Title :
A hybrid approach to character segmentation of Gurmukhi script characters
Author :
Davessar, Neena Madan ; Madan, Sunil ; Singh, Hardeep
Author_Institution :
Dept. of Comput. Sci. & Eng., Guru Nanak Dev Univ., Amritsar, India
Abstract :
A new approach to segmentation of machine printed Gurmukhi text has been suggested. This approach can easily be extended to other Indian language scripts such as Devnagri and Bangla. Most of the characters in these scripts have horizontal lines at the top called headlines. Besides, there are cases in which the characters are found touching in the scanned image, just below the headline. To resolve these issues, a two-pass mechanism is used. In pass-one it approximates the segmentation point, while in pass-two the cutting point is optimized. This approach has been very successful in segmenting a pair as well as triplets of touching characters.
Keywords :
image segmentation; natural languages; optical character recognition; Bangla; Devnagri; Gurmukhi script characters; Indian language scripts; character segmentation; cutting point optimization; horizontal headlines; machine printed Gurmukhi text; segmentation point approximation; two pass mechanism; Banking; Character recognition; Conferences; Error analysis; Image recognition; Image segmentation; Office automation; Optical character recognition software; Pattern recognition; Writing;
Conference_Titel :
Applied Imagery Pattern Recognition Workshop, 2003. Proceedings. 32nd
Print_ISBN :
0-7695-2029-4
DOI :
10.1109/AIPR.2003.1284267