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An improved approach for single and multiple copy-move forgery detection and localization in digital images

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Abstract

With the expeditious advancement in digital technology and image editing software, it has become easy to manipulate digital images. Copy-move is a common type of image forgery, which threatens the authenticity of digital images by copying and pasting a certain part of the image within the same image. The main focus of this paper is to detect single as well as multiple copy-move forgeries efficiently by combining block-based and keypoint-based detection approaches. The fusion of block-based detection techniques i.e. adaptive over-segmentation (AS) and keypoint-based detection techniques i.e. accelerated KAZE (AKAZE) and scale-invariant feature transform (SIFT) makes the proposed scheme robust against various geometrical attacks as well as less computationally expensive. Moreover, the input image is converted into the different color channels and then, Cr channel is used for further processing because it detects the tampering artifacts left in the image which cannot be observed by human eyes. Also, the copy-move forgery is detected more precisely even in smooth regions due to the extraction of an adequate number of key points. The experimental results are executed on MICC-F220, IMD, GRIP, and COVERAGE datasets, and various performance metrics like precision, recall, F1 score, and F2 score are evaluated. The experimental results show that the proposed technique is robust against various geometrical attacks i.e. rotation, scaling, JPEG compression, and noise addition, and proved better when compared with the other existing techniques. Moreover, to ensure the robustness of the proposed approach, the statistical analysis test using ANOVA and cross-dataset performance is evaluated.

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Authors and Affiliations

  1. Electronics and Communication Engineering Department, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

    Navneet Kaur, Neeru Jindal & Kulbir Singh

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  1. Navneet Kaur
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  2. Neeru Jindal
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  3. Kulbir Singh
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Correspondence to Kulbir Singh.

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Kaur, N., Jindal, N. & Singh, K. An improved approach for single and multiple copy-move forgery detection and localization in digital images. Multimed Tools Appl 81, 38817–38847 (2022). https://doi.org/10.1007/s11042-022-13105-6

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