Title :
Fusion of handwritten numeral classifiers based on fuzzy and genetic algorithms
Author :
Pham, Tuan D. ; Yan, Hong
Author_Institution :
Fac. of Inf. Sci. & Eng., Univ. of Canberra, Belconnen, ACT, Australia
Abstract :
Fuzzy and genetic algorithms are used to develop an approach for fusioning multiple handwritten numeral classifiers. A computational scheme of the Choquet (fuzzy) integral serves as a data fusion tool, whereas genetic algorithms are implemented to optimize the derivation of fuzzy densities which play a very important role for the calculation of fuzzy measures and fuzzy integrals. Several experimental results are provided to illustrate the effectiveness of this methodology
Keywords :
fuzzy set theory; genetic algorithms; handwriting recognition; integral equations; pattern classification; sensor fusion; Choquet fuzzy integral; computational scheme; data fusion tool; fuzzy algorithms; fuzzy densities; fuzzy measures; genetic algorithms; multiple handwritten numeral classifier fusion; Australia; Boundary conditions; Computer vision; Density measurement; Event detection; Fuzzy sets; Genetic algorithms; Genetic engineering; Image analysis; Robots;
Conference_Titel :
Fuzzy Information Processing Society, 1997. NAFIPS '97., 1997 Annual Meeting of the North American
Conference_Location :
Syracuse, NY
Print_ISBN :
0-7803-4078-7
DOI :
10.1109/NAFIPS.1997.624047
