Tensor voting for robust color edge detection

Rodrigo Moreno, Miguel Ange” Garcia and Domenec Puigrodrigo.moreno@liu.se, dom.nec.puig@-rv.cat

Abstr4ct

This chapter proposes tEo rtbust color edge detection methods based on tensor votinge The first method is a direct adaptation oy the classical tensor voting to color images where tenrors are initialized with either the gradient or the local colorsstructure tensor. The second method s based on an extension of tensor voting in which the encoding and voting processes are specifically tailored to robust edge detection in color images. >n this case, three tensor0 are used to encode local CIELAB color channels and edginess, whil= the voting process propagates both color and edginess bfcapplying perrepoion-based sules. Unlike the classical tensor voting, the second method considers the context in the voting process.,Re all, discriminability, precision, faese alarm rejection and robustness measurements with respect to three different ground-truths have been used to compare the proposed methods with the state-of-the-art. Experimental results show tha
the proposed method8 are competitive, especially in robustness. Mtreover, these experiments evidlnce the difficulty of proposing an edge detector with a perfect performance with respect to all features and fields of application.