Assamese online handwritten digit recognition system using hidden Markov models

Authors:
G. Siva Reddy;Bandita Sarma;R. Krishna Naik;S. R. M. Prasanna;Chitralekha Mahanta
Affiliations:
Indian Institute of Technology, Guwahati, India;Indian Institute of Technology, Guwahati, India;Indian Institute of Technology, Guwahati, India;Indian Institute of Technology, Guwahati, India;Indian Institute of Technology, Guwahati, India
Venue:
Proceeding of the workshop on Document Analysis and Recognition
Year:
2012

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Abstract

This work describes the development of Assamese online handwritten digit recognition system. Assamese numerals are the same as the Bangla numerals. A large database of handwritten numerals is collected and partitioned into two parts of equal size. The first part is used for developing the Hidden Markov Models (HMM) based digit models. The (x, y) coordinates and their first and second time derivatives are used as features. The second part of the database is tested against the models to evaluate the performance. The digit recognition system provides an average recognition performance of 96.02%. A large amount of confusion is observed among the numerals 5 & 6. The new distance feature is used as an additional feature and the models are retrained. The performance for numeral 5 & 6 increases from 91.60% & 95.40% to 95.30% & 94.90%. As a result, the confusion reduces significantly and the average recognition performance increases to 97.14%.