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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Bibliographic Details
Main Author: Francis, Adam
Format: Student Project
Published: Faculty of Information Technology and Quantitative Sciences 2005
Online Access:https://ir.uitm.edu.my/id/eprint/638/
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author Francis, Adam
author_facet Francis, Adam
author_sort Francis, Adam
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].
first_indexed 2025-11-14T21:22:14Z
format Student Project
id uitm-638
institution Universiti Teknologi MARA
institution_category Local University
last_indexed 2025-11-14T21:22:14Z
publishDate 2005
publisher Faculty of Information Technology and Quantitative Sciences
recordtype eprints
repository_type Digital Repository
spelling uitm-6382024-10-29T03:44:01Z https://ir.uitm.edu.my/id/eprint/638/ Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network 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 Francis, Adam (2005) Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network. (2005) [Student Project] <http://terminalib.uitm.edu.my/638.pdf> (Unpublished)
spellingShingle Francis, Adam
Development of unconstrained handwritten digit extraction, segmentation and recognition on bank cheques using artificial neural network
title 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_short 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
url https://ir.uitm.edu.my/id/eprint/638/