Perceptual grouping using global saliency-enhancing operators

Abstract

Introduces saliency-enhancing operators capable of highlighting features which are considered perceptually relevant. One is able to extract salient curves and junctions and generate a description ranking these features by their likelihood of coming from the original scene. The authors suggest the global extension field as means of describing the behavior of a curve segment, in terms of its continuation. It is shown that a directional convolution of an edge image with the above field can produce useful descriptions. Other fields are also used in the same manner to produce similar results for domain-specific applications. The scheme is particularly useful and robust as a gap filler and in the presence of noise.<>