Abstract

The main requirements of efficient steganographic systems are transparency, robustness and security. In this work, the proposed system is designed to achieve these requirements, as follows: to increase the transparency and robustness, the proposed system uses the transform domain technique, in this case the wavelet domain technique to embed the color secret image into the color cover image. To achieve high security, chaotic systems are used to accomplish the following two purposes: firstly to scramble the secret color image before hiding it into the color cover image, secondly to randomly select the embedding positions in the cover image. Three chaotic systems with many combinations are used for the scrambling and the embedding process. Experimental results including Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Correlation, Signal to Noise Ratio (SNR) and embedding capacity demonstrate that the proposed system has good performance as compared with other existing methods without attack and under different types of attacks such as filtering and noise attacks. Simulation results show that the combination of chaotic systems providing the best performance include the use of Logistic and Henon maps for the embedding process and Arnold's cat map for the encryption process. The MSE, PSNR, correlation, SNR and embedding capacity obtained in this case reach up to 0.0010, 78.1dB, 0.9999, 67.2dB and 0.39% respectively when the secret image is Airplane with 32×32 pixels and the cover image is Girl with 512×512 pixels. For the extracted secret image, the chaotic system set that provides the best performance includes the use of Arnold's cat map for the encryption process. The MSE, PSNR, correlation and SNR obtained in this case reach up to 0.0846, 58.9dB, 1 and 56.1dB respectively. As compared with other methods, the proposed method achieves gains without any attack of 8.2dB for the stego image and 32.4dB for the extracted secret image in PSNR when the secret image is Airplane with 256×256 pixels and the cover image is Girl with 512×512 pixels.

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