A multiscale approach to contour detection by texture suppression

Giuseppe Papari; Patrizio Campisi; Nicolai Petkov; Alessandro Neri

doi:10.1117/12.643700

16 February 2006 A multiscale approach to contour detection by texture suppression

Giuseppe Papari, Patrizio Campisi, Nicolai Petkov, Alessandro Neri

Proceedings Volume 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning; 60640D (2006) https://doi.org/10.1117/12.643700
Event: Electronic Imaging 2006, 2006, San Jose, California, United States

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.

Citation Download Citation

Giuseppe Papari, Patrizio Campisi, Nicolai Petkov, and Alessandro Neri "A multiscale approach to contour detection by texture suppression", Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 60640D (16 February 2006); https://doi.org/10.1117/12.643700

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