TY - GEN
T1 - Geometric invariant digital image watermarking scheme based on feature points detector and histogram distribution
AU - Pun, Chi Man
AU - Yuan, Xiao Chen
AU - Chen, C. L.Philip
PY - 2011
Y1 - 2011
N2 - A robust and geometric invariant digital image watermarking scheme based on SIFT Based Feature Points Detector (SIFT-FPD) and histogram distribution is proposed in this paper. The SIFT-FPD is proposed to extract geometric invariant feature points from the host image for watermark embedding, and the descriptor is generated subsequently. With the feature extraction procedure, the circular regions centered at the extracted feature points and with the given radius are defined as embedding regions. For watermark embedding, some pixels are moved to form a specific pattern in the intensity-level histogram distribution in each embedding region, to indicate the watermark. For watermark extraction, the embedded regions are generated with the descriptor and according to the intensity-level histogram distribution in each region, the watermark can be extracted. Experimental results show that the proposed scheme is very robust against geometric distortion such as rotation, scaling, cropping, and affine transformation, and common signal processing, such as JPEG compression, median filtering, and Gaussian low-pass filtering.
AB - A robust and geometric invariant digital image watermarking scheme based on SIFT Based Feature Points Detector (SIFT-FPD) and histogram distribution is proposed in this paper. The SIFT-FPD is proposed to extract geometric invariant feature points from the host image for watermark embedding, and the descriptor is generated subsequently. With the feature extraction procedure, the circular regions centered at the extracted feature points and with the given radius are defined as embedding regions. For watermark embedding, some pixels are moved to form a specific pattern in the intensity-level histogram distribution in each embedding region, to indicate the watermark. For watermark extraction, the embedded regions are generated with the descriptor and according to the intensity-level histogram distribution in each region, the watermark can be extracted. Experimental results show that the proposed scheme is very robust against geometric distortion such as rotation, scaling, cropping, and affine transformation, and common signal processing, such as JPEG compression, median filtering, and Gaussian low-pass filtering.
KW - Feature Extraction
KW - Geometric Invariant
KW - Histogram Distribution
KW - SIFT
UR - http://www.scopus.com/inward/record.url?scp=84862965400&partnerID=8YFLogxK
U2 - 10.1109/TrustCom.2011.24
DO - 10.1109/TrustCom.2011.24
M3 - Conference contribution
AN - SCOPUS:84862965400
SN - 9780769546001
T3 - Proc. 10th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications, TrustCom 2011, 8th IEEE Int. Conf. on Embedded Software and Systems, ICESS 2011, 6th Int. Conf. on FCST 2011
SP - 166
EP - 172
BT - Proc. 10th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications, TrustCom 2011, 8th IEEE Int. Conf. on Embedded Software and Systems, ICESS 2011, 6th Int. Conf. FCST 2011
T2 - 10th IEEE Int. Conf. on Trust, Security and Privacy in Computing and Communications, TrustCom 2011, 8th IEEE Int. Conf. on Embedded Software and Systems, ICESS 2011, 6th Int. Conf. on Frontier of Computer Science and Technology, FCST 2011
Y2 - 16 November 2011 through 18 November 2011
ER -