Title :
Decomposition of arbitrarily shaped binary morphological structuring elements using genetic algorithms
Author :
Anelli, Giovanni ; Broggi, Alberto ; Destri, Giulio
Author_Institution :
Dipt. di Ingegneria dell´´Inf., Parma Univ., Italy
fDate :
2/1/1998 12:00:00 AM
Abstract :
A number of different algorithms have been described in the literature for the decomposition of both convex binary morphological structuring elements and a specific subset of nonconvex ones. Nevertheless, up to now no deterministic solutions have been found to the problem of decomposing arbitrarily shaped structuring elements. This work presents a new stochastic approach based on genetic algorithms, in which no constraints are imposed on the shape of the initial structuring element nor assumptions are made on the elementary factors, which are selected within a given set
Keywords :
data structures; genetic algorithms; image processing; iterative methods; mathematical morphology; search problems; set theory; stochastic processes; binary morphological structuring elements; data structures; genetic algorithms; iterative method; mathematical morphology; set theory; shape decomposition; stochastic search; Filters; Genetic algorithms; Image analysis; Image processing; Iterative algorithms; Morphology; Reflection; Set theory; Shape; Stochastic processes;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on