observed geometric structure is perceptually “meaningful” if its number of occurences would be very small in a random situation: in this context, geometric structures are characterized as large deviations from randomness. This leads us to define and compute edges and boundaries (closed edges) in an image by a parameter-free method. Maximal detectable boundaries and edges are defined, computed, and the results compared with the ones obtained by classical algorithms.
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Desolneux, A., Moisan, L. & Morel, JM. Edge Detection by Helmholtz Principle. Journal of Mathematical Imaging and Vision 14, 271–284 (2001). https://doi.org/10.1023/A:1011290230196
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DOI: https://doi.org/10.1023/A:1011290230196