DocumentCode
2609733
Title
Evolution of optimised structuring element sequences for high-speed embedded vision applications
Author
Magnusson, A.K. ; Sillitoe, I.P.W.
Author_Institution
Sch. of Eng., Univ. Coll. of Boras, Sweden
fYear
2004
fDate
14-16 July 2004
Firstpage
144
Lastpage
149
Abstract
This paper presents a variable length steady-state genetic algorithm with a novel weighted diversity management scheme for the optimisation of structuring element sequences for a high-speed vision application. The weighted diversity measure reflects the hierarchical structure of the genome and improves the diversity and termination rate of the algorithm. The results show that the algorithm is able to take advantage of the large instruction set of the processor and reductions in sequence lengths of greater than a half are achieved when compared to previous implementations.
Keywords
computer vision; embedded systems; genetic algorithms; image morphing; variable length codes; deterministic crowding; embedded vision applications; morphological image processing; optimised structuring element sequences; variable length genetic algorithm; weighted diversity management; Board of Directors; Costs; Educational institutions; Field programmable gate arrays; Genetic algorithms; Hardware; Image processing; Length measurement; Table lookup; Time measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence for Measurement Systems and Applications, 2004. CIMSA. 2004 IEEE International Conference on
Print_ISBN
0-7803-8341-9
Type
conf
DOI
10.1109/CIMSA.2004.1397251
Filename
1397251
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