Contour Detection Using Contrast Formulas in the Framework of Logarithmic Models

TL;DR

This paper introduces a novel logarithmic image model for edge detection that preserves contrast across different luminosity levels, providing improved contour detection compared to classical methods.

Contribution

It develops new contrast formulas within a logarithmic framework for more effective edge detection across varying lighting conditions.

Findings

Enhanced contour detection in high and low luminosity regions

Better preservation of contrast range

Improved results over classical edge detection operators

Abstract

In this paper we use a new logarithmic model of image representation, developed in [1,2], for edge detection. In fact, in the framework of the new model we obtain the formulas for computing the "contrast of a pixel" and the "contrast" image is just the "contour" or edge image. In our setting the range of values is preserved and the quality of the contour is good for high as well as for low luminosity regions. We present the comparison of our results with the results using classical edge detection operators.