Award Date

12-1-2012

Degree Type

Thesis

Degree Name

Master of Science in Computer Science

Department

Computer Science

First Committee Member

Kazem Taghva

Second Committee Member

Ajoy K. Datta

Third Committee Member

Laxmi P. Gewali

Fourth Committee Member

Venkatesan Muthukumar

Number of Pages

41

Abstract

In this thesis, we report on our design and implementation of a post processing system for Optically Recognized text. The system is based on first order Hidden Markov Model (HMM). The Maximum Likelihood algorithm is used to train the system with over 150 thousand characters. The system is also tested on a file containing 5688 characters. The percentage of errors detected and corrected is 11.76% with a recall of 10.16% and precision of 100%

Keywords

Hidden Markov Models; Optical character recognition; Optical data processing

Disciplines

Computer Engineering | Computer Sciences

Language

English


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