Segmentation of Online Bangla Handwritten Word


To take care of variability involved in the writing style of different individuals in this paper we propose a robust scheme to segment unconstrained handwritten Bangla words into characters. Online handwriting recognition refers to the problem of interpretation of handwriting input captured as a stream of pen positions using a digitizer or other pen position sensor. For online recognition of word the segmentation of word into basic strokes is needed. For word segmentation, at first, we divide the word image into two different zones. The upper zone is taken as the 1/3rd of the height of the total image. Now, based on the concept of downside movement of stroke in this upper zone we segment each word into a combination of basic strokes. We segment at a pixel where the slope of six consecutive pixels satisfies certain angular value. We tested our system on 5500 Bangla word data and obtained 81.13% accuracy on word data from the proposed system.

Cite this paper

@article{Ghosh2009SegmentationOO, title={Segmentation of Online Bangla Handwritten Word}, author={Rajib Ghosh and Debnath Bhattacharyya and Samir Kumar Bandyopadhyay}, journal={2009 IEEE International Advance Computing Conference}, year={2009}, pages={658-663} }