Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network

This project is about the handwritten numerical strings that were extracted, segmented, and verified for bank cheques. This project has four objectives. The first objective is to make data collection for digitized handwritten courtesy amount on bank cheques. The second objective is to locate the...

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Main Author:	Anak Francis, Adam
Format:	Student Project
Published:	Faculty of Information Technology and Quantitative Sciences 2005
Online Access:	http://ir.uitm.edu.my/id/eprint/638/

id	uitm-638
recordtype	eprints
spelling	uitm-6382017-04-19T09:18:44Z http://ir.uitm.edu.my/id/eprint/638/ Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network Anak Francis, Adam This project is about the handwritten numerical strings that were extracted, segmented, and verified for bank cheques. This project has four objectives. The first objective is to make data collection for digitized handwritten courtesy amount on bank cheques. The second objective is to locate the position of the amount courtesy block for the extraction process by using the Coordinate Search. The third objective is to perform Vertical Splitting Algorithm technique for digit segmentation. And lastly, to develop an Artificial Neural Network for digit recognition. The project is hoped to bring benefits to the people who is doing the same studies on image processing. The general result for this project is that; this system has an accuracy of 60% in recognizing and verifying the handwritten numerical strings for 300 training data sets and 50 testing data sets. For the back- propagation neural network module, the numbers of hidden nodes in the hidden layer that have been selected was 2, the sum squared errors was 0.001, the momentum was 0.95, the learning rate was 0.7 and the initial weight was set in the range of [-2.4, 2.4]. Faculty of Information Technology and Quantitative Sciences 2005 Student Project NonPeerReviewed Anak Francis, Adam (2005) Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network. [Student Project] (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
description	This project is about the handwritten numerical strings that were extracted, segmented, and verified for bank cheques. This project has four objectives. The first objective is to make data collection for digitized handwritten courtesy amount on bank cheques. The second objective is to locate the position of the amount courtesy block for the extraction process by using the Coordinate Search. The third objective is to perform Vertical Splitting Algorithm technique for digit segmentation. And lastly, to develop an Artificial Neural Network for digit recognition. The project is hoped to bring benefits to the people who is doing the same studies on image processing. The general result for this project is that; this system has an accuracy of 60% in recognizing and verifying the handwritten numerical strings for 300 training data sets and 50 testing data sets. For the back- propagation neural network module, the numbers of hidden nodes in the hidden layer that have been selected was 2, the sum squared errors was 0.001, the momentum was 0.95, the learning rate was 0.7 and the initial weight was set in the range of [-2.4, 2.4].
format	Student Project
author	Anak Francis, Adam
spellingShingle	Anak Francis, Adam Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network
author_facet	Anak Francis, Adam
author_sort	Anak Francis, Adam
title	Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network
title_short	Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network
title_full	Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network
title_fullStr	Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network
title_full_unstemmed	Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network
title_sort	development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network
publisher	Faculty of Information Technology and Quantitative Sciences
publishDate	2005
url	http://ir.uitm.edu.my/id/eprint/638/
first_indexed	2023-09-18T22:44:47Z
last_indexed	2023-09-18T22:44:47Z
_version_	1777417152273317888

Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network

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