Abstract. We proposed a watermarking method using a concatenated code and evaluated the method on the basis of IHC evaluation criteria. The criteria include JPEG compression, clipping, scaling, and rotation as attacks. For the robustness of messages, we introduced concatenated code, since it has a high error corrective ability to decode messages against JPEG compression. When a region is cropped from a stego-image, the position of watermarks might be unclear. Therefore, markers or synchronization codes were embedded into the stego-image. Since scaling causes pixel loss, and rotation causes distortion, watermarks were embedded into minified images. Quantization index modulation was used for embedding and extracting the watermarks without the original images. As a result, our method was evaluated on the basis of highest image quality and could achieve an average peak signal-to-noise ratio of 36.250 dB. Moreover, our method was evaluated on the basis of highest tolerance and could achieve an average compression ratio of 2.633% without errors.

SUMMARYWe propose a digital image watermarking method satisfying information hiding criteria (IHC) for robustness against JPEG compression, cropping, scaling, and rotation. When a stego-image is cropped, the marking positions of watermarks are unclear. To detect the position in a cropped stego-image, a marker or synchronization code is embedded with the watermarks in a lattice pattern. Attacks by JPEG compression, scaling, and rotation cause errors in extracted watermarks. Against such errors, the same watermarks are repeatedly embedded in several areas. The number of errors in the extracted watermarks can be reduced by using a weighted majority voting (WMV) algorithm. To correct residual errors in output of the WMV algorithm, we use a high-performance error-correcting code: a low-density parity-check (LDPC) code constructed by progressive edgegrowth (PEG). In computer simulations using the IHC ver. 4 the proposed method could a bit error rate of 0, the average PSNR was 41.136 dB, and the computational time for synchronization recovery was less than 10 seconds. The proposed method can thus provide high image quality and fast synchronization recovery.

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