سال انتشار: ۱۳۹۰

محل انتشار: هفتمین کنفرانس ماشین بینایی و پردازش تصویر

تعداد صفحات: ۴

نویسنده(ها):

Fereshteh Gharibi – Computer Engineering Department, University of Kurdistan, Sanandaj, Kurdistan, Iran
Javad RavanJamjah – Computer Engineering Department, University of Kurdistan, Sanandaj, Kurdistan, Iran
Fardin Akhlaghian – Computer Engineering Department, University of Kurdistan, Sanandaj, Kurdistan, Iran
Bahram ZahirAzami – University of Ontario Institute of Technology, Oshawa, Ontario, Canada

چکیده:

Sensor pattern noise (SPN) as the fingerprint of imagingdevices, could be used as a reliable feature in digital sourceidentification. In this paper, we introduce a new methodwhich uses the probability model of SPN to identify thesource. To achieve this goal, after extracting the SPN ofsome images, they are digitized and then for each value, thedistribution of its neighbors is modeled separately (Value-Model). Finally by using the value-model, the quantizedSPN is mapped to the probability domain. The average ofprobability matrix of some images of same camera formscamera model. This SPN model causes noticeable increasesin the true detection rate of the source. To evaluate theefficiency of proposed approach, we do some benchmark onour hypothesis. The accuracy and performance of our modelcompared to similar works, proves high efficiency of theproposed theory.