Classification of Devnagari Numerals using Multiple Classifier

This paper presents a multiple classifier scheme for off-line hand written Devnagri numbers classification. The main purpose of this research is to find out best recognition result using multiple classifiers. This proposed technique uses simple profile and contour base triangular area representation technique for finding feature extraction and multiple classifier schemes on KNN, LDA, and KNN new neural network for classification. The performance of this technique has been tested with 36000 handwritten numerals randomly selected from CPAR datasets out of which 22000 datasets has been used for training sets and 14000 datasets has been used for test sets and we found the different result by different classifier.