Novel Hybrid Blind Digital Image Watermarking in Cepstrum and DCT Domain

Abstract

The problem of affine transform attacks refers to many watermarking algorithms. A slight change in the geometry of watermarked image can disable the decoding of embedded information; therefore the advanced watermarking methods should be robust against the above-mentioned procedures. This paper contains a description of the algorithm consisting of two complementary methods of image watermarking. The watermark is encoded in the luminance and chrominance components in the spatial and frequency domains. The decoding process takes place in the two-dimensional Cepstrum and the discrete cosine transform. The algorithm makes the watermarked image robust against the following affine attacks: scaling shearing and translation. Also the following image distortion processes like JPEG lossy compression, adding noise to the watermarked image, median filtering and majority cropping do not cause any loss of hidden information.

Blind image counterwatermarking – hidden data filter

“…2 Example of 2 homomorphic deconvolution filter Fig. 3 The diagram of the masking algorithm [15], its detection based on function D wm f , which is tantamount to determining the coordinates of the coefficient of the two-dimensional autocepstral function and translation values p x ; p y of the copy of the luminance matrix of the original signal O. Then the PSNR value was measured:…”

“…Taking into account the quality of the recovered host image, the algorithm used l ¼ 4 and M size ¼ 4; 4 ½ as the most optimal values for the method of masking the watermark signal. In addition, the method contained in [15] was tested using a popular masking algorithm removing embedded content described in [12] and it demonstrated high resistance to this type of …”

“…In the case of article [15] m,n -indexes of discrete coefficients of the two-dimensional autocepstral matrix.…”

“…Then, after crossing the decision threshold τ, the coordinates of the cepstral coefficient A masking function M cÀwm has also been implemented for recovering the form of the original signal O 0 deg degraded in the communication channel, based on the degraded watermarked signal O 0 wm for cepstral watermarking described in [15] and algorithms that take advantage of functions modulating the added copies of the whole, or component parts of the original signal. The developed masking function uses Wiener blind deconvolution consisting of deconvolution -separation of the watermark signal (which in the general case is de facto imperceptible noise added to the original picture) from the original signal.…”

A Robust Audio Watermarking in Cepstrum Domain Composed of Sample's Relation Dependent Embedding and Computationally Simple Extraction Phase

“…Research interests for watermarking in audio are new compared to that of video [2] and image [7]. The embedding schemes for audio watermarking can be classified either based on domain transformation (time domain-based scheme [8][9][10][11][12] and transform domain-based schemes [16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32]) or based on the necessity of host signal during extraction (blind schemes and non-blind schemes).…”