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Secret image sharing, a technology of secret communication, transmits secret images by distributing camouflage images (shares) to a group of participants, where each camouflage image contains a part of secret images. Secret images can be reconstructed under the conditions of a sufficient number of shares gathered and processed using a revealing algorithm. In 2009, Tsai et al. proposed a novel secret image sharing scheme using exclusive-or operators, principal component analysis (PCA), and feed-forward (FF) neural networks. The performance of their scheme was better than that of more recently proposed schemes, however, PCA and FF neural networks are time-consuming technologies and secret images cannot be completely restored. In this paper, we proposed an improved secret image sharing scheme to solve these problems. Experimental results show that camouflage image qualities of the proposed method were 54.26 dB on average, which is higher than that of Tsai et al.,'s scheme. Meanwhile, hiding capacity of the proposed mechanism was 1.125 times larger than that of Tsai et al.'s scheme. Additionally, results also contribute to the literature by illustrating that original secret images can be reversed.
Date of Conference: 14-16 Oct. 2011