Handwritten Character Recognition System Using Neural Network
Character recognition has been an area of research for a long period of time. It has been argued that this problem is difficult to be modelled using classical modeling techniques, and that neural network offer a new perspective to approach this problem. Therefore the intention of this project...
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| Main Author: | |
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| Format: | Final Year Project Report |
| Language: | English |
| Published: |
Universiti Malaysia Sarawak, (UNIMAS)
2004
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/47535/1/Kuryati.pdf http://ir.unimas.my/id/eprint/47535/ |
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| Summary: | Character recognition has been an area of research for a long period of time. It has been
argued that this problem is difficult to be modelled using classical modeling techniques,
and that neural network offer a new perspective to approach this problem. Therefore the
intention of this project is to investigate the application of neural networks to the
problem of recognizing handwritten alphabet and digit characters. In this project, a
software system capable of recognizing alphabet and digit characters incorporated with
neural network algorithm was developed using MATLAB neural network toolbox. This
project also outlines the experimental evidence that have been compiled while
investigating possible approaches to character recognition. In addition, performing
recognition simulations compare the performances of the various neural networks and
the best neural network performance is then chosen. At the end of the project, the most
suitable backpropagation network properties setting for character recognition were
presented and discussed |
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