relation: https://khub.utp.edu.my/scholars/1065/
title: Handwriting recognition system using Fast Wavelets Transform
creator: Gumah, M.E.
creator: Schneider, E.
creator: Aburas, A.A.
description: 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.
date: 2010
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Gumah, M.E. and Schneider, E. and Aburas, A.A.  (2010) Handwriting recognition system using Fast Wavelets Transform.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-78049396533&doi=10.1109%2fITSIM.2010.5561302&partnerID=40&md5=a839702dfcd624bb464ccad31f3a9546
relation: 10.1109/ITSIM.2010.5561302
identifier: 10.1109/ITSIM.2010.5561302