1. Online Stroke and Akshara Recognition GUI in Assamese Language Using Hidden Markov Model
- Author
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Prasanna, SRM, Devi, Rituparna, Das, Deepjoy, Ghosh, Subhankar, and Naik, Krishna
- Subjects
FOS: Computer and information sciences ,ComputingMethodologies_PATTERNRECOGNITION ,Computer Vision and Pattern Recognition (cs.CV) ,Computer Science - Computer Vision and Pattern Recognition - Abstract
The work describes the development of Online Assamese Stroke & Akshara Recognizer based on a set of language rules. In handwriting literature strokes are composed of two coordinate trace in between pen down and pen up labels. The Assamese aksharas are combination of a number of strokes, the maximum number of strokes taken to make a combination being eight. Based on these combinations eight language rule models have been made which are used to test if a set of strokes form a valid akshara. A Hidden Markov Model is used to train 181 different stroke patterns which generates a model used during stroke level testing. Akshara level testing is performed by integrating a GUI (provided by CDAC-Pune) with the Binaries of HTK toolkit classifier, HMM train model and the language rules using a dynamic linked library (dll). We have got a stroke level performance of 94.14% and akshara level performance of 84.2%., 6 pages, 9 figures, International Journal of Scientific and Research Publications, Volume 4, Issue 1, January 2014
- Published
- 2014