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ACCURACY ENHANCEMENT OF OMR FOR EXAM MARKING WITHOUT PRE-SET TEMPLATE USING IMAGE PROCESSING

Optical Mark Recognition (OMR) is used to automate answer matching especially in the education sector. OMR marking machine is costly and limited to specific OMR paper design, thus launching researches using image processing to find less costly solutions. However, studies so far have achieved r...

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Main Author: Tow, Jingyi
Format: Final Year Project
Language:English
Published: IRC 2019
Subjects:
Q Science (General)
Online Access:http://utpedia.utp.edu.my/20965/1/Tow%20Jingyi_22784.pdf
http://utpedia.utp.edu.my/20965/
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spelling my-utp-utpedia.209652021-09-10T08:57:33Z http://utpedia.utp.edu.my/20965/ ACCURACY ENHANCEMENT OF OMR FOR EXAM MARKING WITHOUT PRE-SET TEMPLATE USING IMAGE PROCESSING Tow, Jingyi Q Science (General) Optical Mark Recognition (OMR) is used to automate answer matching especially in the education sector. OMR marking machine is costly and limited to specific OMR paper design, thus launching researches using image processing to find less costly solutions. However, studies so far have achieved relatively low accuracy and poor consistency unless a fixed OMR form design is used. Accuracy drops with more OMR questions. Therefore, this study investigate means to improve OMR marking accuracy using enhanced algorithm designed for OMR marking. The results were compared against manual marking as the control and existing image processing algorithms. The metrics used are F1 score and percentage error for accuracy of detected answer options and marking fault respectively. The result is encouraging with consistent full accuracy for up to 90 questions as compared to previous works. IRC 2019-09 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/20965/1/Tow%20Jingyi_22784.pdf Tow, Jingyi (2019) ACCURACY ENHANCEMENT OF OMR FOR EXAM MARKING WITHOUT PRE-SET TEMPLATE USING IMAGE PROCESSING. IRC, Universiti Teknologi PETRONAS. (Submitted)
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
topic Q Science (General)
spellingShingle Q Science (General)
Tow, Jingyi
ACCURACY ENHANCEMENT OF OMR FOR EXAM MARKING WITHOUT PRE-SET TEMPLATE USING IMAGE PROCESSING
description Optical Mark Recognition (OMR) is used to automate answer matching especially in the education sector. OMR marking machine is costly and limited to specific OMR paper design, thus launching researches using image processing to find less costly solutions. However, studies so far have achieved relatively low accuracy and poor consistency unless a fixed OMR form design is used. Accuracy drops with more OMR questions. Therefore, this study investigate means to improve OMR marking accuracy using enhanced algorithm designed for OMR marking. The results were compared against manual marking as the control and existing image processing algorithms. The metrics used are F1 score and percentage error for accuracy of detected answer options and marking fault respectively. The result is encouraging with consistent full accuracy for up to 90 questions as compared to previous works.
format Final Year Project
author Tow, Jingyi
author_facet Tow, Jingyi
author_sort Tow, Jingyi
title ACCURACY ENHANCEMENT OF OMR FOR EXAM MARKING WITHOUT PRE-SET TEMPLATE USING IMAGE PROCESSING
title_short ACCURACY ENHANCEMENT OF OMR FOR EXAM MARKING WITHOUT PRE-SET TEMPLATE USING IMAGE PROCESSING
title_full ACCURACY ENHANCEMENT OF OMR FOR EXAM MARKING WITHOUT PRE-SET TEMPLATE USING IMAGE PROCESSING
title_fullStr ACCURACY ENHANCEMENT OF OMR FOR EXAM MARKING WITHOUT PRE-SET TEMPLATE USING IMAGE PROCESSING
title_full_unstemmed ACCURACY ENHANCEMENT OF OMR FOR EXAM MARKING WITHOUT PRE-SET TEMPLATE USING IMAGE PROCESSING
title_sort accuracy enhancement of omr for exam marking without pre-set template using image processing
publisher IRC
publishDate 2019
url http://utpedia.utp.edu.my/20965/1/Tow%20Jingyi_22784.pdf
http://utpedia.utp.edu.my/20965/
_version_ 1739832818787155968
score 13.211869

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