Camera brand and model identification using moments of 1-D and 2-D characteristic functions
Document Type
Conference Proceeding
Publication Date
1-1-2009
Abstract
Camera brand and model identification has become one important task of image forensics. Most of the research on this topic focuses on only one or two parts of camera inner structure. In this paper, we propose a universal image statistical model which takes the whole image formation pipeline of cameras into consideration. By examining their comprehensive effects on the formulated images, our assumption is that any difference of the parts of the image formation pipeline can result in the statistical difference of the output image. Moments of 1-D characteristic functions generated from the given image, its JPEG 2-D array, their prediction-error 2-D arrays, and all of their three-level wavelet subbands, and moments of 2-D characteristic functions generated only from JPEG 2-D array accordingly are used to build the statistical model for classification. Our experimental works have verified the effectiveness of this proposed method. ©2009 IEEE.
Identifier
77951948315 (Scopus)
ISBN
[9781424456543]
Publication Title
Proceedings International Conference on Image Processing Icip
External Full Text Location
https://doi.org/10.1109/ICIP.2009.5413341
ISSN
15224880
First Page
2917
Last Page
2920
Recommended Citation
Xu, Guanshuo; Shi, Yun Qing; and Su, Wei, "Camera brand and model identification using moments of 1-D and 2-D characteristic functions" (2009). Faculty Publications. 12272.
https://digitalcommons.njit.edu/fac_pubs/12272
