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Detection of copy-move forgery using AKAZE and SIFT keypoint extraction

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Abstract

Digital image manipulation techniques are becoming increasingly sophisticated and widespread. Copy-move forgery is one of the frequently used manipulation techniques. In this paper, we propose a keypoint based copy-move forgery detection (CMFD) technique, which is a combination of accelerated KAZE (AKAZE) and scale invariant feature transform (SIFT) features. By using AKZAE and SIFT, a significant number of keypoints are extracted even in a smooth region to detect the manipulated regions efficiently. After formation of the mixed keypoints, the g2NN is used for matching process to locate the duplicated regions. The experimental results show that the proposed method can detect the duplicated regions even if the image is post-processed with scaling, rotation, noise and JPEG compression operations. To validate the robustness and effectiveness of the proposed method, a statistical analysis is performed using the ANOVA method.

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Authors and Affiliations

  1. Department of Computer Science and Technology, Indian Institute of Technology (Indian School of Mines), Dhanbad, India

    Choudhary Shyam Prakash, Prajwal Pralhad Panzade, Hari Om & Sushila Maheshkar

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  1. Choudhary Shyam Prakash
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  2. Prajwal Pralhad Panzade
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  3. Hari Om
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  4. Sushila Maheshkar
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Correspondence to Choudhary Shyam Prakash.

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Prakash, C.S., Panzade, P.P., Om, H. et al. Detection of copy-move forgery using AKAZE and SIFT keypoint extraction. Multimed Tools Appl 78, 23535–23558 (2019). https://doi.org/10.1007/s11042-019-7629-x

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  • DOI: https://doi.org/10.1007/s11042-019-7629-x

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