Automatic Multiple Choice Test Grader using Computer Vision

This paper contains the procedure for the implementation of an application for exam test grading in a fully automatic way, putting into practice the resources that artificial vision makes available. This application allows you to grade an exam that has been designed in a pre-established format and that has subsequently been solved by the evaluated person. The qualification process is possible through the comparison between the test already solved with the correct answers and the test that the evaluated person has completed. Python and OpenCV were used for the development of the application, the latter was necessary in the image analysis and processing stage, where the objective of the application was based on the recognition of contours and marks detected in the sample photographs. This project proposes a viable and practical option in the optimization of the exam test qualification process, saving time, and making teacher performance more efficient.