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A Super Feature Transform for Small-Size Image Forgery Detection

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1576))

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Abstract

In this digital era, we have a wide variety of image editing software that is prone to create malicious alterations on images. Hence, the evaluation for authenticity of image contents and identification of malicious modifications is an open problem. In this work, an efficient small-size image forgery detection algorithm is presented based on Super Feature Transform - combining Super Resolution and Feature Transform. The approach enhances detection of small-size forgery by pre-processing the input image using super resolution algorithm. A robust feature transform is suggested to extract potential feature points from small-size patches with entanglement properties. Subsequently, feature matching and filtering is achieved by fuzzy threshold so that the false matches are filtered out. Also, the feature matching module employs a soft clustering to determine the matching points between identical and semi-identical feature points in different clusters. The experimental evaluations demonstrated that the proposed method outperforms existing techniques particularly when the forgery size is small and detects manifold duplicate forged regions in terms of TPR and FPR recognition rate.

Supported by DST-PURSE Phase II, Govt of India.

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Acknowledgements

Authors acknowledge the support extended by DST-PURSE Phase II, Govt of India.

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Authors and Affiliations

  1. School of Computer Sciences, Mahatma Gandhi University, Kottayam, Kerala, India

    M. S. Greeshma & V. R. Bindu

Authors
  1. M. S. Greeshma
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  2. V. R. Bindu
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Correspondence to M. S. Greeshma or V. R. Bindu .

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Editors and Affiliations

  1. University of South Dakota, Vermillion, SD, USA

    KC Santosh

  2. Central University of Karnataka, Gulbarga, India

    Ravindra Hegadi

  3. Indian Statistical Institute, Kolkata, India

    Umapada Pal

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Greeshma, M.S., Bindu, V.R. (2022). A Super Feature Transform for Small-Size Image Forgery Detection. In: Santosh, K., Hegadi, R., Pal, U. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2021. Communications in Computer and Information Science, vol 1576. Springer, Cham. https://doi.org/10.1007/978-3-031-07005-1_21

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  • DOI: https://doi.org/10.1007/978-3-031-07005-1_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-07004-4

  • Online ISBN: 978-3-031-07005-1

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