An end-to-end system for bangla online handwriting recognition
Document Type
Conference Article
Publication Title
Proceedings of International Conference on Frontiers in Handwriting Recognition, ICFHR
Abstract
A few studies of online Bangla handwriting recognition such as isolated character recognition or limited vocabulary cursive word recognition are found in the literature. However, development of an end-to-end recognition system of unconstrained online Bangla handwritten texts has not been duly attempted so far. In the present report, we describe a similar system which takes a piece of continuous online handwritten Bangla texts as the input. It first segments the input texts into individual lines, each line into its constituent words and each word into sub-strokes. In the present study, 152 different symbols which include basic characters, character modifiers, frequently used conjunct characters, a few special characters and numerals have been considered. The entire set of sub-strokes obtained from the training sample set has been exhaustively studied by 3 experts and 76 different shapes of sub-strokes have been identified based on consensus among these experts. Also, it has been observed that a character may produce at most 3 sub-strokes. Since a piece of Bangla texts often contains either Bangla or English numerals, the present character set consists of both the numeral set and 3 numeral shapes are common to both the scripts. The proposed recognition system uses two classifiers, one for characters and the other for sub-strokes. Sub-strokes are fed to the character classifier in their temporal order. A single sub-stroke followed by two consecutive sub-strokes and finally three successive sub-strokes are passed to the character classifier and the first two top responses of the character classifier among the three cases are compared. If the difference is less than a threshold, the response of sub-stroke classifier is used to reach a final decision. The proposed system provided 94.3% character level accuracy on a test set consisting of 33,453 word samples written by 31 writers.
First Page
373
Last Page
378
DOI
10.1109/ICFHR.2016.0076
Publication Date
7-2-2016
Recommended Citation
Bhattacharya, Soumik; Maitra, Durjoy Sen; Bhattacharya, Ujjwal; and Parui, Swapan K., "An end-to-end system for bangla online handwriting recognition" (2016). Conference Articles. 668.
https://digitalcommons.isical.ac.in/conf-articles/668
