Multimed Tools Appl (2018) 77:31239–31260 https://doi.org/10.1007/s11042-018-6230-z Digital image splicing detection based on Markov features in block DWT domain 1 1,2 1 Qingbo Zhang · Wei Lu · Ruxin Wang · Guoqiang Li Received: 5 October 2017 / Revised: 24 May 2018 / Accepted: 29 May 2018 / Published online: 5 June 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract Image splicing is very common and fundamental in image tampering. Many splicing detection schemes based on Markov features in transform domain have been pro- posed. Based on previous studies, the traditional DWT based schemes perform not better than the DCT based schemes. In this paper, a block DWT based scheme is proposed to improve the detection performance of the DWT based scheme. Firstly, the block DWT is applied on the source image. Then, the Markov features are constructed in block DWT domain to characterize the dependency among wavelet coefficients across positions. After that, feature selection method SVM-RFE is used to reduce the dimensionality of features. Finally, Support Vector Machine is exploited to classify the authentic and spliced images. Experiment results show that the detection performance of the features extracted in DWT domain can be improved with
Multimedia Tools and Applications – Springer Journals
Published: Jun 5, 2018
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