Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features

Offline handwritten digit recognition continues to be a fundamental research problem in document analysis and retrieval. The common method used in extracting handwritten mark from assessment forms is to assign a person to manually type in the marks into a spreadsheet. This method is found to be time...

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Main Authors: Ghai, L.L., Hisham, S.B., Yahya, N.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.31307 /
Published: Institute of Electrical and Electronics Engineers Inc. 2014
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946686315&doi=10.1109%2fICCSCE.2014.7072747&partnerID=40&md5=26b442229f3f6f336729b35cf318bbac
http://eprints.utp.edu.my/31307/
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recordtype eprints
spelling utp-eprints.313072022-03-25T09:05:41Z Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features Ghai, L.L. Hisham, S.B. Yahya, N. Offline handwritten digit recognition continues to be a fundamental research problem in document analysis and retrieval. The common method used in extracting handwritten mark from assessment forms is to assign a person to manually type in the marks into a spreadsheet. This method is found to be time consuming, not cost effective and prone to human mistakes. Thus, a number recognition system is developed using local binary pattern (LBP) technique to extract and convert students' identity numbers and handwritten marks on assessment forms into a spreadsheet. The training data contain three sets of LBP values for each digit. The recognition rate of handwritten digits using LBP is about 50 because LBP could not fully describe the structure of the digits. Instead, LBP is useful in term of scaling the digits '0 to 9' from the highest to the lowest similarity score as compared with the sample using chi square distance. The recognition rate can be greatly improved to about 95 by verifying the ranking of chi square distance with the salient structural features of digits. © 2014 IEEE. Institute of Electrical and Electronics Engineers Inc. 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946686315&doi=10.1109%2fICCSCE.2014.7072747&partnerID=40&md5=26b442229f3f6f336729b35cf318bbac Ghai, L.L. and Hisham, S.B. and Yahya, N. (2014) Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features. In: UNSPECIFIED. http://eprints.utp.edu.my/31307/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Offline handwritten digit recognition continues to be a fundamental research problem in document analysis and retrieval. The common method used in extracting handwritten mark from assessment forms is to assign a person to manually type in the marks into a spreadsheet. This method is found to be time consuming, not cost effective and prone to human mistakes. Thus, a number recognition system is developed using local binary pattern (LBP) technique to extract and convert students' identity numbers and handwritten marks on assessment forms into a spreadsheet. The training data contain three sets of LBP values for each digit. The recognition rate of handwritten digits using LBP is about 50 because LBP could not fully describe the structure of the digits. Instead, LBP is useful in term of scaling the digits '0 to 9' from the highest to the lowest similarity score as compared with the sample using chi square distance. The recognition rate can be greatly improved to about 95 by verifying the ranking of chi square distance with the salient structural features of digits. © 2014 IEEE.
format Conference or Workshop Item
author Ghai, L.L.
Hisham, S.B.
Yahya, N.
spellingShingle Ghai, L.L.
Hisham, S.B.
Yahya, N.
Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features
author_sort Ghai, L.L.
title Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features
title_short Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features
title_full Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features
title_fullStr Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features
title_full_unstemmed Automatic assessment mark entry system using local binary pattern (LBP) and salient structural features
title_sort automatic assessment mark entry system using local binary pattern (lbp) and salient structural features
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946686315&doi=10.1109%2fICCSCE.2014.7072747&partnerID=40&md5=26b442229f3f6f336729b35cf318bbac
http://eprints.utp.edu.my/31307/
_version_ 1741197552327327744
score 11.62408

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