A genetic algorithm environment for star pattern recognition

Article type: Research Article

Authors: McClintock, Shaunna | Lunney, Tom | Hashim, Abdulla

Affiliations: Faculty of Informatics, University of Ulster, Londonderry, Northern Ireland, BT48-7JL, UK. E-mail: [email protected]

Abstract: This paper reviews genetic algorithms and considers their application in the domain of attributed point pattern matching, specifically star pattern recognition. Conventional algorithms employed in this area are first reviewed and the suitability of the genetic algorithm approach considered. A test environment is built and used to provide feedback on the viability of this approach. Algorithm testing is carried out using this environment, and results compared with the performance of the traditional star pattern search algorithms. The genetic algorithm approach discussed in this paper is shown to be a viable alternative to the conventional search algorithms (Benelli and Mecocci, ESA J. 17 (1993), 185–198; Murtagh, Astronom. Soc. Pacific 104 (1992), 301–307; Junkins and White, J. Astronom. Sci. XXV(3) (1977), 251–270), achieving on average fewer multiple matches and producing 'higher quality' solutions.

Journal: Journal of Intelligent and Fuzzy Systems, vol. 6, no. 1, pp. 3-16, 1998