In this paper we describe a heuristic approach to the problem of identifying a pattern embedded within a figure from a predefined set of patterns via the utilization of a genetic algorithm (GA). By applying this GA we are able to recognize a set of simple figures independently of scale, translation and rotation. We discuss the fact that this GA is, purportedly, the best among a set of alternatives; a fact which was previously proven appealing to statistical techniques. We describe the general process, the special type of genetic algorithm utilized, report some results obtained from a test set and we discuss the aforementioned results and we comment on these. We also point out some possible extensions and future directions. © Springer-Verlag 2004.
CITATION STYLE
Angel, K. M. (2004). Pattern recognition via vasconcelos’ genetic algorithm. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3287, 328–335. https://doi.org/10.1007/978-3-540-30463-0_40
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