FEATURE SELECTION USING GENETIC ALGORITHMS FOR HANDWRITTEN CHARACTER RECOGNITION

Microsoft, Motorola, Siemens, Hitachi, IAPR, NICI, IUF A feature selection method using genetic algorithms which are suitable means for selecting appropriate set of features from ones with huge dimension is proposed. SGA (Simple Genetic Algorithm) and its modified methods are applied to improve the recognition speed as well as the recognition accuracy. Experimental results show that the proposed methods improve the recognition performance with significant reduction in feature dimension. Several trials also have been made to investigate how the outcome of feature selection is affected as the feature dimension is changed.