A System for Online Gurmukhi Script Recognition

Abstract

Handwriting recognition is the task of transforming a language represented in its spatial form of graphical marks into its symbolic representation. There are two type of handwriting recognition, offline and online. In offline handwriting recognition, the user writes on the paper which is digitized by the scanner. The output of the scanner is presented as an image to the system which recognizes the writing. In contrast, the online handwriting recognition requires that the user’s writing is captured through digitizer pen and tablet before recognition. Online handwriting recognition assumes importance as it is still much more convenient to write with pen as compared to typing on the keyboard. Secondly, these days so many PDAs and handheld devices are used where it is easier to work with stylus then using keyboard. This has motivated research in online handwriting recognition in different languages of the world including Indic scripts such as Tamil, Telgu, Kannada, Devanagari and Gurmukhi. In our work, a system for recognition of Gurmukhi Script is presented. In this work, the input of the user’s handwriting is taken as a sequence of packets captured through the movement of stylus or pen on the surface of the tablet. The packet consists of x,y position of the stylus, button(tip of stylus), pressure of the stylus and the time of each packet. The user’s writing is preprocessed and is segmented into meaniningful shapes. The segmented shapes are processed to extract features which are Distributed Directional Feature. The feature data is fed to the recognition engine which is a Nearest Neighbor Classifier. The average recognition accuracy is 76% approximately. The block diagram of the system for Online Gurmukhi Script recognition is shown in Fig 1 below. The main strengths of this system is that it takes complete word for segmentation and recognition.