PCEP: Few-Shot Model-Based Source Camera Identification

Bo Wang, Fei Yu, Yanyan Ma (), Haining Zhao, Jiayao Hou and Weiming Zheng
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Bo Wang: School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China
Fei Yu: School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China
Yanyan Ma: School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China
Haining Zhao: School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China
Jiayao Hou: School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China
Weiming Zheng: School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China

Mathematics, 2023, vol. 11, issue 4, 1-16

Abstract: Source camera identification is an important branch in the field of digital forensics. Most existing works are based on the assumption that the number of training samples is sufficient. However, in practice, it is unrealistic to obtain a large amount of labeled samples. Therefore, in order to solve the problem of low accuracy for existing methods in a few-shot scenario, we propose a novel identification method called prototype construction with ensemble projection (PCEP). In this work, we extract a variety of features from few-shot datasets to obtain rich prior information. Then, we introduce semi-supervised learning to complete the construction of prototype sets. Subsequently, we use the prototype sets to retrain SVM classifiers, and take the posterior probability of each image sample belonging to each class as the final projection vector. Finally, we obtain classification results through ensemble learning voting. The PCEP method combines feature extraction, feature projection, classifier training and ensemble learning into a unified framework, which makes full use of image information of few-shot datasets. We conduct comprehensive experiments on multiple benchmark databases (i.e., Dresden, VISION and SOCRatES), and empirically show that our method achieves satisfactory performance and outperforms many recent methods in a few-shot scenario.

Keywords: source camera identification; few-shot; prototype construction; ensemble projection (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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