tailieunhanh - Báo cáo hóa học: " Research Article A Biologically Motivated Multiresolution Approach to Contour Detection"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Biologically Motivated Multiresolution Approach to Contour Detection | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 71828 28 pages doi 2007 71828 Research Article A Biologically Motivated Multiresolution Approach to Contour Detection Giuseppe Papari 1 Patrizio Campisi 2 Nicolai Petkov 1 and Alessandro Neri2 1 Institute of Mathematics and Computing Science University of Groningen P. O. Box 800 9700 AV Groningen The Netherlands 2 Dipartimento di Elettronica Applicata Universita degli Studi di Roma Roma Tre Via della Vasca Navale 84 00146 Roma Italy Received 3 January 2006 Revised 3 November 2006 Accepted 3 November 2006 Recommended by Maria Concetta Morrone Standard edge detectors react to all local luminance changes irrespective of whether they are due to the contours of the objects represented in a scene or due to natural textures like grass foliage water and so forth. Moreover edges due to texture are often stronger than edges due to object contours. This implies that further processing is needed to discriminate object contours from texture edges. In this paper we propose a biologically motivated multiresolution contour detection method using Bayesian denoising and a surround inhibition technique. Specifically the proposed approach deploys computation of the gradient at different resolutions followed by Bayesian denoising of the edge image. Then a biologically motivated surround inhibition step is applied in order to suppress edges that are due to texture. We propose an improvement of the surround suppression used in previous works. Finally a contour-oriented binarization algorithm is used relying on the observation that object contours lead to long connected components rather than to short rods obtained from textures. Experimental results show that our contour detection method outperforms standard edge detectors as well as other methods that deploy inhibition. Copyright 2007 Giuseppe Papari et al. This is an open access article distributed under the Creative Commons .