Abstract
Many existing source camera identification technique depend on a set of images of known origins to train a classifier or to acquire the reference pattern noise of camera, and match the being tested images. However, it is hard to get the natural images which are the same type of tested image as training image library in our actual applications. In this work, we propose the automatic source camera identification technique based-on Hierarchy Clustering method, which can formulate the classification task without any training image library. Experimental results have verified the validity and practicality of the proposed approach at last.
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Acknowledgement
The authors would like to thank Professor Yongjian Hu from South China University of Technology.
Funding
This work is partially supported by Young Teachers Program of Scientific Innovation Project from China People's Police University (ZQN2020028), Key Research Project from China People's Police University (2019zdgg012), Sino-Singapore International Joint Research Institute (206-A017023, 206-A018001), Science and Technology Project of Hebei Education Department (QN2021417) and Natural Science Foundation of Shenzhen (JCYJ20190808122005605).
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Lai, Z., Wang, Y., Sun, W., Zhang, P. (2021). Automatic Source Camera Identification Technique Based-on Hierarchy Clustering Method. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2021. Lecture Notes in Computer Science(), vol 12737. Springer, Cham. https://doi.org/10.1007/978-3-030-78612-0_58
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