A multiscale approach to contour detection by texture suppression

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.

Motion detection, noise reduction, texture suppression, and contour enhancement by spatiotemporal Gabor filters with surround inhibition

“…3.2 has a multiscale aspect. Elsewhere, the concept of surround inhibition has been used in a multiscale approach for enhancing contour detection in purely spatial images (Papari et al 2006).…”

Contour Detection by Multiresolution Surround Inhibition

“…A multiresolution approach to contour detection has been proposed in [5]. In the current work we extend our previous studies [6] in combining a multiresolution approach and surround inhibition. We propose a method that detects contours at different resolutions and combines them by a contour-oriented selection algorithm.…”

“…On the other hand, contours detected at coarse scales are smoothed, shifted [9], and the non-maxima suppression destroys the junctions [10]. Thus, information at more scales can be combined in order to obtain contours being as detailed as at the fine scales, but without the texture that does not appear at coarse scales [5,6,11]. In [6], this has been achieved through the pixel by pixel logic AND combination of binary contour maps obtained at different scales.…”

Mission-critical monitoring based on surround suppression variational Retinex enhancement for non-uniform illumination images

“…In Fig. 1b, the sensations of the central points in region A, B, and C are suppressed by their surroundings [31].The effect is strong in texture region C because its surrounding is full of textures, whereas the boundary regions A and B are less affected. Thus, the boundaries of A and B are highlighted.…”