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The Impact of Picture Splicing Operation for Picture Forgery Detection

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Advances in Computing and Data Sciences (ICACDS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 905))

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Abstract

In the time of the present world, analyze of pictures accept a fundamental part. Some picture editing software are open in the market which can change the photo in particular ways. By abusing these software’s, we can adjust the photo by splicing which is difficult to distinguish by human eyes. The electronic pictures have a no. of applications like in criminal and legalistic examination, military, news and so on. So we required some strong strategy for a picture to identify the forgery. This paper proposes a forgery detection technique with Markov Procedure and ensemble classifier, It focuses on splicing detection which extricates Markov-features in spatial and DCT-domain to recognize the antiquated rarities exhibited by the splicing operation and classify them with the ensemble classifier. Not at all like the earlier work, for reducing the computational complexity of SVM with PCA, is an ensemble classifier with an Adaboost algorithm is utilized to classify the photos as being altered or original. The suggested system is surveyed on a straightforwardly available picture splicing data file by using the cross-verification. The results exhibited that the suggested strategy eclipse in inactive splicing identification method.

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Authors and Affiliations

  1. Maharana Partap University of Agriculture and Technology, Udaipur, 313001, India

    Rachna Mehta & Navneet Agrawal

Authors
  1. Rachna Mehta
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  2. Navneet Agrawal
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Correspondence to Rachna Mehta .

Editor information

Editors and Affiliations

  1. University of KwaZulu-Natal, Durban, South Africa

    Mayank Singh

  2. Jaypee University of Information Technology, Solan, India

    P. K. Gupta

  3. Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. Institute of Information Theory and Automation, Prague 8, Czech Republic

    Jan Flusser

  5. University of Ottawa, Ottawa, Canada

    Tuncer Ören

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Mehta, R., Agrawal, N. (2018). The Impact of Picture Splicing Operation for Picture Forgery Detection. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 905. Springer, Singapore. https://doi.org/10.1007/978-981-13-1810-8_29

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  • DOI: https://doi.org/10.1007/978-981-13-1810-8_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1809-2

  • Online ISBN: 978-981-13-1810-8

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