Abstract
The paper presents results of research oriented towards an application of image processing methods into document comparisons in view of their application into plagiarism-detection systems. Among all image processing methods, the feature-point ones, thanks to their invariance to various image transforms, are best suited for computing image similarity. In the paper various combination of feature point detectors and descriptors are investigated as potential tool for finding similar images in document. The methods are tested on the database consisting of scientific papers containing 5 well known image processing test images. Also, an idea is presented in the paper how the algorithms computing the image similarity may extend the functionality of plagiarism detection systems.
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Notes
- 1.
The total number of images in the last row of the Table 1 does not sum up to 162 (total number of images) because some multiple images consist of several test ones.
- 2.
The implementation of all but one detectors and descriptors was based on the appropriate procedures included in MATLAB Computer Vision Systems Toolbox. Only the code for the SIFT method was taken from the VLfeat external MATLAB toolbox.
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Acknowledgments
This work was partially supported by the European Union within the European Regional Development Fund. The authors would like also to thank prof. Marek Kowalski for support and fruitful discussions on the plagiarism detection topic.
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Iwanowski, M., Cacko, A., Sarwas, G. (2016). Comparing Images for Document Plagiarism Detection. In: Chmielewski, L., Datta, A., Kozera, R., Wojciechowski, K. (eds) Computer Vision and Graphics. ICCVG 2016. Lecture Notes in Computer Science(), vol 9972. Springer, Cham. https://doi.org/10.1007/978-3-319-46418-3_47
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