OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi

Optical Mark Recognition (OMR) sheets have been used by many educational institutions. Marking process approach varied either using automatic OMR machine or manually marking the answers. By using the image processing techniques, researchers came up with solutions to automatically mark the answers wi...

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Bibliographic Details
Main Author:	Rosdi, Rasrizal Hakimi
Format:	Student Project
Language:	English
Published:	Faculty of Computer and Mathematical Sciences 2019
Subjects:	Application software Android T Technology (General)
Online Access:	http://ir.uitm.edu.my/id/eprint/24097/ http://ir.uitm.edu.my/id/eprint/24097/1/PPb_RASRIZAL%20HAKIMI%20ROSDI%20M%20CS%2019_5.pdf

id	uitm-24097
recordtype	eprints
spelling	uitm-240972019-05-29T04:06:24Z http://ir.uitm.edu.my/id/eprint/24097/ OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi Rosdi, Rasrizal Hakimi Application software Android T Technology (General) Optical Mark Recognition (OMR) sheets have been used by many educational institutions. Marking process approach varied either using automatic OMR machine or manually marking the answers. By using the image processing techniques, researchers came up with solutions to automatically mark the answers without the need of OMR machine. In this project, OMR Grader Mobile Application is system prototype for OMR answer grading that had been developed to approach the automatic way of process the OMR answer without OMR machines based on image processing. The prototype developed is using OpenCV library for image processing purposes. Rapid Application Development (RAD) model is used in this project There are four phases in this development model, the requirement gathering, user design, development and cutover. The developed prototype main concerned is about accuracy. To know the accuracy of the system, accuracy test is used. There are three categories for the test, camera resolution test, grid lines alignment test and light intensity test. For the samples, five files were tested for each category. The camera resolution test included three camera resolutions, 0.3 MP with the 20 percent accurate, 0.7 MP with 100 percent accurate and 5.0 MP with 40 percent accurate. The test for grid lines alignment consists of three conditions, correctly aligned with 100 percent accuracy, slightly aligned with 40 percent accuracy and completely misaligned with 0 percent accuracy. The test result for light intensity for dark surrounding is 40 percent accurate, for the home light conditions is 100 percent accuracy and 80 percent accuracy for uneven lighting. For future works, the warp perspective functions should be applied to image processing algorithm to make the answer detection accuracy much precise. Faculty of Computer and Mathematical Sciences 2019 Student Project NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/24097/1/PPb_RASRIZAL%20HAKIMI%20ROSDI%20M%20CS%2019_5.pdf Rosdi, Rasrizal Hakimi (2019) OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi. [Student Project] (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Teknologi MARA
building	UiTM Institutional Repository
collection	Online Access
language	English
topic	Application software Android T Technology (General)
spellingShingle	Application software Android T Technology (General) Rosdi, Rasrizal Hakimi OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi
description	Optical Mark Recognition (OMR) sheets have been used by many educational institutions. Marking process approach varied either using automatic OMR machine or manually marking the answers. By using the image processing techniques, researchers came up with solutions to automatically mark the answers without the need of OMR machine. In this project, OMR Grader Mobile Application is system prototype for OMR answer grading that had been developed to approach the automatic way of process the OMR answer without OMR machines based on image processing. The prototype developed is using OpenCV library for image processing purposes. Rapid Application Development (RAD) model is used in this project There are four phases in this development model, the requirement gathering, user design, development and cutover. The developed prototype main concerned is about accuracy. To know the accuracy of the system, accuracy test is used. There are three categories for the test, camera resolution test, grid lines alignment test and light intensity test. For the samples, five files were tested for each category. The camera resolution test included three camera resolutions, 0.3 MP with the 20 percent accurate, 0.7 MP with 100 percent accurate and 5.0 MP with 40 percent accurate. The test for grid lines alignment consists of three conditions, correctly aligned with 100 percent accuracy, slightly aligned with 40 percent accuracy and completely misaligned with 0 percent accuracy. The test result for light intensity for dark surrounding is 40 percent accurate, for the home light conditions is 100 percent accuracy and 80 percent accuracy for uneven lighting. For future works, the warp perspective functions should be applied to image processing algorithm to make the answer detection accuracy much precise.
format	Student Project
author	Rosdi, Rasrizal Hakimi
author_facet	Rosdi, Rasrizal Hakimi
author_sort	Rosdi, Rasrizal Hakimi
title	OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi
title_short	OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi
title_full	OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi
title_fullStr	OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi
title_full_unstemmed	OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi
title_sort	omr grader mobile app using image processing / rasrizal hakimi rosdi
publisher	Faculty of Computer and Mathematical Sciences
publishDate	2019
url	http://ir.uitm.edu.my/id/eprint/24097/ http://ir.uitm.edu.my/id/eprint/24097/1/PPb_RASRIZAL%20HAKIMI%20ROSDI%20M%20CS%2019_5.pdf
first_indexed	2023-09-18T23:11:52Z
last_indexed	2023-09-18T23:11:52Z
_version_	1777418855989116928

OMR grader mobile app using image processing / Rasrizal Hakimi Rosdi

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