Edge Detection in Complex Scenes Based on Gestalt Principles of Proximity and Similarity
University of Wisconsin-Madison Department of Computer Sciences
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An edge detection function is defined on a very broad class of pictures. It departs from previous approaches to edge detection, which are based on differences in intensity or other properties between adjacent areas of a picture, in using the spatial and similarity relations among individual entities, called elements, to determine the locations and probabilities of edges. With auxiliary definitions of similarity, it may be applied to digitized pictures, treating picture points as elements, or to scenes of diversified shapes distributed in any way - although only scenes of disks are discussed in this paper. This generality permits recursive use of the edge detector in the discrimination of visual textures. An algorithm for the efficient computation of the function is described. The program runs at the University of Wisconsin in a larger system, which includes T.V. input and additional programs that cluster edges into boundaries.