Innovative Image-Based Approach Enhances Plagiarism Detection in Academia
An Adaptive Image-based Plagiarism Detection Approach đź”—
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.
What is the main purpose of the adaptive image-based plagiarism detection approach?
This approach aims to enhance the detection of disguised forms of academic plagiarism, such as paraphrases and translations, by analyzing images in academic documents.
How is the new detection method evaluated?
The method was evaluated using 15 representative image pairs embedded in a collection of 4,500 related images from academic texts.
What were the results of the evaluation?
The detection approach achieved a recall of 0.73 and a precision of 1, indicating its effectiveness in identifying suspiciously similar content.