• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.76-82
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• 2010

Reversible watermarking hides some information in a digital image in such a way that an authorized party could decode the hidden information and also restore the image to its original state. In this paper, a high capacity reversible watermarking method using histogram shifting is proposed. In order to increase embedding capacity, the proposed method divides the image into $2{\times}2$ blocks and uses a paring(horizontal, vertical, diagonal) inside each block, then finds a maximum embedding bin which has the most frequent difference values among the parings. Also, the proposed method removes the overflow and underflow by using location map which including the maximum embedding bin and increases the embedding capacity by embedding iteratively. The experimental results show that the proposed method provides a high embedding capacity and good visual quality compared with the conventional reversible watermarking methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.3
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• pp.794-814
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• 2012

We propose a novel method for improving Wi-Fi positioning accuracy while reducing the energy consumption of mobile devices. Our method presents three contributions. First, we jointly and intelligently select the optimal subset of access points for positioning via maximum mutual information criterion. Second, we further propose local discriminant embedding algorithm for nonlinear discriminative feature extraction, a process that cannot be effectively handled by existing linear techniques. Third, to reduce complexity and make input signal space more compact, we incorporate clustering analysis to localize the positioning model. Experiments in realistic environments demonstrate that the proposed method can lower energy consumption while achieving higher accuracy compared with previous methods. The improvement can be attributed to the capability of our method to extract the most discriminative features for positioning as well as require smaller computation cost and shorter sensing time.