Robust watermark technique using masking and Hermite transform

Abstract

The following paper evaluates a watermark algorithm designed for digital images by using a perceptive mask and a normalization process, thus preventing human eye detection, as well as ensuring its robustness against common processing and geometric attacks. The Hermite transform is employed because it allows a perfect reconstruction of the image, while incorporating human visual system properties; moreover, it is based on the Gaussian functions derivates. The applied watermark represents information of the digital image proprietor. The extraction process is blind, because it does not require the original image. The following techniques were utilized in the evaluation of the algorithm: peak signal-to-noise ratio, the structural similarity index average, the normalized crossed correlation, and bit error rate. Several watermark extraction tests were performed, with against geometric and common processing attacks. It allowed us to identify how many bits in the watermark can be modified for its adequate extraction.

A Perceptive Approach to Digital Image Watermarking Using a Brightness Model and the Hermite Transform

“…Our results with geometric attacks also show that the watermark resisted most of them, the worst case being Lena image under a scaling attack, with only 13 out of 16 satisfactory detection instances. Comparison with other methods demonstrated that using Hermite Transform is a good way to improve watermark algorithms, as we can review in [12,30].…”

“…A solution is the use of central geometric moments, as proposed in different researches [18,26]. In this work, we suggest achieving robustness to geometric attacks by normalizing the image before embedding the mark [12]. We aim at obtaining the necessary parameters to create a normalized template with intensity values up to 255.…”

“…Among these cases, we find the Discrete Fourier Transform (DFT), the Discrete Wavelet Transform (DWT), the Discrete Cosine Transform (DCT), the Contourlet transform, and other techniques. [4][5][6][7][8][9][10][11][12]. Nevertheless, their use does not guarantee by itself a robust watermarking technique.…”

“…In order to find textured areas, we use the high order Hermite Transform coefficients, which are known to represent perceptually relevant image structures; however, the visual perception of texture is also determined by the contrast and luminance; therefore we use the light adaptation threshold and contrast sensitivity measures that account for a better identification of textured areas where information can be perceptively hidden. In order to improve robustness against geometric attacks, we propose the use of image normalization techniques [1,12,18] that transform the original image so that the orientation and the scale of the objects are fixed. For this purpose, we employ geometric moments and invariants.…”