Novel Approach to Segmentation of Handwritten Devnagari Word

Abstract

This paper makes an attempt to segment the handwritten Devnagari words. Segmentation of script is essential for handwritten script recognition. Segmentation affects recognition so accurate segmentation is important for implementing OCR. Little work had been reported towards segmentation of handwritten text. Segmentation of handwritten words is a bit complicated as the shape of the handwritten characters is uncertain due to variability in writing styles. The proposed system carries out segmentation in hierarchical order. The system deploys the morphological operations of image processing for segmentation. Neighbourhood tracing algorithm is used for finding the segmented objects in the specific zones that correspond to constituent symbols of the Devnagari script. Segmentation accuracy is found to be 57% for segmentation of top modifiers and 55% for lower modifiers and 52% for characters in core zone.