In the realm of document processing and data extraction, OMR plays a crucial role in automating tasks such as grading exams, conducting surveys, and processing questionnaires. Our project takes advantage of the powerful OpenCV library to develop an OMR Sheet Scanning system that scans and analyzes OMR sheets, accurately calculating correct answers based on the marked circles.
Using computer vision techniques provided by OpenCV, our system processes scanned or captured images of OMR sheets. It employs image processing algorithms to detect and extract individual circles or bubbles representing answer choices. By analyzing the marked circles and their locations, our system determines the selected answers for each question.
The OpenCV OMR Sheet Scanning system also incorporates sophisticated image segmentation and recognition techniques to eliminate noise, improve accuracy, and enhance the reliability of results. The system precisely identifies the relevant regions of interest (ROIs), focuses on extracting the necessary information, and discards any irrelevant or redundant data.
Once the system has recognized the marked circles, it compares them against the correct answer key to determine the accuracy of the responses. The OMR Sheet Scanning system then generates a report indicating the number of correct and incorrect answers, as well as any additional statistics or metrics required.
This repository contains all the necessary code and resources to implement the OpenCV OMR Sheet Scanning system. Whether you are a developer seeking to explore the inner workings of the algorithms or an organization looking to automate your OMR sheet processing, you will find everything you need here.