An Iterative Algorithm for Segmentation of Isolated Handwritten Words in Gurmukhi Script

Segmentation of handwritten text in Gurmukhi script is an uphill task primarily because of the structural features of the script and varied writing styles. The presence of a horizontal line connecting characters of a word (i.e. head line), half characters and overlapping of some vowel between middle and lower zone of a word make the task even more difficult. Handwritten text is also prone to the problem of overlapped, connected and merged characters with in a word. Structural features are helpful in segmentation of machine printed text but these are of little help for segmentation of handwritten words. The proposed technique segments the words in an iterative manner by focusing on presence of headline, aspect ratio of characters and vertical and horizontal projection profiles. The proposed approach of segmentation can be used for handwritten text of Indian language scripts like Devnagri, Bangla etc. having structural feature similar to Gurmukhi script