Blind Detection of Partial-Color-Manipulation Based on Self-PRNU Estimation

Blind Detection of Partial-Color-Manipulation Based on Self-PRNU Estimation

Sun Yuting, Guo Jing, Du Ling, Ke Yongzhen
Copyright: © 2018 |Volume: 10 |Issue: 3 |Pages: 14
ISSN: 1941-6210|EISSN: 1941-6229|EISBN13: 9781522543626|DOI: 10.4018/IJDCF.2018070101
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MLA

Yuting, Sun, et al. "Blind Detection of Partial-Color-Manipulation Based on Self-PRNU Estimation." IJDCF vol.10, no.3 2018: pp.1-14. http://doi.org/10.4018/IJDCF.2018070101

APA

Yuting, S., Jing, G., Ling, D., & Yongzhen, K. (2018). Blind Detection of Partial-Color-Manipulation Based on Self-PRNU Estimation. International Journal of Digital Crime and Forensics (IJDCF), 10(3), 1-14. http://doi.org/10.4018/IJDCF.2018070101

Chicago

Yuting, Sun, et al. "Blind Detection of Partial-Color-Manipulation Based on Self-PRNU Estimation," International Journal of Digital Crime and Forensics (IJDCF) 10, no.3: 1-14. http://doi.org/10.4018/IJDCF.2018070101

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Abstract

This article describes how to detect color manipulation which is a commonly used method in the field of digital image forgery. The difficulty that hue forgery does not change the image edges, shapes and gradations brings certain challenge to authenticity detection. Current methods utilize the PRNU from multiple un-tampered images, requiring the camera type to be known. However, the increasing varieties of digital devices greatly complicates the preparation of prior knowledge. This article proposes a blind detection method for partial color manipulation based on self-PRNU of suspicious image, eliminating the necessity of acquiring camera information. The authors estimate the PRNU of suspicious image by removing the regions due to its texture complexity. The tamper region is detected by calculating the correlation between estimated PRNU and residual noise. As to partial manipulation detection, an introduced threshold of connected components is used to reduce the false positive. The experimental results show that the method can effectively detect and locate the partial color manipulation.

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