Modeling and Detection of Blurred Illumination Edges

Abstract

Luminance edges are classified into reflectance edges and illumination edges. Most of the edge detection papers published focus on reflectance edges detections, whereas only few of them deal with illumination edges. In this paper, a new approach to detect illumination edges in grayscale images is proposed. Differing from the conventional illumination edge detection techniques, which were mostly based on the grayscale intensity changes in the image being processed, instead, an error-function-based formulation is introduced to model blurred illumination edges, using a factor called the illumination ratio defined in this paper. Then, the profile of the illumination ratio is fitted with the proposed error-function model to determine the locations of all illumination edges. Although the frame-differencing method using complementary patterns is generally acknowledged to be the most accurate illumination edge detector, the proposed technique could perform better than it in both speed and accuracy. This technique benefits the fields of visual detection, machine vision, and especially the coded structured-light-based 3D scanning systems.