A High Capacity Secured Image Steganography Method with Five Pixel Pair Differencing and LSB Substitution

Gulve, Avinash K.; Joshi, Madhuri S.

doi:10.5815/ijigsp.2015.05.08

Cited by 19 publications

(11 citation statements)

References 16 publications

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“…x stands for the standard deviation of pixel values of original image, 2 y stands for the standard deviation of pixel values of stego image, and xy is the covariance between original image and stego image. Equations (17), (18), (19), (20), and (21) are used to calculate these values. Table 3 notes the results of seven-way PVD [18] which is an extension of Wu and Tsai's [1] technique.…”

Section: Resultsmentioning

confidence: 99%

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Digital Image Steganography Using Eight-Directional PVD against RS Analysis and PDH Analysis

Swain

2018

Advances in Multimedia

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The least significant bit (LSB) substitution techniques are detected by RS analysis and the traditional pixel value differencing (PVD) approaches are detected by pixel difference histogram (PDH) analysis. The PVD steganography can escape from PDH analysis by using the edges in multiple directions. This paper proposes a steganography technique by exploiting the edges in eight directions and also using LSB substitution to resist from both RS analysis and PDH analysis. For every 3×3 pixel block the central pixel is embedded with 3 or 4 bits of data by modified LSB substitution technique. Then this new value of the central pixel is utilized to calculate eight difference values with eight neighboring pixels. These eight difference values are used to hide the data. There are two types with regard to two different range tables. Type 1 uses 3 bit modified LSB substitution and range table 1. Type 2 uses 4 bit modified LSB substitution and range table 2. Type 1 and type 2 are also known as variant 1 and variant 2, respectively. Type 1 possesses higher PSNR and type 2 possesses higher hiding capacity.

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Section: Resultsmentioning

confidence: 99%

“…A PVD steganography technique which is an extension of Wu and Tsai's PVD approach should be verified by PDH analysis. Gulve and Joshi [20] used PVD with LSB in six-pixel blocks to achieve higher embedding capacity. In one of the six pixels LSB substitution was applied.…”

Section: Introductionmentioning

confidence: 99%

Digital Image Steganography Using Eight-Directional PVD against RS Analysis and PDH Analysis

Swain

2018

Advances in Multimedia

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“…Gulve et al [16] proposed a PVD method utilizing 5 pixel blocks and LSB substitution. An average value is calculated and the pixel block is modified using the average value of the number of bits that can be embedded in the block.…”

Section: Weiqi Luo Et Al [6]mentioning

confidence: 99%

Chaotic Pixel Value Differencing

Pun¹,

Juneja

2016

IJIGSP

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Pixel Value Differencing (PVD) is a spatial steganography technique that is area sensitive and considers complete visual invisibility while data hiding. While Least Significant Bit Approach (LSB) still remains the most popular technique and is simplest in approach its simplicity makes it vulnerable against steganalysis. Our proposed technique is an enhancement over traditional Pixel Value Differencing. We have added a layer of security using chaotic encryption approaches. Also some PVD based hybrid techniques are compared and analyzed to draw conclusions on the basis of various statistical measures.

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“…These two drawbacks are addressed in [22] using modified LSB substitution and PVD in 2×3 and 3×3 pixel blocks. Gulve and Joshi [7] used five pair differencing with LSB substitution to achieve higher embedding capacity. The traditional edge detection techniques can be used to identify the edges and accordingly embedding capacity in a block can be varied.…”

Section: Introductionmentioning

confidence: 99%

A data hiding technique by mixing MFPVD and LSB substitution in a pixel

Swain

2018

ITC

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Pixel difference range mismatch at sender and receiver is a major problem with pixel value differencing (PVD) steganography techniques. This paper proposes a new steganography technique combining modulus function PVD (MFPVD) and least significant bit (LSB) substitution to address the range mismatch problem. It uses 2×3 size pixel blocks to utilize the edges in five directions. The two LSBs of all the pixels of the block form the lower bit plane block. It is also known as remainder block. Similarly, the six most significant bits (MSBs) of all the pixels of the block form the higher bit plane block. It is also known as quotient block. The quotient block is formed by applying quotient division on all the pixels of the pixel block. Similarly, the remainder block is formed by applying remainder division on all the pixels of the pixel block. MFPVD is applied on the quotient block. The central quotient in the quotient block is considered as reference value and five difference values with five neighboring quotients are calculated. Based on the average of these five difference values, the hiding capacity in all the five directions is decided. The central remainder value in the remainder block acts as an indicator to represent the number of bits hidden in each of these five quotients, so that data extraction can be done successfully. In remaining five remainders LSB substitution is applied. The experimental results prove that there are no step effects in pixel difference histograms of stego-images. It means that the pixel difference histogram (PDH) analysis cannot detect this proposed technique. Further, it is also justified that the proposed technique achieves higher hiding capacity as compared to the existing techniques without compromising the peak signal-to-noise ratio (PSNR).

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A High Capacity Secured Image Steganography Method with Five Pixel Pair Differencing and LSB Substitution

Cited by 19 publications

References 16 publications

Digital Image Steganography Using Eight-Directional PVD against RS Analysis and PDH Analysis

Digital Image Steganography Using Eight-Directional PVD against RS Analysis and PDH Analysis

Chaotic Pixel Value Differencing

A data hiding technique by mixing MFPVD and LSB substitution in a pixel

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