Recognition of the cursive handwritten courtesy amounts of Malaysian bank cheques.

In this paper, we present techniques to recognise the cursive handwritten courtesy amount from Malaysian bank cheques and convert it into its corresponding ASCII codes. The image is pre- processed and segmented using the combination of crossed-point, curved-point and histogram techniques. Three t...

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Main Authors: Sulaiman, Md. Nasir, Khalid, Marzuki
Format: Conference or Workshop Item
Language:English
English
Published: 2001
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/20832/
http://psasir.upm.edu.my/id/eprint/20832/1/ID%2020832.pdf
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author Sulaiman, Md. Nasir
Khalid, Marzuki
author_facet Sulaiman, Md. Nasir
Khalid, Marzuki
author_sort Sulaiman, Md. Nasir
building UPM Institutional Repository
collection Online Access
description In this paper, we present techniques to recognise the cursive handwritten courtesy amount from Malaysian bank cheques and convert it into its corresponding ASCII codes. The image is pre- processed and segmented using the combination of crossed-point, curved-point and histogram techniques. Three type of feature extraction methods which are transitions, shapes and moment invariant are used to extract local and global features of segmented handwritten digits. The main purpose of the feature extraction is to capture the most relevant and discriminant characteristics of the object. A three layer Neural Network architecture with the new error function of backpropagation learning algorithm is used as recogniser. This approach yields good recognition results with faster convergence rates.
first_indexed 2025-11-15T08:25:04Z
format Conference or Workshop Item
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institution Universiti Putra Malaysia
institution_category Local University
language English
English
last_indexed 2025-11-15T08:25:04Z
publishDate 2001
recordtype eprints
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spelling upm-208322014-08-28T08:03:40Z http://psasir.upm.edu.my/id/eprint/20832/ Recognition of the cursive handwritten courtesy amounts of Malaysian bank cheques. Sulaiman, Md. Nasir Khalid, Marzuki In this paper, we present techniques to recognise the cursive handwritten courtesy amount from Malaysian bank cheques and convert it into its corresponding ASCII codes. The image is pre- processed and segmented using the combination of crossed-point, curved-point and histogram techniques. Three type of feature extraction methods which are transitions, shapes and moment invariant are used to extract local and global features of segmented handwritten digits. The main purpose of the feature extraction is to capture the most relevant and discriminant characteristics of the object. A three layer Neural Network architecture with the new error function of backpropagation learning algorithm is used as recogniser. This approach yields good recognition results with faster convergence rates. 2001 Conference or Workshop Item NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/20832/1/ID%2020832.pdf Sulaiman, Md. Nasir and Khalid, Marzuki (2001) Recognition of the cursive handwritten courtesy amounts of Malaysian bank cheques. In: Persidangan Kebangsaan Penyelidikan & Pembangunan IPTA 2001 (25-26 Oktober 2001) hosted in Universiti Kebangsaan Malaysia, Bangi, Selangor, 25-26 Oktober 2001, Universiti Kebangsaan Malaysia, Bangi, Selangor. (pp. 848-852). Handwritten checks - Malaysia Neural networks (Computer science) English
spellingShingle Handwritten checks - Malaysia
Neural networks (Computer science)
Sulaiman, Md. Nasir
Khalid, Marzuki
Recognition of the cursive handwritten courtesy amounts of Malaysian bank cheques.
title Recognition of the cursive handwritten courtesy amounts of Malaysian bank cheques.
title_full Recognition of the cursive handwritten courtesy amounts of Malaysian bank cheques.
title_fullStr Recognition of the cursive handwritten courtesy amounts of Malaysian bank cheques.
title_full_unstemmed Recognition of the cursive handwritten courtesy amounts of Malaysian bank cheques.
title_short Recognition of the cursive handwritten courtesy amounts of Malaysian bank cheques.
title_sort recognition of the cursive handwritten courtesy amounts of malaysian bank cheques.
topic Handwritten checks - Malaysia
Neural networks (Computer science)
url http://psasir.upm.edu.my/id/eprint/20832/
http://psasir.upm.edu.my/id/eprint/20832/1/ID%2020832.pdf