Segmentation of Offline Handwritten Gurmukhi Words Using Projection Features

Abstract

Segmentation of words into isolated characters is the essential component in handwritten character recognition systems. In this paper, the segmentation of Gurmukhi handwritten words into characters is presented. For this, horizontal and vertical projection features have been used to segment the characters from words. Simple words without upper and lower modifier of Gurmukhi handwritten text having three and four characters are considered in the present work. An overall accuracy of 91.4 % on a dataset of 550 handwritten Gurmukhi words has been achieved in this work.