Accession Number : ADA089173
Title : Edge Relaxation and Boundary Continuity.
Descriptive Note : Technical rept.,
Corporate Author : MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER AND INFORMATION SCIENCE
Personal Author(s) : Hanson,Allen R. ; Riseman,Edward M. ; Glazer,Frank C.
Report Date : MAY 1980
Pagination or Media Count : 113
Abstract : Many image analysis tasks require the construction of a boundary representation as a means of partitioning an image. This paper develops a parallel relaxation algorithm for updating initial heuristic estimates of the likelihood of edges so that continuous boundaries are formed. Bayesian probability theory is used to analyze the probability updating of a single edge based upon the joint probabilities of the edges in its local surrounding context. The relationships between edges, sometimes referred to as compatibility coefficients in relaxation algorithms, are embodied as conditional probabilities between the central edge and the context of edges. The set of conditional probabilities are theoretically derived from a model of desired line drawings that satisfy basic notions of boundary continuity. The local updating function attempts to drive the likelihood of each central edge into consistency with the surrounding context. Experiments involving the iterative parallel application of this non-linear Bayesian updating function to all edge probabilities demonstrates serious problems in the formulation. A variety of heuristic modifications, guided by theoretical considerations, are examined empirically. The final formulation is an algorithm that performs in an effective manner on several very complex images. (Author)
Descriptors : *IMAGE PROCESSING, *IMAGE DISSECTION, ALGORITHMS, TWO DIMENSIONAL, EDGES, BOUNDARIES, NONLINEAR SYSTEMS, HEURISTIC METHODS, RELAXATION, BAYES THEOREM.
Subject Categories : Human Factors Engineering & Man Machine System
Distribution Statement : APPROVED FOR PUBLIC RELEASE