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Fast Source Camera Identification Using Content Adaptive Guided Image Filter
Author(s) -
Zeng Hui,
Kang Xiangui
Publication year - 2016
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/1556-4029.13017
Subject(s) - computer vision , identification (biology) , artificial intelligence , computer science , content (measure theory) , filter (signal processing) , mathematics , biology , botany , mathematical analysis
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.