Andy Yuanfang Guo

Bio: Andy Yuanfang Guo is an academic researcher from Hong Kong University of Science and Technology. The author has contributed to research in topics: Distortion & Peak signal-to-noise ratio. The author has an hindex of 1, co-authored 1 publications receiving 5 citations.

Adaptive Predictor Structure Based Interpolation for Reversible Data Hiding

Abstract: In this paper, we present an additive prediction error expansion (PEE) based reversible data hiding scheme that gives overall low distortion and relatively high embedding capacity. Recently reported interpolation based PEE method uses fixed order predictor that fails to exploit the correlation between the neighborhood pixels and the unknown pixel (to be interpolated). We observed that embedding capacity and distortion of PEE based algorithm depends on the prediction accuracy of the predictor. In view of this observation, we propose an interpolation based method that predicts pixels using predictors of different structure and order. Moreover, we use only original pixels for interpolation. Experimental results demonstrate that the proposed algorithm outperforms the state-of-the-art algorithms both in terms of embedding capacity and Peak Signal to Noise Ratio.

Reversible data hiding based on prediction error expansion using adjacent pixels

Abstract: Reversible watermarking is a method of hiding the watermark in digital media in such a way that visually its effect is almost negligible and after extracting the watermark, digital media can be restored to its original form bit-by-bit. Reversible watermarking has applications in the fields that are very sensitive towards security such as defense, medical, legal matters, artwork, and so on. This paper investigates the concept of prediction error expansion in developing a fragile reversible data hiding technique for digital images. The fact that the adjacent pixels are highly correlated is exploited by the proposed technique for providing high embedding capacity along with good visual quality. The proposed technique utilizes odd columns to predict the values of even columns and embeds the watermark into even columns. Compressed location map is used to handle the overflow and underflow problem. Experimental results using various standard test images and a comparison with recent existing techniques show that the proposed technique provides high embedding capacity with better visual quality. Higher peak signal-to-noise ratio values indicate the effectiveness of the proposed technique. Copyright © 2016 John Wiley & Sons, Ltd.

A Modulo Function-Based Robust Asymmetric Variable Data Hiding Using DCT

Abstract: This work presents a new asymmetric data hiding technique that hides a variable number of secret message bits in the discrete cosine transform (DCT) coefficients of a cover image using a modular distance technique. Prior to data hiding, the proposed framework transforms a cover image from a spatial domain to various frequency coefficients using DCT. The DCT coefficients are arranged in two groups: one with low-frequency coefficient, and the other with the medium and high-frequency coefficients. The medium and higher frequency coefficients are processed for variable data hiding asymmetrically. The proposed technique hides variable sets of secret information bits in different coefficients. The variation in hidden secret information is maintained using a key developed based on the modulo of distance of a coefficient from the reference point. The same key is also used to retrieve the confidential information at the receiver ends. The results reveal that the presented framework does not create any visually significant distortion, and thus the hidden information does not attract the human visual system (HVS). The technique also results in high data hiding efficiency.

Adaptive interpolation and segmentation based reversible image watermarking

Abstract: Reversible image watermarking schemes are used to protect ownership and copyrights of digital images. This paper proposes a novel reversible image watermarking scheme based on adaptive image interpolation, segmentation and additive prediction error expansion (PEE). Proposed interpolation comprises of weighted average of neighboring pixels by allocating higher and lower weights to less and more distant neighboring pixel values respectively. The proposed adaptive image interpolation focuses on detection of edges thus minimizing artifacts imposed by interpolation. The idea of embedding varying amount of watermark bits in different image segments has been explored. Simple linear iterative clustering (SLIC) based image segmentation is performed to separate very sharp, sharp, smooth and very smooth regions in image. Higher number of watermark bits are embedded in sharp regions by using additive prediction error expansion embedding technique. Simulations of proposed and existing techniques were performed on different images and compared using embedding capacity (EC), peak signal to noise ratio (PSNR), computational efficiency, image quality, mean square error (MSE), normalized cross correlation (NCC) and structural similarity index (SSIM). The experimental results show that proposed scheme achieves better results in terms of EC, PSNR, computational efficiency, image quality, MSE, NCC and SSIM as compared to existing techniques.

Adjacent Pixel Values Blocking and Prediction Error Expansion Based High Fidelity Reversible Data Hiding Scheme

Abstract: This paper presents a novel reversible data hiding method based on pixel value blocking and prediction-error expansion. A cover image is divided into non-overlapping sub-blocks of two pixels. Watermark bits are embedded in two phases. In Phase-I, for each sub-block, second pixel value is predicted by the first pixel value and depending on prediction-error within a threshold limit secret bit is embedded into second pixel. Also secret bit is embedded into first pixel just by adjusting the location map without effecting into the pixel value. Then another compressed location map value is used to indicate overflow/underflow or the sub-blocks are outer threshold limit. Again in Phase-II, for each sub-block, first pixel value is predicted by the second pixel value and by depending on prediction-error within a threshold limit secret bit is embedded into first pixel. Also secret bit is embedded into second pixel by adjusting location map without effecting into the pixel value and another compressed location map value is used to indicate overflow/underflow or the sub-blocks of outer threshold limit. All secret bits can be recovered and restored the cover image completely from watermarked image. Experimental result of comparison of this scheme with recent existing scheme using different standard images shows that the embedding capacity with visual quality and PSNR values of the proposed scheme is larger than the existing scheme.