Paper Info
Title
Camera brand and model identification using moments of 1-D and 2-D characteristic functions
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.
Year
DOI
Venue
2009
10.1109/ICIP.2009.5413341
ICIP
Keywords
Field
DocType
universal image,image representation,jpeg 2-d array,jpeg 2d array,universal image statistical model,model identification,moments of characteristic functions,statistical analysis,camera identification,image formation pipeline,2-d array,cameras,output image,image forensics,whole image formation pipeline,2-d characteristic function,statistical model,camera brand,image formation,characteristic function,histograms,transform coding,prediction error,feature extraction,pixel
Computer vision,Pattern recognition,Computer science,Image quality,Feature extraction,Image formation,JPEG,Artificial intelligence,Statistical model,Pixel,System identification,Wavelet
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-5655-0
978-1-4244-5655-0
2
PageRank 
References 
Authors
0.36
4
3
Name
Order
Citations
PageRank
Guanshuo Xu11245.26
Yun Qing Shi251823.34
Wei Su362938.52