Shape-Based Plagiarism Detection for Flowchart Figures in Texts
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TLDR
In this article, the authors presented a method for detecting flow chart figure plagiarism based on shape-based image processing and multimedia retrieval, which managed to retrieve flowcharts with ranked similarity according to different matching sets.Abstract:
Plagiarism detection is well known phenomenon in the academic arena. Copying other people is considered as serious offence that needs to be checked. There are many plagiarism detection systems such as turn-it-in that has been developed to provide this checks. Most, if not all, discard the figures and charts before checking for plagiarism. Discarding the figures and charts results in look holes that people can take advantage. That means people can plagiarized figures and charts easily without the current plagiarism systems detecting it. There are very few papers which talks about flowcharts plagiarism detection. Therefore, there is a need to develop a system that will detect plagiarism in figures and charts. This paper presents a method for detecting flow chart figure plagiarism based on shape-based image processing and multimedia retrieval. The method managed to retrieve flowcharts with ranked similarity according to different matching sets.read more
Citations
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Book ChapterDOI
Content-Based Scientific Figure Plagiarism Detection Using Semantic Mapping
TL;DR: This paper investigates the issue of idea and figure plagiarism and proposes a detection method which copes with text and structure change and depends on finding similar semantic meanings between figures by applying image processing and semantic mapping techniques.
Journal ArticleDOI
Flowchart Plagiarism Detection System: An Image Processing Approach
TL;DR: In the proposed flow chart plagiarism detection system, flowcharts are compared by comparing both the shape, orientation as well as text, which is capable to detect the plagiarism with same shaped objects even though the orientation of the graph is changed.
Proceedings ArticleDOI
Detecting plagiarism in images
TL;DR: A flaw has been identified in this system that when a document is getting scanned for plagiarism each and every line is tested if any image is detected during scan then that image is simply discarded, which is very inappropriate because an image can also be plagiarized.
Book ChapterDOI
Figure Plagiarism Detection Using Content-Based Features
TL;DR: This paper focuses on detecting plagiarism in scientific figures and proposes a content-based figure plagiarism detection technique based on the feature extraction and similarity computation methods.
Proceedings ArticleDOI
Figure plagiarism detection based on textual features representation
TL;DR: The enhanced feature extraction method was found to be capable of extracting textual references such as captions and description texts and 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.
References
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Dengsheng Zhang,Guojun Lu +1 more
TL;DR: This paper identifies some promising techniques for image retrieval according to standard principles and examines implementation procedures for each technique and discusses its advantages and disadvantages.
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Plagiarism - A Survey
TL;DR: This paper discusses the complex general setting, then reports on some results of plagiarism detection software, and draws attention to the fact that any serious investigation in plagiarism turns up rather unexpected side-effects.
Journal ArticleDOI
Online plagiarism detection services—saviour or scourge?
TL;DR: It is argued that if online detection is used in conjunction with the many valuable ‘anti‐plagiarism’ resources and tutorials available on the web, it really can become a positive teaching aid for staff and students alike, rather than a threatening online policing system.
Proceedings ArticleDOI
First experiments on a new online handwritten flowchart database
TL;DR: This paper proposes a new online handwritten flowchart database, adopts a global learning schema and a recognition architecture that considers a simultaneous segmentation and recognition, and proposes different classifiers to perform two tasks, text/non-text separation and graphical symbol recognition.
Book
Data Management for Multimedia Retrieval
TL;DR: This textbook on multimedia data management techniques offers a unified perspective on retrieval efficiency and effectiveness and presents data structures and algorithms that help store, index, cluster, classify, and access common data representations.