Title
Scanner identification using spectral noise in the frequency domain
Abstract
As digital images have been propagated all over the world, identification techniques for image sources become more important. In this paper, we analyze properties of the scanner and find the spectral noise appeared in the frequency domain. Based on this observation, we propose a new method for identifying scanner models from scanned images. To enhance characteristics of the spectral noise, a refining process is proposed and employed to scanned images. We make reference patterns with the refined noise for each scanner. The proposed method uses the Euclidean distance to calculate a similarity between each reference pattern and the extracted spectral noise from the test image. The experimental results show that the proposed method achieves high accuracy with various types of images.
Year
DOI
Venue
2010
10.1109/ICIP.2010.5652108
ICIP
Keywords
Field
DocType
image scanners,sensor noise,digital images,frequency-domain analysis,spectral analysis,image denoising,identification techniques,scanner models,scanned images,image forensics,refining process,source identification,reference patterns,spectral noise,frequency domain,scanner identification,euclidean distance,scanner,image sources,accuracy,noise,frequency domain analysis,forensics,digital image
Frequency domain,Computer vision,Noise measurement,Pattern recognition,Computer science,Euclidean distance,Image noise,Digital image,Scanner,Artificial intelligence,Spectral analysis,Standard test image
Conference
ISSN
ISBN
Citations 
1522-4880 E-ISBN : 978-1-4244-7993-1
978-1-4244-7993-1
4
PageRank 
References 
Authors
0.41
7
3
Name
Order
Citations
PageRank
Chang-Hee Choi1120.93
Min-Jeong Lee221114.49
Heung-kyu Lee3101687.53