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.