JPR_V1_N4_RP2 Y.C. Kiran V.N. Manjunath Aradhya C. Naveena Journal on Pattern Recognition 2350-112X 1 4 11 20 Hand Written Characters, Ridgelets, Distance Measure, Principal Component Analysis The Ridgelet Transform [6] was introduced as a sparse expansion for functions of continuous spaces that are smooth away from discontinuities along lines. The powerful properties of the ridgelets are catching and representing monodimensional singularities in bi-dimensional space [8]. Using these effective properties, in this paper the authors propose an effect of Ridgelet Transform on various Similarity/Distance Measure Techniques namely Euclidean Distance, Modified Squared Euclidean Distance, Correlation Distance and Angle Distance for an unconstrained bi-lingual handwritten character recognition. Ridgelet Transform is used to extract a character image of low pass energy and is then fed to PCA for feature extraction. We conducted experiment on very large database of bi-lingual handwritten characters (Kannada and English). The database contains the samples of 22,600 and the effect of the proposed method is compared with the standard PCA & FLD methods. Among the above mentioned similarity/distance measure techniques the better recognition accuracy were achieved using angle distance measure. December 2014 - February 2015 Copyright © 2015 i-manager publications. All rights reserved. i-manager Publications http://www.imanagerpublications.com/Article.aspx?ArticleId=3306