{"id":{"repo_id":"windsor","oai_identifier":"oai:uwindsor.scholaris.ca:20.500.14776/9565"},"canonical_url":"https://search.dev.ndltd.org/etd/windsor/oai:uwindsor.scholaris.ca:20.500.14776/9565","repository":{"repo_id":"windsor","name":"University of Windsor","base_url":"https://uwindsor.scholaris.ca/server/oai/request"},"display":{"title":"Webcam-Based Optical Mark Reader for Grading Assessments","abstract":"Optical Mark Recognition (OMR) is a process of retrieving information from the forms where users put marks in particular locations. OMR technique has been improved significantly since its inception, moving from specialized hardware-based solutions to more adaptable and sophisticated software-based solutions using a scanner. Recently, webcam-based software solutions have emerged because of their affordability and ease of use. In this thesis, we propose an improved webcam-based OMR solution for grading the student tests given on a specifically formatted answer sheet. We apply various image processing techniques to achieve effective grading, resolving technical problems stemming from multiple factors like image orientation, skewness, and uneven illumination. In particular, we propose a new variant of the Otsu binarization technique for image segmentation to effectively separate the background and foreground. The proposed grading solution aims at maximizing the criteria for acceptable operations so that 100% accurate grading among those accepted ones can be achieved. The evaluation of the proposed method is two-fold: (i) the proposed variant of Otsu is compared with other binarization algorithms for its effectiveness in background separation; (ii) the grading system is compared with the state-of-the-art webcam-based systems where the individual contribution of each applied image processing technique to the grading enhancement will be identified.","abstract_html":"Optical Mark Recognition (OMR) is a process of retrieving information from the forms where users put marks in particular locations. OMR technique has been improved significantly since its inception, moving from specialized hardware-based solutions to more adaptable and sophisticated software-based solutions using a scanner. Recently, webcam-based software solutions have emerged because of their affordability and ease of use. In this thesis, we propose an improved webcam-based OMR solution for grading the student tests given on a specifically formatted answer sheet. We apply various image processing techniques to achieve effective grading, resolving technical problems stemming from multiple factors like image orientation, skewness, and uneven illumination. In particular, we propose a new variant of the Otsu binarization technique for image segmentation to effectively separate the background and foreground. The proposed grading solution aims at maximizing the criteria for acceptable operations so that 100% accurate grading among those accepted ones can be achieved. The evaluation of the proposed method is two-fold: (i) the proposed variant of Otsu is compared with other binarization algorithms for its effectiveness in background separation; (ii) the grading system is compared with the state-of-the-art webcam-based systems where the individual contribution of each applied image processing technique to the grading enhancement will be identified.","abstract_has_math":false,"creators":["Zafar, Muhammad Fahad"],"institution":"University of Windsor","degree_name":"M.Sc.","degree_level":"Masters","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["scholarship@uwindsor.ca"],"advisors":["Baki, Mohammed Fazle","Ahmad, Imran Shafiq"],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-01-01","date_published":"2023-01-01","updated_at":"2026-07-27T22:04:54Z","subjects":[],"languages":["en_CA"],"rights":[],"rights_urls":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/20.500.14776/9565","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["scholarship@uwindsor.ca"]},{"key":"dc:contributor.advisor","label":"Advisor","values":["Baki, Mohammed Fazle","Ahmad, Imran Shafiq"]},{"key":"dc:creator","label":"Author","values":["Zafar, Muhammad Fahad"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2025-07-03 14:27"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2023-02-28 14:06","2025-07-03T18:27:50Z"]},{"key":"dc:date.issued","label":"Date","values":["2023-01-01"]},{"key":"dc:type","label":"Dc Type","values":["info:eu-repo/semantics/masterThesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science","Computer Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.Sc."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Windsor"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en_CA"]},{"key":"dc:rights","label":"Dc Rights","values":["http://creativecommons.org/licenses/by-nc-nd/4.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/20.500.14776/9565"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Optical Mark Recognition (OMR) is a process of retrieving information from the forms where users put marks in particular locations. OMR technique has been improved significantly since its inception, moving from specialized hardware-based solutions to more adaptable and sophisticated software-based solutions using a scanner. Recently, webcam-based software solutions have emerged because of their affordability and ease of use. In this thesis, we propose an improved webcam-based OMR solution for grading the student tests given on a specifically formatted answer sheet. We apply various image processing techniques to achieve effective grading, resolving technical problems stemming from multiple factors like image orientation, skewness, and uneven illumination. In particular, we propose a new variant of the Otsu binarization technique for image segmentation to effectively separate the background and foreground. The proposed grading solution aims at maximizing the criteria for acceptable operations so that 100% accurate grading among those accepted ones can be achieved. The evaluation of the proposed method is two-fold: (i) the proposed variant of Otsu is compared with other binarization algorithms for its effectiveness in background separation; (ii) the grading system is compared with the state-of-the-art webcam-based systems where the individual contribution of each applied image processing technique to the grading enhancement will be identified."]},{"key":"dc:title","label":"Title","values":["Webcam-Based Optical Mark Reader for Grading Assessments"]}]}],"canonical_facts":{"dc:contributor":["scholarship@uwindsor.ca"],"dc:contributor.advisor":["Baki, Mohammed Fazle","Ahmad, Imran Shafiq"],"dc:creator":["Zafar, Muhammad Fahad"],"dc:date.accessioned":["2025-07-03 14:27"],"dc:date.available":["2023-02-28 14:06","2025-07-03T18:27:50Z"],"dc:date.issued":["2023-01-01"],"dc:description.abstract":["Optical Mark Recognition (OMR) is a process of retrieving information from the forms where users put marks in particular locations. OMR technique has been improved significantly since its inception, moving from specialized hardware-based solutions to more adaptable and sophisticated software-based solutions using a scanner. Recently, webcam-based software solutions have emerged because of their affordability and ease of use. In this thesis, we propose an improved webcam-based OMR solution for grading the student tests given on a specifically formatted answer sheet. We apply various image processing techniques to achieve effective grading, resolving technical problems stemming from multiple factors like image orientation, skewness, and uneven illumination. In particular, we propose a new variant of the Otsu binarization technique for image segmentation to effectively separate the background and foreground. The proposed grading solution aims at maximizing the criteria for acceptable operations so that 100% accurate grading among those accepted ones can be achieved. The evaluation of the proposed method is two-fold: (i) the proposed variant of Otsu is compared with other binarization algorithms for its effectiveness in background separation; (ii) the grading system is compared with the state-of-the-art webcam-based systems where the individual contribution of each applied image processing technique to the grading enhancement will be identified."],"dc:identifier.uri":["https://hdl.handle.net/20.500.14776/9565"],"dc:language.iso":["en_CA"],"dc:rights":["http://creativecommons.org/licenses/by-nc-nd/4.0/"],"dc:title":["Webcam-Based Optical Mark Reader for Grading Assessments"],"dc:type":["info:eu-repo/semantics/masterThesis"],"thesis:degree_discipline":["Computer Science","Computer Sciences"],"thesis:degree_level":["Masters"],"thesis:degree_name":["M.Sc."],"thesis:institution_name":["University of Windsor"]},"updated_at":"2026-07-27T22:04:54Z"}