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Image Splicing Forgery Detection Using DWT and Local Binary Pattern

Conference paper
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Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 120)

Abstract

The broad use of high-performance tools for image acquisition and strong image processing software has made it easy for malicious purposes to manipulate images. Image splicing, which posed a threat to image integrity and authenticity, is a very popular and easy image forgery trick. Therefore, detection of image splicing is one of the major problems in digital forensics. A new passive (non-intrusive) image tampering detection technique is proposed here to detect splicing forgery based on discrete wavelet transform (DWT) and local binary pattern (LBP). First, input image is converted into YCbCr channels, and then, chroma channels are used as input image for feature extraction using 5-bin histogram and 3-CF moments from DWT domain. Then, ensemble classifier is used for detection of spliced and authentic images.

Keywords

Forgery detection Image splicing CF moments DWT LBP 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringCGPIT, BardoliSuratIndia
  2. 2.Department of Computer Science and EngineeringKoneru Lakshmaiah Education FoundationVaddeswaramIndia
  3. 3.Department of Computer Science and EngineeringR. N. G. Patel Institute of Technology (RNGPIT)BardoliIndia

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