PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Improved Content-Based Watermarking Using Scale-Invariant Feature Points
Na Li, Edwin Hancock, Xiaoshi Zheng and Lin Han
In: Image Analysis and Processing - ICIAP 2011 - 16th International Conference, September 14-16, 2011, Ravenna, Italy.


For most HVS(Human Visual System) perceptual models, the JND(Just Noticeable Difference) values in highly-textured image regions have little difference with those in edge areas. This is not consistent with the characteristics of human vision. In this paper, an improved method is introduced to give a better content-based perceptual mask than traditional ones using the arrangement of scale-invariant feature points. It could decrease the JND values in edge areas of those traditional masks so that they have an obvious difference with values in highly textured areas. Experimental results show the advantages of this improved approach visually, and the enhancement of the invisibility of watermarks.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:8558
Deposited By:Edwin Hancock
Deposited On:13 February 2012