Title: Plagiarism detection of figure images in scientific publications
Authors: Taiseer Abdalla Elfadil Eisa
Addresses: College of Science and Arts-Girls Section, King Khalid University Mahayil, Asir, Saudi Arabia
Abstract: Plagiarism is stealing others' work using their words directly or indirectly without a credit citation. Copying others' ideas is another type of plagiarism that may occur in many areas but the most serious one is the academic plagiarism. Therefore, technical solutions are urgently required for automatic detection of idea plagiarism. Detection of figure plagiarism is a particularly challenging field of research, because not only the text analytics but also graphic features need to be analysed. This paper investigates the issues of idea and figure plagiarism and proposes a detection method which copes with both text and structure change. The procedure depends on finding similar semantic meanings between figures by applying image processing and semantic mapping techniques. The figures were compared using the representation of shape features based on detailed comparisons between the components of figures. This is an improvement over existing methods, which only compare the numbers and types of shapes inside figures.
Keywords: plagiarism detection; figure plagiarism detection; idea plagiarism detection; academic plagiarism; image processing; semantic mapping techniques; content-based algorithms.
International Journal of Data Mining, Modelling and Management, 2022 Vol.14 No.1, pp.15 - 29
Received: 30 Nov 2019
Accepted: 28 Jun 2020
Published online: 08 Apr 2022 *