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Forensic Detection Based on Color Label and Oriented Texture Feature

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11691))

Abstract

Copy-move forgery is one of the most tampered means. In this paper, we propose a blind method based on the color label and oriented color texture feature for copy-move detection. Firstly, we compute local color entropy of every pixel, which is grouped into several categories as color labels. Then an image is divided into overlapping blocks, oriented color texture feature of which is extracted. Similar blocks are searched in these blocks with the same color label, and then we fuse these similar block pairs into several regions. According to the linkage relation of these regions, the tampered regions are located. Experiment results have demonstrated that the proposed algorithm has good performance in terms of improved detection accuracy and reduced execution time, at the same time, it also can detect these tampered images inpainted by exemplar-based inpainting technique.

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Acknowledgement

This authors would like to acknlowledge the financial support of the following research grants: Grant No. 2018GY-135 from Key Research and Development Project of Shaanxi Science and Technology.

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Correspondence to Tingge Zhu .

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Zhu, T. et al. (2020). Forensic Detection Based on Color Label and Oriented Texture Feature. In: Ren, J., et al. Advances in Brain Inspired Cognitive Systems. BICS 2019. Lecture Notes in Computer Science(), vol 11691. Springer, Cham. https://doi.org/10.1007/978-3-030-39431-8_37

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  • DOI: https://doi.org/10.1007/978-3-030-39431-8_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-39430-1

  • Online ISBN: 978-3-030-39431-8

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