title: Fast Source Camera Identification Using Content Adaptive Guided Image Filter.
abstract: Source camera identification (SCI) is an important topic in image forensics. One of the most effective fingerprints for linking an image to its source camera is the sensor pattern noise, which is estimated as the difference between the content and its denoised version. It is widely believed that the performance of the sensor-based SCI heavily relies on the denoising filter used. This study proposes a novel sensor-based SCI method using content adaptive guided image filter (CAGIF). Thanks to the low complexity nature of the CAGIF, the proposed method is much faster than the state-of-the-art methods, which is a big advantage considering the potential real-time application of SCI. Despite the advantage of speed, experimental results also show that the proposed method can achieve comparable or better performance than the state-of-the-art methods in terms of accuracy.
authors.affiliation: School of Information Science & Tech., Sun Yat-sen University, Guangzhou, 510006, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Zeng
authors.affiliation: School of Information Science & Tech., Sun Yat-sen University, Guangzhou, 510006, China.
authors.forename: Xiangui
authors.initials: X
authors.lastname: Kang
keywords: content adaptive guided image filter; denoising filter; forensic science; image forensics; sensor pattern noise; source camera identification