OMR Automated Grading

Abstract

The paper highlights the necessity for a technologically advanced system capable of efficiently grading multiple-choice question (MCQ) exams through webcam-based evaluation. MCQ-style assessments have gained widespread use in educational and organizational settings due to their effectiveness and time-saving advantages. However, manually grading these exams presents significant challenges. Managing a large number of answer sheets in a timely manner is labor-intensive and error-prone, potentially leading to scoring discrepancies. Additionally, the logistical burden of storing and handling physical answer sheets is cumbersome, with risks such as damage from environmental factors like fire or moisture. While larger institutions may utilize specialized Optical Mark Recognition (OMR) technology for grading, smaller educational entities often lack access to such costly equipment. To address these challenges, the paper proposes an innovative solution: leveraging webcam technology to automate the grading process. By capturing images of answer sheets and employing sophisticated content-filtering and image processing algorithms facilitated by the OpenCV library, the system can accurately interpret and evaluate marked answers. Overall, the proposed system represents a significant advancement in exam grading methodology, providing a practical and cost-effective solution to the longstanding challenges associated with manual grading of MCQ-based assessments. By integrating webcam technology into the grading process, the system aims to enhance efficiency and accuracy while catering to the needs of various educational and organizational assessments.