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Recent Trends in Communication, Computing, and Electronics pp 289–299Cite as

Copy-Move Forgery Detection Using Shift-Invariant SWT and Block Division Mean Features

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Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 524))

Abstract

Digital images are used in courtrooms as evidence. We cannot predict nativity of the image without forensic analysis. Tampering with the image is common nowadays with a lot of online and offline tools. To hide an object in an image, regions of the same image are copied and pasted on that object, and this is known as copy-move forgery. In this paper, we have introduced a technique to detect such type of forgery, known as CMFD. In this technique, the image is pre-processed by converting RGB into YCbCr and then Y channel is decomposed into four components of translation-invariant stationary wavelet transform (SWT). Its LL (approximation) component is then divided into 8 × 8 blocks. Further, from each block, we have taken six mean features which are calculated by dividing each block into four squares and two triangular blocks and put them into feature vector with block location. After sorting these feature vectors into lexicographical order, we get the location of forged regions.

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Author information

Authors and Affiliations

  1. Computing and Vision Lab, Department of Computer Science and Engineering, Indian Institute of Technology (BHU) Varanasi, Varanasi, India

    Ankit Kumar Jaiswal & Rajeev Srivastava

Authors
  1. Ankit Kumar Jaiswal
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  2. Rajeev Srivastava
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Corresponding author

Correspondence to Ankit Kumar Jaiswal .

Editor information

Editors and Affiliations

  1. University of Allahabad, Allahabad, India

    Ashish Khare

  2. Indian Institute of Information Technology, Allahabad, Uttar Pradesh, India

    Uma Shankar Tiwary

  3. Oakland University, Rochester, MI, USA

    Ishwar K. Sethi

  4. University of Allahabad, Allahabad, Uttar Pradesh, India

    Nar Singh

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Cite this paper

Jaiswal, A.K., Srivastava, R. (2019). Copy-Move Forgery Detection Using Shift-Invariant SWT and Block Division Mean Features. In: Khare, A., Tiwary, U., Sethi, I., Singh, N. (eds) Recent Trends in Communication, Computing, and Electronics. Lecture Notes in Electrical Engineering, vol 524. Springer, Singapore. https://doi.org/10.1007/978-981-13-2685-1_28

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  • DOI: https://doi.org/10.1007/978-981-13-2685-1_28

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2684-4

  • Online ISBN: 978-981-13-2685-1

  • eBook Packages: EngineeringEngineering (R0)

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