The study of different similarity measure techniques in recognition of handwritten characters

Abstract

In this paper, we compare the affect of four different similarity measure techniques namely Euclidean distance, Modified squared euclidean distance, Correlation distance and Angle distance for an unconstrained handwritten character recognition. The strength of these similarity measures are estimated between feature vectors with respect to the recognition performance of the Gabor-PCA method. Gabor filter is used to extract spatially localized features of character image. The dimensions of such Gabor feature vector is prohibitively high & in order to compress Gabor features we used PCA method. The experiments were performed using the database containing 22,600 samples of Kannada and English. From the analysis the better recognition accuracy were achieved using angle distance measure.