UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 12 | Issue 10 | October 2025

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Published in:

Volume 12 Issue 5
May-2025
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2505750


Registration ID:
562803

Page Number

g516-g522

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Title

Automatic Valuation of OMR using Computer Vision Techniques

Abstract

Optical Mark Recognition (OMR) systems have become increasingly vital in educational environments for automating the evaluation of multiple-choice answer sheets. This project presents a Python-based OMR solution using OpenCV to detect and evaluate filled bubbles representing student responses. A novel aspect of this system is its capability to extract a student's Unique Student Number (USN) directly from the bubbled ID section on the answer sheet. The methodology involves a sequence of image processing techniques including grayscale conversion, inverse binary thresholding, contour detection, and morphological filtering to accurately identify marked choices. The system also employs predefined regions of interest to localize both the answer and identification zones. Additionally, results are organized and stored in an Excel file for easy access and record-keeping. This approach reduces manual effort, increases accuracy, and supports scalability for academic institutions. The system was tested on structured OMR sheets with predefined coordinates and demonstrated high precision in both answer recognition and USN extraction. The combination of automation and data accuracy offers a practical, low-cost alternative to commercial OMR scanners, making it well-suited for use in schools, colleges, and online examination platforms.

Key Words

Optical Mark Recognition (OMR), OpenCV,Image Processing, Automated Grading,Contour Detection, Thresholding, USN Extraction, Computer Vision.

Cite This Article

"Automatic Valuation of OMR using Computer Vision Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.g516-g522, May-2025, Available :http://www.jetir.org/papers/JETIR2505750.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Automatic Valuation of OMR using Computer Vision Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppg516-g522, May-2025, Available at : http://www.jetir.org/papers/JETIR2505750.pdf

Publication Details

Published Paper ID: JETIR2505750
Registration ID: 562803
Published In: Volume 12 | Issue 5 | Year May-2025
DOI (Digital Object Identifier):
Page No: g516-g522
Country: Bangalore, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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