Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi

This project presents a study on the offline handwritten character recognition using backpropagation algorithm that is one of the training algorithms used in Artificial Neural Network. In this method, information about errors is propagated backwards from output to input layers in order to adjust the...

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Bibliographic Details
Main Author:	Mohadi, Masnizah
Format:	Thesis
Language:	English
Published:	2005
Subjects:	Neural networks (Computer science) Pattern recognition systems
Online Access:	https://ir.uitm.edu.my/id/eprint/9391/1/TD_MASNIZAH%20MOHADI%20CS%2005_1.pdf
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id	my-uitm-ir.9391
record_format	uketd_dc
spelling	my-uitm-ir.93912017-01-25T06:45:33Z Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi 2005 Mohadi, Masnizah Neural networks (Computer science) Pattern recognition systems This project presents a study on the offline handwritten character recognition using backpropagation algorithm that is one of the training algorithms used in Artificial Neural Network. In this method, information about errors is propagated backwards from output to input layers in order to adjust the connection between the layers thus improving the network's performances. The purpose of this project is to recognized handwritten characters that were scanned earlier before the recognition process begins. For the purpose of this project, only lowercase characters from a to z are considered which total up to 26 characters all. Each handwritten characters is collected from 19 people, each in a 2 X 1.5cm box using a black ballpoint pen. From this process, 13 data collected are used for training and 6 more are used to train the network in order to evaluate the network's performance. The useful features of information that was extracted from the handwritten character images are the edges of the character using Sobel Edge Detection Method. As a result of this project, it is proven that the backpropagation algorithm can be used for recognizing handwritten characters and recognition tasks depends highly on how the data was preprocessed and the network parameter itself. 2005 Thesis https://ir.uitm.edu.my/id/eprint/9391/ https://ir.uitm.edu.my/id/eprint/9391/1/TD_MASNIZAH%20MOHADI%20CS%2005_1.pdf text en public other degree Universiti Teknologi MARA Faculty of Computer and Mathematical Science
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Neural networks (Computer science) Pattern recognition systems
spellingShingle	Neural networks (Computer science) Pattern recognition systems Mohadi, Masnizah Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi
description	This project presents a study on the offline handwritten character recognition using backpropagation algorithm that is one of the training algorithms used in Artificial Neural Network. In this method, information about errors is propagated backwards from output to input layers in order to adjust the connection between the layers thus improving the network's performances. The purpose of this project is to recognized handwritten characters that were scanned earlier before the recognition process begins. For the purpose of this project, only lowercase characters from a to z are considered which total up to 26 characters all. Each handwritten characters is collected from 19 people, each in a 2 X 1.5cm box using a black ballpoint pen. From this process, 13 data collected are used for training and 6 more are used to train the network in order to evaluate the network's performance. The useful features of information that was extracted from the handwritten character images are the edges of the character using Sobel Edge Detection Method. As a result of this project, it is proven that the backpropagation algorithm can be used for recognizing handwritten characters and recognition tasks depends highly on how the data was preprocessed and the network parameter itself.
format	Thesis
qualification_name	other
qualification_level	Bachelor degree
author	Mohadi, Masnizah
author_facet	Mohadi, Masnizah
author_sort	Mohadi, Masnizah
title	Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi
title_short	Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi
title_full	Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi
title_fullStr	Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi
title_full_unstemmed	Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi
title_sort	offline handwritten character recognition using backpropagation neural network / masnizah mohadi
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Science
publishDate	2005
url	https://ir.uitm.edu.my/id/eprint/9391/1/TD_MASNIZAH%20MOHADI%20CS%2005_1.pdf
_version_	1783733155287531520

Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi

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