On the Role of Contrast and Regularity in Perceptual Boundary Saliency

TL;DR

This paper introduces a new method for detecting perceptually significant image boundaries by allowing partial saliency detection of level lines, improving robustness and stability in shape analysis.

Contribution

It extends existing contrast-based boundary detection by enabling partial saliency detection and proposes a method to combine multiple gestalt cues for enhanced detection.

Findings

Effective detection of salient boundaries in natural images

Improved robustness and stability over classical methods

Successful combination of gestalt cues enhances detection accuracy

Abstract

Mathematical Morphology proposes to extract shapes from images as connected components of level sets. These methods prove very suitable for shape recognition and analysis. We present a method to select the perceptually significant (i.e., contrasted) level lines (boundaries of level sets), using the Helmholtz principle as first proposed by Desolneux et al. Contrarily to the classical formulation by Desolneux et al. where level lines must be entirely salient, the proposed method allows to detect partially salient level lines, thus resulting in more robust and more stable detections. We then tackle the problem of combining two gestalts as a measure of saliency and propose a method that reinforces detections. Results in natural images show the good performance of the proposed methods.