AbstractTo solve the sensitive problem of signal processing and geometricdistortion of digital image watermarking, an image watermarkingalgorithm against geometric attacks was proposed in the paper.After decomposing the whole image with 3 level of discrete wavelettransform and transforming the watermark image by Arnoldshuffling, embed the watermark data to the media frequencycoefficients of wavelet domain according to the conceal quality ofHuman Visual System (HVS); and extract two invariant centroids asfactors to correcting geometric transformation by using thetheories of invariant centroid, the watermarked image could becorrected. The experimental results show that the algorithm isrobust to general signal processing and geometric attack such asrotation, scaling and translation.
Secure Part In Secure Part In Secure Part Result Embedding Attacking DetectingSignals Function E Function A Retrieval Function S General digital watermark life-cycle phases with embedding-, attacking-, and detection and retrieval functions
• The transformation for a square digital image is
(1) Use Haar wavelet, the images A be done 3 level discrete wavelettransform, to produce LL3, HL3, LH3, HH3 and so on ten sub-band.(2) Use ascending order for the intermediate region HL3, LH3 ofimage, get the sequence C, and note the location corresponding toorder (3) Arnold scrambling the watermark information, then obtainscrambling watermark information W.(4) Using the multiplicative rule, large absolute value coefficientwith C embed , then get the watermark information W.c′ i = ci(1 + alpha*wi)where the size of determines the intensity of the image frequencymodified by the watermark signal.
(5) According to corresponding sequence in step (2), the modifiedmedia frequency sequence c′i is assigned to corresponding location of original intermediatefrequency regions HL3, LH3.(6) Use the modified wavelet coefficients in step (5) by discreteinverse wavelet transform to get image embedded with thewatermark information.(7) Extract the two invariant centroid points tm, tn of the imagesembedded watermark information, and obtain the coordinates andcorresponding radius r1, r2 of the two points as geometricdistortion correction key for watermark detection.
(1) Use the methods described before as well as the key of geometric distortion of thewatermark image rotation, scaling, translation correction.(2) Use DWT for watermarking image A∗ with geometric distortion correction to get LL3, HL3,LH3, HH3 and so on ten sub-bands.(3) According to the corresponding position sequence and the embedded watermarksequence size, a embedding position of intermediate frequency regions HL3, LH3 inwatermarkimage is determined, and embedded watermark sequence c′ i is obtained.(4) Use the Eq. (4), to get scrambling watermark information W′.W′i = (c′ /ci − 1)/alpha(5) Use the saved Arnold scrambling key to do periodic transformation for W′, then get theextracted watermark image W∗.
• Extraction of the Invariant Centroid• Parameter Correction of Geometric Distortion• Image Rotation Correction Algorithm• Image Scaling Correction Algorithm• Image Translation Correction Algorithm
Wavelet Host Image LL3,LH3,HL3 transformAnother strategy use only high value Use LL3 butcoefficients to hide your coefficients low energy or LH3 and/or HL3 for higher energyAnother strategy use additive way ormultiplicative way
Wavelet Wavelet Wavelet Host Image transform transform transform Watermark Image LL3,LH3,HL3 Use LL3 but Arnold low energy scramblingWatermarked Wavelet +* Image inverse 3 levels