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Morphology-Based Sensor Pattern Noise Extraction for Device Identification

Hae-Yeoun Lee
Department of Computer Software Engineering, Kumoh National Institute of Technology, 61 Daehak-ro, Gumi, Gyeongbuk, Republic of Korea

Abstract—Multimedia such as image, audio, and video is easy to create and distribute with the advance of IT. Since novice uses them for illegal purposes, multimedia forensics are required to protect contents and block illegal usage. Using a Morphology-based Sensor Pattern Noise (M-SPN), this paper presents a multimedia forensic algorithm for video to identify the device used for acquiring unknown video files. First, the way to calculate a sensor pattern noise using morphology filter is presented, which comes from the imperfection of photon detectors against light. Then, the way to identify the device is explained after estimating M-SPNs from the reference device and the unknown video. For the experiment, 15 devices including DSLR, compact camera, smartphone, and camcorder are tested and analyzed quantitatively. Based on the results, the presented algorithm can achieve the 92.0% identification accuracy.

Index Terms—multimedia forensics, sensor pattern noise, imaging device identification, morphology filter

Cite: Hae-Yeoun Lee, "Morphology-Based Sensor Pattern Noise Extraction for Device Identification," Journal of Image and Graphics, Vol. 4, No. 2, pp. 145-149, December 2016. doi: 10.18178/joig.4.2.145-149