Automated Verification of English Proficiency Test Scores Using OCR for Graduation Qualification

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dc.contributor.authorTitijaroonroj, Taravichet
dc.contributor.authorMaliwan, Thitiwut
dc.contributor.authorJaimetha, Nattakamon
dc.contributor.authorWattanacheep, Bhattarabhorn
dc.date.accessioned2026-08-06T10:48:37Z
dc.date.available2026-08-06T10:48:37Z
dc.date.issued2025-01-01
dc.description.abstractAn algorithm is proposed to verify English proficiency scores using OCR for graduation qualification, aiming to reduce errors and workload in the current manual verification process of officer. Score reports in image or PDF format, including TOEIC and KMITL-TEP, are processed using two deep learning-based document classifiers that identify the test type and score type prior to OCR execution. Preprocessing techniques such as noise reduction, contrast enhancement, and skew correction are applied to improve OCR accuracy. Three OCR models-Tesseract, TrOCR, and EasyOCR-are evaluated for text extraction performance. The extracted textual data are then converted into structured JSON, enabling automated rule-based comparison against graduation criteria. Evaluation performance is measured using Accuracy, F1-Score, Character Error Rate (CER), and Word Error Rate (WER). Experimental results show that the proposed system achieves 99% accuracy, demonstrating both high reliability and adaptability to institutional scoring standards. The integration of OCR significantly reduces processing time while maintaining flexibility to accommodate future changes in assessment policies.
dc.identifier.citationIcsec 2025 29th International Computer Science and Engineering Conference 2025, 123-128, 2025
dc.identifier.doi10.1109/ICSEC67360.2025.11298124
dc.identifier.other2-s2.0-105032741118
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/16301
dc.sourceIcsec 2025 29th International Computer Science and Engineering Conference 2025
dc.subjectDocument classification
dc.subjectEasyOCR
dc.subjectEnglish exam score
dc.subjectOptical Character Recognition
dc.subjectScore verification
dc.subjectTesseract OCR
dc.subjectTrOCR
dc.titleAutomated Verification of English Proficiency Test Scores Using OCR for Graduation Qualification
dc.typeConference Paper

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