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An Efficient Forensic Method Based on High-speed Corner Detection Technique and SIFT Descriptor

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Cloud Computing and Security (ICCCS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10040))

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Abstract

Image manipulation has become commonplace with growing easy access to sophisticated photo editing softwares. One of the most common types of image forgeries is the copy–move forgery, wherein a region from an image is replaced with another region from the same image. Many existing forensic methods suffer from their inability to detect the cloned area, which is subjected to various transformations such as scaling, rotation, flipping and blurring. In this paper, we propose a novel forensic method based on high-speed corner detection (HSCD) technique and improved scale invariant features transform (SIFT) descriptor. Machine learning technique is used to detect feature points which greatly decreasing the processing time compare to other feather detectors. Experimental results show the efficacy of this technique in detecting copy-move forgeries and estimating the geometric transformation parameters. Compared with the state of the art, our approach obtains a higher true positive rate and a lower false positive rate.

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Acknowledgment

This work is supported in part by the National Natural Science Foundation of China (NO. 61232016, U1405254, 61173141, 61173142, 61173136, 61373133, 51503084); the Fundamental Research Funds for the Central Universities (NO. JUSRP11534); the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD); Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET).

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Authors and Affiliations

  1. School of Design, Jiangnan University, Wuxi, 214122, China

    Bin Yang & Honglei Guo

Authors
  1. Bin Yang
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  2. Honglei Guo
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Correspondence to Bin Yang .

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Editors and Affiliations

  1. University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Michigan State University , EAST LANSING, Michigan, USA

    Alex Liu

  3. National Dong Hwa University , Shoufeng, Taiwan

    Han-Chieh Chao

  4. Purdue University , West Lafayette, Indiana, USA

    Elisa Bertino

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Yang, B., Guo, H. (2016). An Efficient Forensic Method Based on High-speed Corner Detection Technique and SIFT Descriptor. In: Sun, X., Liu, A., Chao, HC., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2016. Lecture Notes in Computer Science(), vol 10040. Springer, Cham. https://doi.org/10.1007/978-3-319-48674-1_40

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  • DOI: https://doi.org/10.1007/978-3-319-48674-1_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48673-4

  • Online ISBN: 978-3-319-48674-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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