Abstract
in an academic environment, plagiarism is the process of copying someone else's text, idea or data verbatim or without due recognition of the source, which is a serious academic offence. Many techniques have been proposed in the literature for detecting plagiarism in texts, but only a few techniques exist for detecting figure plagiarism. The main problem associated with existing techniques of plagiarism detection is that they are not applicable to non-textual elements of figures in research publications. This paper focuses on detecting plagiarism in scientific figures. Textual-reference representation based figure plagiarism detection techniques are proposed and evaluated, based on existing limitations. The proposed techniques use enhanced feature extraction such as textual features and similarity computation methods such as similarity based on textual-reference of figures. The enhanced feature extraction method was found to be capable of extracting textual references such as captions and description texts. The similarity detection method was capable of categorising a given figure as either plagiarised or non-plagiarised from a source collection of scientific publications, depending on a certain threshold value. Results showed that the proposed technique achieved precision=0.78 and recall=0.67 result in terms of the evaluation measure.