An End to End System for Online Handwritten Bangla Character Recognition

Abstract

This report summarizes the attempt to find the way towards building an Optical Character Recognition System for handwritten Bangla characters. The complex

and unique structure of scripts like Bangla and ever challenging nature of hand- written texts combined makes it really difficult to complete a perfect system to

approach to convert the scanned handwritten Bangla scripts to machine editable

digital counterpart format of it- as segmentation of the whole image into char- acters and then classification of the segmented characters is difficult enough to

make the task challenging. In our work, we propose to approach the segmentation process (directly segment to words) with Distance Transform and morphological operations for error correction later. Then two zone approach (either side of matra- upper and lower zone) and apply connected component analysis on both zones. We handled or adjusted the failed and not directly successful cases by

experimenting with the characteristics of handwritten characters. Then for clas- sification process, we proposed to classify the segmented characters using neural

networks trained on the relatively newly available datasets. Multiple column, Mixed characters (Bangla- other languages) and Scene Text Recognition is out of the scope of our study so far. And we could not include the post-processing part for our work for lack of work or mention in existing literature, which might be a great addition in the way of building a complete OCR system.