A novel multi-group exploiting modification direction method based on switch map

Wang, Xingtian; Chang, Chin‐Chen; Lin, Chia Feng; Li, Mingchu

doi:10.1016/j.sigpro.2011.12.013

Cited by 15 publications

(3 citation statements)

References 26 publications

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“…This CS-based ME is just the EMD embedding method [16] and the grid coloring steganography [51]. (21) and A composed of the three arithmetic progressions. These CSs are based on our previous work [13].…”

Section: Examples Of Cs-based Mementioning

confidence: 99%

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Matrix embedding in finite abelian group

Li¹,

Cai²,

Zhang³

et al. 2015

Signal Processing

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Section: Examples Of Cs-based Mementioning

confidence: 99%

“…In another work, Zhang and Wang proposed a new steganographic method based on exploiting modification direction (EMD) [16]. The EMD method and its related works such as [17][18][19][20][21][22][23] are also designed to reduce the embedding distortion and enhance the embedding efficiency.…”

Section: Introductionmentioning

confidence: 99%

Matrix embedding in finite abelian group

Li¹,

Cai²,

Zhang³

et al. 2015

Signal Processing

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“…Zhang and Wang introduced an exploiting modification direction (EMD) for data hiding, where n number of pixels were utilized to hide the (2n + 1) base secret digits [22]. Furthermore, different EMD-based methods [23][24][25][26] were proposed to improve the visual quality but suffered from low payload.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Data Hiding Scheme Using Right-Most Digit Replacement and Adaptive Least Significant Bit for Digital Images

et al. 2016

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Abstract:The goal of image steganographic methods considers three main key issues: high embedding capacity, good visual symmetry/quality, and security. In this paper, a hybrid data hiding method combining the right-most digit replacement (RMDR) with an adaptive least significant bit (ALSB) is proposed to provide not only high embedding capacity but also maintain a good visual symmetry. The cover-image is divided into lower texture (symmetry patterns) and higher texture (asymmetry patterns) areas and these textures determine the selection of RMDR and ALSB methods, respectively, according to pixel symmetry. This paper has three major contributions. First, the proposed hybrid method enhanced the embedding capacity due to efficient ALSB utilization in the higher texture areas of cover images. Second, the proposed hybrid method maintains the high visual quality because RMDR has the closest selection process to generate the symmetry between stego and cover pixels. Finally, the proposed hybrid method is secure against statistical regular or singular (RS) steganalysis and pixel difference histogram steganalysis because RMDR is capable of evading the risk of RS detection attacks due to pixel digits replacement instead of bits. Extensive experimental tests (over 1500+ cover images) are conducted with recent least significant bit (LSB)-based hybrid methods and it is demonstrated that the proposed hybrid method has a high embedding capacity (800,019 bits) while maintaining good visual symmetry (39.00% peak signal-to-noise ratio (PSNR)).

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Sensor-based risk perception ability network design for drivers in snow and ice environmental freeway: a deep learning and rough sets approach

Zhao

et al. 2017

Soft Comput

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A novel multi-group exploiting modification direction method based on switch map

Cited by 15 publications

References 26 publications

Matrix embedding in finite abelian group

Matrix embedding in finite abelian group

Hybrid Data Hiding Scheme Using Right-Most Digit Replacement and Adaptive Least Significant Bit for Digital Images

Sensor-based risk perception ability network design for drivers in snow and ice environmental freeway: a deep learning and rough sets approach

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