COMPARISON OF CLASSIFIERS FOR GUJARATI NUMERAL RECOGNITION
BAHETI MJ, KALE KV, JADHAV ME · International Journal of Machine Intelligence · 2011
Handwritten script has been the most acknowledged method of collecting, storing and transmitting information all the way through the centuries. In this paper an attempt is made to compare the offline handwritten character recognition system for the isolated Gujarati numerals. For feature extraction affine invariant moments based model is used. We are using KNN classifier and PCA (to reduce dimensions of feature space) and used Euclidean similarity measure to classify the numerals. KNN classifier yielded 90 % as recognition rate whereas PCA scored recognition rate of 84%. The comparison of KNN and PCA is made and it can be seen that KNN classifier has shown better results as compared to PCA classifier.