Source camera identification is still a hard task in forensics community, especially for the case of the small query image size. In this paper, we propose a solution to identify the source camera of the small-size images: content-adaptive fusion network. In order to learn better feature representation from the input data, content-adaptive convolutional neural networks(CA-CNN) are constructed. We add a convolutional layer in preprocessing stage. Moreover, with the purpose of capturing more comprehensive information, we parallel three CA-CNNs: CA3-CNN, CA5-CNN, CA7-CNN to get the content-adaptive fusion network. The difference of three CA-CNNs lies in the convolutional kernel size of pre-processing layer. The experimental results show that the proposed method is practicable and satisfactory.
@article{arxiv.1703.04856,
title = {Source Camera Identification Based On Content-Adaptive Fusion Network},
author = {Pengpeng Yang and Wei Zhao and Rongrong Ni and Yao Zhao},
journal= {arXiv preprint arXiv:1703.04856},
year = {2017}
}
Comments
This article has been submitted to the 2017 IEEE International Conference on Image Processing