Automated Plagiarism Detection in Handwritten Documents Using Various Computer Vision Algorithms

The aim of the paper is to devise an integrated web-based system that incorporates automated plagiarism detection across handwritten documents with user authentication features. This system basically improves text visibility using advanced image processing techniques, digitizes handwritten text by Optical Character Recognition, and uses string matching algorithms to come up with some sort of textual similarity quantification. It will calculate a plagiarism percentage, thereby giving a clear indication of textual overlap between documents. The web-based platform shall integrate secure login functionality for faculty and students. As a student, one would be able to upload an assignment and compare it with a reference file. As faculty, one would have the functionality to compare files from two students in order to detect plagiarism. This shall help in plagiarism detection across multiple languages. It will further provide feedback regarding detected plagiarism, store the given feedback in a database, and finally generate detailed reports for reviewing students' plagiarism history and overall performance. The solution will address challenges for handwritten text comparison and academic integrity, providing a practical tool for educational institutions to verify the originality of handwritten work.