On-line Handwritten Devanagari Character Recognition using Fuzzy Directional Features

This paper describes a new feature set for use in the recognition of on-line handwritten Devanagari script based on Fuzzy Directional Features. Experiments are conducted for the automatic recognition of isolated handwritten character primitives (sub-character units). Initially we describe the proposed feature set, called the Fuzzy Directional Features (FDF) and then show how these features can be effectively utilized for writer independent character recognition. Experimental results show that FDF set perform well for writer independent data set at stroke level recognition. The main contribution of this paper is the introduction of a novel feature set and establish experimentally its ability in recognition of handwritten Devanagari script.

[1]  Sriganesh Madhvanath,et al.  Machine recognition of online handwritten Devanagari characters , 2005, Eighth International Conference on Document Analysis and Recognition (ICDAR'05).

[2]  Ujjwal Bhattacharya,et al.  Direction Code Based Features for Recognition of Online Handwritten Characters of Bangla , 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

[3]  Guy Lorette,et al.  A genetic algorithm for on-line cursive handwriting recognition , 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

[4]  Anil K. Jain,et al.  Online handwritten script recognition , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  S. Sundaram,et al.  A Novel Hierarchical Classification Scheme for Online Tamil Character Recognition , 2007, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007).

[6]  P. Rege,et al.  Fuzzy stroke analysis of Devnagari handwritten characters , 2008 .

[7]  Bidyut Baran Chaudhuri,et al.  Online handwritten Bangla character recognition using HMM , 2008, 2008 19th International Conference on Pattern Recognition.

[8]  Anil K. Jain,et al.  Template-based online character recognition , 2001, Pattern Recognit..

[9]  Patrick Gallinari,et al.  Maximum mutual information training for an online neural predictive handwritten word recognition system , 2001, International Journal on Document Analysis and Recognition.

[10]  Gerhard Rigoll,et al.  Neural net vector quantizers for discrete HMM-based on-line handwritten whiteboard-note recognition , 2008, 2008 19th International Conference on Pattern Recognition.

[11]  Sriganesh Madhvanath,et al.  Hidden Markov Models for Online Handwritten Tamil Word Recognition , 2007 .

[12]  L. Prasanth,et al.  HMM-Based Online Handwriting Recognition System for Telugu Symbols , 2007 .