Innovative Image-Based Approach Enhances Plagiarism Detection in Academia

Identifying plagiarism in academic work is vital for educational and research institutions. Traditional plagiarism detection systems excel in finding copied text but struggle with disguised forms, like paraphrasing or translations. To address this, a new adaptive image-based approach has been developed that analyzes images in documents as independent features. This method combines established techniques like perceptual hashing with innovative assessments, yielding promising results in identifying image similarities in academic texts. The system demonstrated a recall rate of 0.73 and a precision of 1, suggesting it effectively complements existing text-based systems. The researchers have made their code available as open source to encourage further exploration in this area.