Gumah, M.E. and Schneider, E. and Aburas, A.A. (2010) Handwriting recognition system using Fast Wavelets Transform. In: UNSPECIFIED.
Full text not available from this repository.Abstract
Optical Characters Recognition (OCR) is one of the active subjects of research since the early days of computer science. There are two main stages in most of OCR systems: features extraction and classification. Artificial Neural Networks and Hidden Markov Models are the most popular classification methods used for OCR systems. In this paper, a method that relays on Fast Wavelets Transform (FWT) for optical character recognition is proposed. The idea of the proposed technique is to use the FWT to produce a coefficient vector of the character images, which will be directly used to recognize characters. Using the proposed technique, an accuracy of 94.18 in average was achieved. © 2010 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 2; Conference of 2010 International Symposium on Information Technology, ITSim'10 ; Conference Date: 15 June 2010 Through 17 June 2010; Conference Code:81915 |
Uncontrolled Keywords: | A-coefficient; Arabic characters; Artificial Neural Network; Character images; Classification methods; Features extraction; Handwriting recognition; Optical Characters Recognition; Wavelets transform, Feature extraction; Hidden Markov models; Information technology; Neural networks; Optical character recognition, Wavelet transforms |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 15:49 |
Last Modified: | 09 Nov 2023 15:49 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/1065 |