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Bee Ee Khoo

Researcher at Universiti Sains Malaysia

Publications -  60
Citations -  1762

Bee Ee Khoo is an academic researcher from Universiti Sains Malaysia. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 18, co-authored 56 publications receiving 1465 citations. Previous affiliations of Bee Ee Khoo include Universiti Sains Malaysia Engineering Campus.

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Robust blind image watermarking scheme based on Redundant Discrete Wavelet Transform and Singular Value Decomposition

TL;DR: A new image watermarking scheme based on the Redundant Discrete Wavelet Transform (RDWT) and the Singular Value Decomposition (SVD) that showed a high level of robustness not only against the image processing attacks but also against the geometrical attacks which are considered as difficult attacks to resist.
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A new robust and secure digital image watermarking scheme based on the integer wavelet transform and singular value decomposition

TL;DR: A challenge due to the false positive problem which may be faced by most of SVD-based watermarking schemes has been solved in this work by adopting a digital signature into the watermarked image.
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Block-based discrete wavelet transform-singular value decomposition image watermarking scheme using human visual system characteristics

TL;DR: This study presents a robust block-based image watermarking scheme based on the singular value decomposition (SVD) and human visual system in the discrete wavelet transform (DWT) domain that outperformed several previous schemes in terms of imperceptibility and robustness.
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Passive detection of copy-move forgery in digital images: state-of-the-art.

TL;DR: The current state-of-the-art of passive copy-move forgery detection methods are described and the key current issues in developing a robust copy- move forgery detector are identified and the trends of tackling those issues are addressed.
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Authentication and Data Hiding Using a Hybrid ROI-Based Watermarking Scheme for DICOM Images

TL;DR: The experimental results show the ability of hiding patient’s data with a very good visual quality, while ROI, the most important area for diagnosis, is retrieved exactly at the receiver side, and the scheme shows some robustness against certain levels of salt and pepper and cropping noise.