A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

2021 ◽  
pp. 1-11
Author(s):  
Kusan Biswas

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems  (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.

Symmetry ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 1360
Author(s):  
Kusan Biswas

Recently, the H.265/HEVC video coding has been standardised by the ITU-T VCEG and the ISO/IEC MPEG. The improvements in H.265/HEVC video coding structure (CTU, motion compensation, inter- and intra-prediction, etc.) open up new possibilities to realise better data hiding algorithms in terms of capacity and robustness. In this paper, we propose a new data hiding method for HEVC videos. The proposed method embeds data in 4 × 4 and some selected larger transform units. As theory of Human Visual System suggests that human vision is less sensitive to change in uneven areas, relatively coarser blocks among the 8 × 8 and 16 × 16 blocks are selected as embedding destinations based on the proposed Jensen-Shannon Divergence and Second Moment (JSD-SM) block coarseness measure. In addition, the SME(1,3,7) embedding technique is able to embed three bits of message by modifying only one coefficient and therefore exhibits superior distortion performance. Furthermore, to achieve better robustness against re-compression attacks, BCH and Turbo error correcting codes have been used. Comparative studies of BCH and Turbo codes show the effectiveness of Turbo codes. Experimental results show that the proposed method achieves greater payload capacity and robustness than many existing state-of-the-art techniques without compromising on the visual quality.


Informatica ◽  
2004 ◽  
Vol 15 (1) ◽  
pp. 127-142 ◽  
Author(s):  
Hsien‐Wen Tseng ◽  
Chin‐Chen Chang

2016 ◽  
Vol 2016 (21) ◽  
pp. 1-7
Author(s):  
V. Itier ◽  
A.G. Bors ◽  
W. Puech ◽  
J.-P. Pedeboy

Optik ◽  
2016 ◽  
Vol 127 (4) ◽  
pp. 1762-1769 ◽  
Author(s):  
Wen-Chung Kuo ◽  
Shao-Hung Kuo ◽  
Chun-Cheng Wang ◽  
Lih-Chyau Wuu

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 145
Author(s):  
Jung-Yao Yeh ◽  
Chih-Cheng Chen ◽  
Po-Liang Liu ◽  
Ying-Hsuan Huang

Data hiding is the art of embedding data into a cover image without any perceptual distortion of the cover image. Moreover, data hiding is a very crucial research topic in information security because it can be used for various applications. In this study, we proposed a high-capacity data-hiding scheme for absolute moment block truncation coding (AMBTC) decompressed images. We statistically analyzed the composition of the secret data string and developed a unique encoding and decoding dictionary search for adjusting pixel values. The dictionary was used in the embedding and extraction stages. The dictionary provides high data-hiding capacity because the secret data was compressed using dictionary-based coding. The experimental results of this study reveal that the proposed scheme is better than the existing schemes, with respect to the data-hiding capacity and visual quality.


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