• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Classifier Combination Based Source Identification for Cell Phone Images


Abstract

Rapid popularization of smart cell phone equipped with camera has led to a number of new legal and criminal problems related to multimedia such as digital image, which makes cell phone source identification an important branch of digital image forensics. This paper proposes a classifier combination based source identification strategy for cell phone images. To identify the outlier cell phone models of the training sets in multi-class classifier, a one-class classifier is orderly used in the framework. Feature vectors including color filter array (CFA) interpolation coefficients estimation and multi-feature fusion is employed to verify the effectiveness of the classifier combination strategy. Experimental results demonstrate that for different feature sets, our method presents high accuracy of source identification both for the cell phone in the training sets and the outliers.


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Cite this article

[IEEE Style]
Bo Wang, Yue Tan, Meijuan Zhao, Yanqing Guo and Xiangwei Kong, "Classifier Combination Based Source Identification for Cell Phone Images," KSII Transactions on Internet and Information Systems, vol. 9, no. 12, pp. 5087-5102, 2015. DOI: 10.3837/tiis.2015.12.019

[ACM Style]
Wang, B., Tan, Y., Zhao, M., Guo, Y., and Kong, X. 2015. Classifier Combination Based Source Identification for Cell Phone Images. KSII Transactions on Internet and Information Systems, 9, 12, (2015), 5087-5102. DOI: 10.3837/tiis.2015.12.019