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Forgery detection using feature-clustering in recompressed JPEG images

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Abstract

JPEG images are widely used in a large range of applications. The properties of JPEG compression can be used for detection of forgery in digital images. The forgery in JPEG images requires the image to be resaved thereby, re-compression of image. Therefore, the traces of recompression can be identified in order to detect manipulation. In this paper, a method to detect forgery in JPEG image is presented and an algorithm is designed to classify the image blocks as forged or non-forged based on a particular feature present in multi-compressed JPEG images. The method performs better than the previous methods which use the probability based approach for detecting forgery in JPEG images.

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Authors and Affiliations

  1. Department of Computer Engineering and Applications, GLA University, Mathura, Uttar Pradesh, India

    Gunjan Bhartiya & Anand Singh Jalal

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  1. Gunjan Bhartiya
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  2. Anand Singh Jalal
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Correspondence to Anand Singh Jalal.

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Bhartiya, G., Jalal, A.S. Forgery detection using feature-clustering in recompressed JPEG images. Multimed Tools Appl 76, 20799–20814 (2017). https://doi.org/10.1007/s11042-016-3964-3

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  • DOI: https://doi.org/10.1007/s11042-016-3964-3

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