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Selective bit embedding scheme for robust blind color image watermarking


Huynh-The, T and Hua, C-H and Anh Tu, N and Hur, T and Bang, J and Kim, D and Amin, MB and Kang, BH and Seung, H and Lee, S, Selective bit embedding scheme for robust blind color image watermarking, Information Sciences, 426 pp. 1-18. ISSN 0020-0255 (2018) [Refereed Article]

Copyright Statement

Copyright 2017 Elsevier Inc.

DOI: doi:10.1016/j.ins.2017.10.016


In this paper, we propose a novel robust blind color image watermarking method, namely SMLE, that allows to embed a gray-scale image as watermark into a host color image in the wavelet domain. After decomposing the gray-scale watermark to component binary images in digits ordering from least significant bit (LSB) to most significant bit (MSB), the retrieved binary bits are then embedded into wavelet blocks of two optimal color channels by using an efficient quantization technique, where the wavelet coefficient difference in each block is quantized to either two pre-defined thresholds for corresponding 0-bits and 1-bits. To optimize the watermark imperceptibility, we equally split the coefficient modified quantity on two middle-frequency sub-bands instead of only one as in existing approaches. The improvement of embedding rule increases approximately 3 dB of watermarked image quality. An adequate trade-off between robustness and imperceptibility is controlled by a factor representing the embedding strength. As for extraction process, we exploit 2D Otsu algorithm for higher accuracy of watermark detection than that of 1D Otsu. Experimental results prove the robustness of our SMLE watermarking model against common image processing operations along with its efficient retention of the imperceptibility of the watermark in the host image. Compared to state-of-the-art methods, our approach outperforms in most of robustness tests at a same high payload capacity.

Item Details

Item Type:Refereed Article
Keywords:color image watermarking, discrete wavelet transform, quantization technique
Research Division:Information and Computing Sciences
Research Group:Data management and data science
Research Field:Information retrieval and web search
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Amin, MB (Dr Muhammad Bilal Amin)
UTAS Author:Kang, BH (Professor Byeong Kang)
ID Code:121878
Year Published:2018
Web of Science® Times Cited:52
Deposited By:Information and Communication Technology
Deposited On:2017-10-19
Last Modified:2021-03-23

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