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2015 | OriginalPaper | Chapter

75. Identifying Image Splicing Based on Local Statistical Features in DCT and DWT Domain

Authors : Yujin Zhang, Shenghong Li, Shilin Wang, Xudong Zhao

Published in: The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems

Publisher: Springer International Publishing

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Abstract

In this paper, an effective image splicing detection algorithm based on the local statistical features in DCT and DWT domain is proposed. The local ternary pattern (LTP) operator is introduced to characterize the statistical changes of DCT and DWT coefficients caused by image splicing. The LTP histograms are generated from the magnitude components of the block DCT coefficients with varying block sizes and the DWT coefficients in three detail subbands, respectively. All these LTP histograms are concatenated together to form the discriminative feature set for splicing detection. The effectiveness of the proposed detector is evaluated on the Columbia image splicing detection evaluation dataset. Simulation results have shown that the proposed method can perform better than several state-of-the-art methods investigated.

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Metadata
Title
Identifying Image Splicing Based on Local Statistical Features in DCT and DWT Domain
Authors
Yujin Zhang
Shenghong Li
Shilin Wang
Xudong Zhao
Copyright Year
2015
Book
The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems

Print ISBN: 978-3-319-08990-4

Electronic ISBN: 978-3-319-08991-1

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-08991-1_75