Shiau-Rung Tsui

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This study presents a new steganographic method that embeds secret data into a cover digital image using VQ encoding. The core concept of the proposed method uses the gradient adjacent prediction (GAP) algorithm, which enhances prediction accuracy of neighboring blocks in SMVQ encoding. To embed secret data into the cover image, the proposed method utilizes(More)
Up to now, the VQ-based steganographic methods are all lossy approaches since they cannot recover the cover images. Prior studies on reversibility in VQ-based steganography only show the ability to recover the quantized cover images. This paper presents a new two-phase steganographic protocol of genuine VQ-based reversibility, referring to the ability of(More)
Steganography conceals the secret data into cover media to avoid detection, such that no one suspects the existence of the embedded secret data. The existing VQ-based and SMVQ-based steganographic methods can only provide the same level of visual quality of what the VQ/SMVQ compression method can offer. In this study, we present the idea of using secret(More)
Many traditional clustering algorithms have the scalability problem while dealing with large data sets. One common strategy to handle the problem is to parallelize the algorithms and execute them along with the input data on high-performance computers. However, many graph-based clustering algorithms are hard to be parallelized since they need to calculate(More)
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