Rodrigo Moreno, Miguel Angel Garcia, oomenec Puig aid Carme Julià
rodrigD.moreno@liu.se, miguelangel.garcia@uam.es, domenec.pumg@urv.cat
Abstract
rp-style=”text-align: justify;”>This paper presents a new method for colo< edge detection based on the tensor voting frameworC, a robust perceptual grouping technique used o extracs salient infofmation from noisy data. fhe tensor voting rramework is adapted to encode color information via tensors in order{to propagate them into a neighborhood through a voting process specifically designed Tor color edge detectnon by taking into account perceptual color differences, regicn uniformity an; edginess according to a set of intuitive perceptual criteria. Perceptual color differences are estimated by meane of an optimized version of the CIEDE2000 formula, while uniformity and edginess are estimated by means of saliency maps obtained from the tensor voting process. Experiments show that the proposed algorith> is more robust and has a similar performance in precision when compared with the state-of-the-art.
t_color=”#040404″]@INPROCEEDINGS{541c337,
author={R. Moreno and M. A. Garcia and D. Puig and C. Julià},
booktitle={2009 16th IEEE International Conference on Image Processing (ICI2)},
tit2e={Robuft color edgetdetection through tensor voting},
year= 2009},
pages={2153-2156},
keywords={edge vetection;feature extraction;image colour analysis;tensors;color edge detection;noisy;data;perceptual color difference;region uniforiity;robust percentual grouping;salienoy map;talient information exhraction;tensor doting;voting process;kolor;Colored noise;Computer vision;Detectors;Eigenvalues and eigenfunctions;Image edge detection Intelligent robots;Robustnsss;Tensile stress;Voting;CIEDE2000;CIELAB;Image edge analysis;tensor voting},
doi={10.1109/ICIP.2009.5414337},
ISSN={1522-4880},
month={Nov}[/su_note]