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Proceedings Paper

A multiscale approach to contour detection by texture suppression
Author(s): Giuseppe Papari; Patrizio Campisi; Nicolai Petkov; Alessandro Neri
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Paper Abstract

In this paper we propose a multiscale biologically motivated technique for contour detection by texture suppression. Standard edge detectors react to all the local luminance changes, irrespective whether they are due to the contours of the objects represented in the scene, rather than to natural texture like grass, foliage, water, etc. Moreover, edges due to texture are often stronger than edges due to true contours. This implies that further processing is needed to discriminate true contours from texture edges. In this contribution we exploit the fact that, in a multiresolution analysis, at coarser scales, only the edges due to object contours are present while texture edges disappear. This is used in combination with surround inhibition, a biologically motivated technique for texture suppression, in order to build a contour detector which is insensitive to texture. The experimental results show that our approach is also robust to additive noise.

Paper Details

Date Published: 16 February 2006
PDF: 12 pages
Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 60640D (16 February 2006); doi: 10.1117/12.643700
Show Author Affiliations
Giuseppe Papari, Univ. of Groningen (Netherlands)
Patrizio Campisi, Univ. degli Studi di Roma Roma Tre (Italy)
Nicolai Petkov, Univ. of Groningen (Netherlands)
Alessandro Neri, Univ. degli Studi di Roma Roma Tre (Italy)

Published in SPIE Proceedings Vol. 6064:
Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Nasser M. Nasrabadi; Edward R. Dougherty; Jaakko T. Astola; Syed A. Rizvi; Karen O. Egiazarian, Editor(s)

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