Title :
Combining multiple classifiers based on statistical method for handwritten Chinese character recognition
Author :
Lin, Lei ; Wang, Xiao-long ; Liu, Bing-quan
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., China
Abstract :
In various application areas of pattern recognition, combining multiple classifiers is regarded as a method for achieving a substantial gain in performance of systems. The paper presents a method for handwritten Chinese character recognition to combine multiple classifiers based on statistics. Fusion strategies are discussed for providing a basis for combining classifiers. These combination strategies are experimentally tested on an online handwritten Chinese character recognition system. In our experiments, other combination approaches are also involved for comparison.
Keywords :
Bayes methods; decision theory; handwritten character recognition; probability; classifiers; fusion strategies; handwritten Chinese character recognition; online recognition system; pattern recognition; statistical method; Application software; Bayesian methods; Character recognition; Computer science; Electronic mail; Handwriting recognition; Pattern recognition; Performance gain; Statistical analysis; Statistics;
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
DOI :
10.1109/ICMLC.2002.1176750
