Segmentation of Broken Characters of Handwritten Gurmukhi Script

Character Segmentation of Handwritten Documents has been an active area of research and due to its diverse applicable environment; it continues to be a challenging research topic. The desire to edit scanned text document forces the researchers to think about the optical character recognition (OCR). OCR is the process of recognizing a segmented part of the scanned image as a character. OCR process consists of three major sub processes pre processing, segmentation and then recognition. Out of these three, the segmentation process is the most important phase of the overall OCR process. Different problems in the characters segmentation of handwritten text is due to the different writing style of different people because the size and shape is not fixed while we write any text. In this work, we formulate an algorithm to segment the scanned document image as a character. According to proposed algorithm, broken characters in Gurmukhi script, we used the segmentation of these characters that can become easily identify how many characters are in one word. To develop the algorithm to segment the characters from a word we are using combinations of two approaches which are Horizontal Profile Projection and Vertical Profile Projection. And get the accuracy is 93%.