Fuzzy Directional Features for unconstrained on-line Devanagari handwriting recognition

Abstract

This paper describes a novel feature set for recognition of unconstrained on-line handwritten Devanagari script. Experiments are conducted for the automatic recognition of handwritten character primitives (sub-character units) collected without any constraints from different writers. Initially we describe the Fuzzy Directional Feature (FDF) extraction method and then show how these features can be effectively utilized for writer independent Devanagari character recognition. The recognition algorithm uses second order statistics to construct different stroke models. Experimental results show that FDF set out performs commonly used Directional Features (DF) for writer independent data set at stroke level recognition.