Fundamental study on identification of CMOS cameras

Kenji Kurosawa; Naoki Saitoh

doi:10.1117/12.487480

8 August 2003 Fundamental study on identification of CMOS cameras

Kenji Kurosawa, Naoki Saitoh

Proceedings Volume 5108, Visual Information Processing XII; (2003) https://doi.org/10.1117/12.487480
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

In this study, we discussed individual camera identification of CMOS cameras, because CMOS (complementary-metal-oxide-semiconductor) imaging detectors have begun to make their move into the CCD (charge-coupled-device) fields for recent years. It can be identified whether or not the given images have been taken with the given CMOS camera by detecting the imager's intrinsic unique fixed pattern noise (FPN) just like the individual CCD camera identification method proposed by the authors. Both dark and bright pictures taken with the CMOS cameras can be identified by the method, because not only dark current in the photo detectors but also MOS-FET amplifiers incorporated in each pixel may produce pixel-to-pixel nonuniformity in sensitivity. Each pixel in CMOS detectors has the amplifier, which degrades image quality of bright images due to the nonuniformity of the amplifier gain. Two CMOS cameras were evaluated in our experiments. They were WebCamGoPlus (Creative), and EOS D30 (Canon). WebCamGoPlus is a low-priced web camera, whereas EOS D30 is for professional use. Image of a white plate were recorded with the cameras under the plate's luminance condition of 0cd/m² and 150cd/m². The recorded images were multiply integrated to reduce the random noise component. From the images of both cameras, characteristic dots patterns were observed. Some bright dots were observed in the dark images, whereas some dark dots were in the bright images. The results show that the camera identification method is also effective for CMOS cameras.

Citation Download Citation

Kenji Kurosawa and Naoki Saitoh "Fundamental study on identification of CMOS cameras", Proc. SPIE 5108, Visual Information Processing XII, (8 August 2003); https://doi.org/10.1117/12.487480

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