Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/94550
標題: A novel general multiple-base data embedding algorithm
作者: Wei-SungChen
Yi-KaiLiao
Yun-TeLin
Wang, C. M. 
關鍵字: Multiple-base;Data embedding;Payload;Image quality;Optimal base vector;Prediction
Project: Information Sciences, Volumes 358–359, 1 September 2016, Pages 164-190
摘要: 
This paper presents a general multiple-base (GMB) data embedding algorithm to conceal a serial secret bit stream equivalent to an M-ary secret digit in a pixel-cluster consisting of n pixels, where M is automatically determined by the initial input (n, F) given by the end user. Through the change of two parameters, n and M, the proposed algorithm offers a multiple-purpose message embedding style to produce a high quality embedded image or provide a large embedding payload. Inspired by a single base (SB) data embedding approach, this study first introduces a multiple-base (MB) scheme which adopts an n-tuple optimal base vector (OBV) to conceal a secret M-ary digit with minimal pixel distortion, where M is the product of all vector components in the OBV. This study extends the MB scheme to develop the GMB algorithm, which supports a serial secret bit stream as a secret message. Four binary to M-ary conversion schemes are introduced, allowing the GMB algorithm to carry an extra secret bit per pixel-cluster, offering a larger payload without increasing the pixel distortion caused by data embedding. The proposed algorithm is analyzed, and mathematical expressions are derived so that prior to a real message embedding, it is possible to predict the expected payloads and the corresponding image quality. Finally, we extend the GMB algorithm to support content-adaptive data embedding. To the best of the authors' knowledge, the proposed algorithm is the first multiple-purpose data embedding technique, providing greater flexibility and offering large payloads or high image quality. Experimental results demonstrate that the proposed scheme outperforms current state-of-the-art competitors.
URI: http://hdl.handle.net/11455/94550
DOI: 10.1016/j.ins.2016.03.045
Appears in Collections:資訊科學與工程學系所

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