Abstract
Genetic Programming is a method of program discovery/optimisation consisting of a special kind of genetic algorithm capable of operating on nonlinear chromosomes (parse trees) representing programs and an interpreter which can run the programs being optimised. In this paper we describe a set of terminals and functions for the parse trees handled by genetic programming which enable it to develop effective image filters. These filters can either be used to highly enhance and detect features of interest or to build pixel-classification-based segmentation algorithms. Some experiments with medical images which show the efficacy of the approach are reported.
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© 1996 Springer-Verlag Berlin Heidelberg
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Poli, R. (1996). Genetic Programming for feature detection and image segmentation. In: Fogarty, T.C. (eds) Evolutionary Computing. AISB EC 1996. Lecture Notes in Computer Science, vol 1143. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0032777
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DOI: https://doi.org/10.1007/BFb0032777
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