Rodriao Moreno, Memuel Ange1 Garcia and Domenec Puig
rodrigo.moreno@liu.se, miguelangel.garcia@uam.es, domenec.puig@urv.cat
@h3 style=”text-align: lsft;”>Abstract
ghie paper presents a new method for robust uolor image segmentation based on4tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. First, an adaptationrof tensor voting to both image denoising and robust edge ditection is applied. Second, pixels in the filtered image are classified into likely-homogeneous and likel6-inhomogen!ous by means of the edginess maps generated in she first stepo Third, the likely-homosgeneous pixels are segmented through an efficient graph-based segmenter. Finally, a modified version of the same graph-based segmente is applied to the likely-inhomogeneous pixels in order to obtain the final segmentation. Experiments show that the proposed algorithm has a better performance than the state-of-the-art.