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In this study, a rapid, reliable, and low-cost approach for recognizing and evaluating multiple-choice test marks by placing the OMR sheet in front of the camera. This technology is known as optical mark recognition, and it is the process of capturing data on multiple-choice forms. The image processing library OpenCV was used to create the recognition application, which was written in the Python programming language. When the answer sheet is imported into the application, erroneous answers are highlighted in red, while correct answers are highlighted in green, and the result is written on the optical form image after the calculation of the correct/incorrect answers and blanks. This is a low-cost, quick, and efficient method. The success rate of recognition was calculated to be 99.76 percent. In terms of accuracy, reliability, and performance, empirical experiments have revealed that the proposed system outperforms traditional optical mark recognition systems.
Keywords:
OMR(Optical Mark Recognition), Open CV, Otsu thresholding, Binary Image, Grey Scale Image, Canny Algorithm, Contours.
Cite Article:
"An Optical Mark Recognition And Evaluation System Based On Image Processing", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 7, page no.844 - 849, July-2022, Available :http://www.ijrti.org/papers/IJRTI2207124.pdf
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000204964
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator