  This paper presents a Devnagari Numerical recognition method based on
statistical discriminant functions. 17 geometric features based on pixel
connectivity, lines, line directions, holes, image area, perimeter,
eccentricity, solidity, orientation etc. are used for representing the
numerals. Five discriminant functions viz. Linear, Quadratic, Diaglinear,
Diagquadratic and Mahalanobis distance are used for classification. 1500
handwritten numerals are used for training. Another 1500 handwritten numerals
are used for testing. Experimental results show that Linear, Quadratic and
Mahalanobis discriminant functions provide better results. Results of these
three Discriminants are fed to a majority voting type Combination classifier.
It is found that Combination classifier offers better results over individual
classifiers.
