TY - GEN
T1 - Digital forgery detection scheme incorporating imaging device characteristics using wiener filter
AU - Shim, Jae Youn
AU - Kim, Seong Whan
PY - 2012
Y1 - 2012
N2 - Advent of digital cameras and photo editing software allows digital images easily manipulated and altered. Although accurate forgeries may leave no visual clues of having been tampered with, they may, nevertheless, alter the underlying statistics of an image. As previous research works, we analyzed digital camera image processing schemes, and identified what kind of imaging device characteristics can be unique and how to identify them. To exploit the imaging device characteristics, we perform Wiener filter to extract the unique feature of imaging device. After we identified the device characteristics, we perform EM based forensic scheme for the domain. We design an overlapped Wiener filter based forgery detection scheme for each image blocks to test evidence of forgery in a specific image. Our experimental results show that our forgery detection performance achieved more robustness on JPEG compression (quality factor set to 98).
AB - Advent of digital cameras and photo editing software allows digital images easily manipulated and altered. Although accurate forgeries may leave no visual clues of having been tampered with, they may, nevertheless, alter the underlying statistics of an image. As previous research works, we analyzed digital camera image processing schemes, and identified what kind of imaging device characteristics can be unique and how to identify them. To exploit the imaging device characteristics, we perform Wiener filter to extract the unique feature of imaging device. After we identified the device characteristics, we perform EM based forensic scheme for the domain. We design an overlapped Wiener filter based forgery detection scheme for each image blocks to test evidence of forgery in a specific image. Our experimental results show that our forgery detection performance achieved more robustness on JPEG compression (quality factor set to 98).
KW - Digital image forensics
KW - EM algorithm
KW - Image noise
KW - Wiener filter
UR - http://www.scopus.com/inward/record.url?scp=84255198339&partnerID=8YFLogxK
U2 - 10.1007/978-94-007-2792-2_70
DO - 10.1007/978-94-007-2792-2_70
M3 - Conference contribution
AN - SCOPUS:84255198339
SN - 9789400727915
T3 - Lecture Notes in Electrical Engineering
SP - 713
EP - 721
BT - Computer Science and Convergence, CSA 2011 and WCC 2011 Proceedings
T2 - 3rd International Conference on Computer Science and Its Applications, CSA 2011 and 2011 FTRA World Convergence Conference, WCC 2011
Y2 - 12 December 2011 through 15 December 2011
ER -