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Selective bit embedding scheme for robust blind color image watermarking

journal contribution
posted on 2023-05-19, 12:48 authored by Huynh-The, T, Hua, C-H, Anh Tu, N, Hur, T, Bang, J, Kim, D, Muhammad Bilal AminMuhammad Bilal Amin, Byeong KangByeong Kang, Seung, H, Lee, S
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.

History

Publication title

Information Sciences

Volume

426

Pagination

1-18

ISSN

0020-0255

Department/School

School of Information and Communication Technology

Publisher

Elsevier Science Inc

Place of publication

360 Park Ave South, New York, USA, Ny, 10010-1710

Rights statement

Copyright 2017 Elsevier Inc.

Repository Status

  • Restricted

Socio-economic Objectives

Information systems, technologies and services not elsewhere classified

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