Pixel Value Differencing Research Articles

CLSM: COUPLE LAYERED SECURITY MODEL A HIGH-CAPACITY DATA HIDING SCHEME USING WITH STEGANOGRAPHY

Cryptography and steganography are the two significant techniques used in secrecy of communications and in safe message transfer. In this study CLSM – Couple Layered Security Model is suggested which has a hybrid structure enhancing information security using features of cryptography and steganography. In CLSM system; the information which has been initially cryptographically encrypted is steganographically embedded in an image at the next step. The information is encrypted by means of a Text Keyword consisting of maximum 16 digits determined by the user in cryptography method. Similarly, the encrypted information is processed, during the embedding stage, using a 16 digit pin (I-PIN) which is determined again by the user. The carrier images utilized in the study have been determined as 24 bit/pixel colour. Utilization of images in .jpeg, .tiff, .pnp format has also been provided. The performance of the CLSM method has been evaluated according to the objective quality measurement criteria of PSNR-dB (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index). In the study, 12 different sized information between 1000 and 609,129 bits were embedded into images. Between 34.14 and 65.8 dB PSNR values and between 0.989 and 0.999 SSIM values were obtained. CLSM showed better results compared to Pixel Value Differencing (PVD) method, Simulated Annealing (SA) Algorithm and Mix column transform based on irreducible polynomial mathematics methods.

Recursive Information Hiding Scheme Through LSB, PVD Shift, and MPE

ABSTRACTIn this study, a new data embedding method is proposed to enhance the embedding payload by combining irreversible and reversible methods. The proposed method is based on pixel value difference (PVD), least significant bit (LSB) substitution, PVD shift, and modification of prediction error (MPE). A pixel block (2 × 1) is initially classified into lower and higher texture areas, and secret data are embedded through LSB and PVD, respectively. The pixel block is then recursively employed through PVD shift and MPE embedding methods to increase the payload. Experimental results demonstrate that the proposed method significantly increases the embedding capacity to 53,917 bits and maintains the visual image quality to 38 dB. The proposed method also provides robustness against regular/singular steganalysis.

基于像素差和索引函数的信息隐藏算法

在2 × 2像素块中，参考像素值由索引函数随机确定，然后计算参考像素与其周围的其它三个像素值的差，根据像素差所处的划分范围决定嵌入像素的秘密信息比特数。利用余函数嵌入秘密信息有效地减少载密图像的失真度，在提取信息的过程中，量化后的像素值能准确的提取秘密信息。改进了Jung和Yoo提出的基于索引函数信息隐藏算法，使算法更具有安全性。 In the 2 × 2 pixel block, reference pixel values was randomly determined by the index function, And we calculated the pixel value difference between reference pixel value and the other three pixel value around it. The number of secret data was embedded according to the range of pixel value difference. Using complementary function embedded secret information to effectively re-duce the load of image distortion degree. In the process of extracting information, the quantitative pixel values can accurately extract the secret information. Our proposed method improves the Jung and Yoo information hiding algorithm based on index function, and the proposed algorithm has more security.

Adaptive PVD Steganography Using Horizontal, Vertical, and Diagonal Edges in Six-Pixel Blocks

The traditional pixel value differencing (PVD) steganographical schemes are easily detected by pixel difference histogram (PDH) analysis. This problem could be addressed by adding two tricks: (i) utilizing horizontal, vertical, and diagonal edges and (ii) using adaptive quantization ranges. This paper presents an adaptive PVD technique using 6-pixel blocks. There are two variants. The proposed adaptive PVD for 2×3-pixel blocks is known as variant 1, and the proposed adaptive PVD for 3×2-pixel blocks is known as variant 2. For every block in variant 1, the four corner pixels are used to hide data bits using the middle column pixels for detecting the horizontal and diagonal edges. Similarly, for every block in variant 2, the four corner pixels are used to hide data bits using the middle row pixels for detecting the vertical and diagonal edges. The quantization ranges are adaptive and are calculated using the correlation of the two middle column/row pixels with the four corner pixels. The technique performs better as compared to the existing adaptive PVD techniques by possessing higher hiding capacity and lesser distortion. Furthermore, it has been proven that the PDH steganalysis and RS steganalysis cannot detect this proposed technique.

Block-Based Steganographic Algorithm Using Modulus Function and Pixel-Value Differencing

The main purpose in developing the steganographic algorithms lies in achieving most of the steganographic objectives which comprise the embedding capacity, imperceptibility, security, robustness and complexity. In this paper, we propose a high quality steganographic algorithm using new block structure which makes a good use of both modulus function and pixel-value differencing, namely, MF-PVD. We have made many experiments with various test images from several galleries, such as USC-SIPI and UWATERLOO-LINK. The performance of our proposed algorithm is verified using three different performance metrics which include peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and embedding capacity (EC). Experimental results and comparisons with six pertinent state-of-art algorithms are given to prove the validation and efficiency of the proposed algorithm.

Digital Watermarking Approach Based on Edge Based Sorted Pixel Value Difference (ESPVD)

Objectives: The major challenge in Imaging applications, particularly Digital Multimedia data transfer over the internet is data authentication with copyright protection to ensure ownership of identification. This paper aims to propose a new digital watermarking approach based on Edgebased sorted pixel value difference (ESPVD) to protect copyrights. Method: The hypothesis behind the proposed method is mainly composed of two phases: Watermark inserting phase, detection and extraction phase. In the inserting phase, first of all motif pattern approach is used to generate the mixed Image and then, identify the edge pixel locations using morphological edge (ME) operator to embed the watermark. Now, sorted pixel value difference method is used to insert the watermark. The watermark extraction phase also uses the same procedure which is stated earlier to retrieve the watermark image. To evaluate and match the ground truth images with the proposed watermarked images, peak signal to noise ratio (PSNR) and normalized cross correlation (NCC) are employed as quantitative measures. Findings: The proposed algorithm is tested with two logo images inserted over 30 different popular images and the outcomes indicates that the proposed approach is consistently performing well in terms of PSNR and NCC. Application/Improvements: The present approach provides high level of authentication, robustness, security and copyright protection against several attacks by using motif patterns while changing the order of pattern sequence in the formation of mixed image.

The Invention of Stretcher Trolley for Trauma Patient Radiography to Reduce Patient Transport Process

Objective: To design and invent a stretcher trolley for trauma patient radiography.Material and Method: The design of device size and maximum range of table movement in transverse plane was based on the height and width of a stretcher trolley at Buddhachinaraj Hospital and the average size of Thai people. The size and thickness of film cassette with grid were used to determine the size of film cassette tray. Radiation attenuation and load test of acrylic were done. The stretcher trolley design was evaluated by a professor in the Faculty of Engineering, Naresuan University. The device was made from stainless steel and acrylic. Image uniformity test was doneResults: The radiation attenuation of acrylic resembled the x-ray table top. The stretcher trolley size was 67x185x90 cm (widthxlengthxheight) and weight 55 kg. The floating top table could move in the transverse plane. The cassette tray size was 48x67 cm, the cassette tray could beapplied with the cassette of size 14x17 in and the cassette tray could move in the horizontal plane. The difference in mean pixel value was 0.1-0.4%. The device was evaluated by 7 radiological technologists at Buddhachinaraj Hospital. The results showed that the suitability of device was fair. The convenience was fair. The ability to decrease the number of workers was fair. The ability to decrease patient movement was good to excellent. The ability to decrease working time was fair.Conclusion: The overall of stretcher trolley evaluation results were fair. The stretcher trolley could probably be used for radiography.

Perancangan Aplikasi Steganografi Berbasis Android dengan Metode Pixel Value Differencing (PVD)

Simplicity in message exchanges on current technological developments. But on the other hand it brings new problems in terms of security of the message. One method used to overcome this problem is steganography. Steganography is a technique for hiding information on an image. The purpose of this study is to analyze the quality of the images used steganography to hide text messages. One of steganography techniques to be used in this research is Pixel Value Differencing (PVD). Quality of the image of will be declined. The application will be tested using .bmp, .png and .jpg images types and quality of steganography image is tested by calculating the Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) results of the insertion process of the message. The results of the study showed that the characteristics of the image greatly affect the capacity of the message and the quality of the image after embedded message. Images with different sizes and types tested using MSE get values between 1.62022 dB and 0.000116 dB and using PSNR get values between 46.0 dB and 90.0 dB. This shows that the qualities between the original images and the steganography images are not much different. It can be concluded that the quality of the image are slightly different

Perancangan Aplikasi Steganografi Berbasis Android dengan Metode Pixel Value Differencing (PVD)

Simplicity in message exchanges on current technological developments. But on the other hand it brings new problems in terms of security of the message. One method used to overcome this problem is steganography. Steganography is a technique for hiding information on an image. The purpose of this study is to analyze the quality of the images used steganography to hide text messages. One of steganography techniques to be used in this research is Pixel Value Differencing (PVD). Quality of the image of will be declined. The application will be tested using .bmp, .png and .jpg images types and quality of steganography image is tested by calculating the Mean Square Error (MSE) and Peak Signal to Noise Ratio (PSNR) results of the insertion process of the message. The results of the study showed that the characteristics of the image greatly affect the capacity of the message and the quality of the image after embedded message. Images with different sizes and types tested using MSE get values between 1.62022 dB and 0.000116 dB and using PSNR get values between 46.0 dB and 90.0 dB. This shows that the qualities between the original images and the steganography images are not much different. It can be concluded that the quality of the image are slightly different

Adaptive block‐based pixel value differencing steganography

AbstractSteganography is the science of hiding secure data in digital carriers such as images and videos. Pixel value differencing (PVD) steganography algorithms embed data into images depending on pixel neighborhood differences. We have proposed PVD scheme for embedding secure data into digital images. The image is divided into non‐overlapping 3 × 3 blocks. The block's median pixel is used as a reference for calculating pixel differences. The distance between the minimum and maximum differences are fine tuned for spreading the secure data on a wide range of image regions with high‐intensity fluctuations. The embedding procedure embeds secure data into the content regions with edges and intensity transitions. Texture images provide higher embedding size compared with regular images. The results showed that the proposed algorithm is successfully able to avoid smooth regions in the embedding process. In addition, the proposed algorithm shows better embedding quality compared with the state of the art PVD approaches especially with low‐embedding rates. Copyright © 2016 John Wiley & Sons, Ltd.

A data hiding scheme using parity-bit pixel value differencing and improved rightmost digit replacement

The fundamental objectives of image steganographic algorithm are to simultaneously achieve high payload, good visual imperceptibility, and security. This paper proposes a new data hiding method that increases visual quality and payload, as well as maintains steganographic security. The proposed scheme consists of two novel methods of parity-bit pixel value difference (PBPVD) and improved rightmost digit replacement (iRMDR). It partitions the cover image into two non-overlapping pixel blocks. The difference value between pixels in each block is used to determine the selection of PBPVD and iRMDR. According to the experimental results, the iRMDR method attains the best closest stego-pixels for good visual imperceptibility by resolving the region inconsistency problem in the existing RMDR method. In addition, the method reduces the risk of regular/singular (RS) detection attacks caused by its pixel-digit replacement nature. The PBPVD method exploits the pixel value difference (PVD) to adjust an extra parity bit that increases the payload while retaining the similar visual quality of PVD. Moreover, the iterative readjustment process of PBPVD minimizes the underflow/overflow problem. Overall, the proposed method achieves the steganographic objectives and reduces the detection artifacts against RS and pixel difference histogram analysis.

Digital Image Steganography based on Seven Way Pixel Value Differencing

Background/Objectives: This paper presents a steganographic method by calculating the pixel value differences along seven directions using nine-pixel blocks. Methods/Statistical Analysis: The centrally located pixel in nine-pixel block is used to form seven pairs with its seven neighboring pixels. The eighth neighbor pixel is used as the indicator to identify whether a block suffers with Fall Off Boundary Problem (FOBP) or not. Findings: Seven pixel value differences are calculated and based on these differences embedding is done. After embedding, the central pixel value is normalized to have a single value for all the seven pairs by suitable adjustments. After adjustments if any pixel value in the block falls off boundary, then the entire block is exempted from embedding. This is noted at the eighth neighbor pixel, so that it can also be exempted during extraction. Furthermore, to increase the capacity and peak signal-to-noise ratio, the nine-pixel blocks which suffer with FOBP are embedded using Wu and Tsai’s PVD method. The extraction process is very simple and the secret message can be extracted from the stego-image without using the original cover image. Application/ Improvements: Without compromising the security and imperceptibility the hiding capacity is almost 50% increased as compared to Wu and Tsai’s Pixel Value Differencing (PVD) method.

A New Pixel Value Based Steganography Method for Data Security

Objective: This paper proposes a new data hiding method to improve the security for data hiding. Method: This method first maps the cover image into a 1D pixel sequence and then divides it into non-overlapping blocks containing two successive pixels for embedding. It then calculates the difference between the two pixel values for the blocks. It then compares the difference with a reference table. The reference table is referred in every iteration for the comparison of pixel value differences and the range it falls in. This leads to the calculation of the number of bits which can be embedded in that particular block. Findings: The embedded pixels are then modified and their difference is calculated and compared with the range table. If the difference falls in same range, the embedded pixels are used as modified pixels, and if the difference does not fall in the same range, the pixels are modified such that the difference falls in the appropriate range. Extraction of the data is done in the same way to get the covert data. Application/Improvements: Experimental results show that this method enhances embedding rate while preserving the stego image quality

A perceptually optimized mapping technique for display images

AbstractLiquid crystal displays (LCDs) are often viewed in the energy‐saving mode or under high ambient illumination. However, both these conditions compress the tonal dynamic range of the display device, resulting in undesirable visual perception effects. In this paper, we propose a local algorithm for improving the display image quality under either of these conditions. The proposed algorithm is based on a tone mapping technique, and it reproduces the image appearance to almost its original quality with a lower dynamic range. We also develop a more accurate definition of the image distortion, which takes into account the difference in pixel values to reduce the distortion significantly. By minimizing the differences in contrast and pixel intensity between the input and output images, the algorithm preserves the contrast while simultaneously providing brightness compensation. Simulation results show that the proposed algorithm can effectively maintain image quality while enabling power savings of 30%–50%.

Optimum wavelength of ultraviolet rays in gafchromic EBT2

Introduction Gafchromic films have been used for the measurement of X-ray dose in diagnostic radiology. UV-A ray can be used as a substitute for X-rays in the double exposure technique to compensate for nonuniformity error of Gafchromic EBT2. Purpose When using a UV-A light emitting diode (UV-A LED), it is necessary to determine the optimal UV-A wavelength to react with the active layer of Gafchromic EBT2. Therefore, changes in the optical density of Gafchromic EBT2 induced by UV-A were investigated by irradiating it at various wavelengths with UV-A LED. Materials and methods At first, Gafchromic EBT2 was pre-irradiated using a uniform UV-A by using fluorescent lamp for 60 min from a distance of 72 cm to reduce nonuniformity error. Second, Gafchromic EBT2 was irradiated for 60 min from a distance of 5.3 cm using a UV-A LED at a wavelength of 353–410 nm. The maximum, minimum, and mean ± standard deviation of pixel values of the subtraction images were evaluated using 0.5 inch of circular region of interest (ROI). The most sensitive wavelength of UV ray was decided. In addition, UV strength was measured in each UV-A LED. Results When a UV-A LED wavelength of 375 nm was used, the mean ± SD of pixel value of Gafchromic EBT2 was indicated highly pixel value. It was 8915.25 ± 608.86. A 375 nm wavelength UV-A was most effective and sensitive for Gafchromic EBT2. Conclusion The 375 nm wavelength of UV-A is available as a substitute for X-rays in the double exposure technique. Disclosure Research supported by JSPS KAKENHI Grant Number 26460740 .

High-capacity reversible data hiding method using block expansion in digital images

A reversible data hiding method allows recovery of the cover image after the secret data have been extracted. In this paper, a novel reversible data hiding method is proposed using neighboring interpolation and pixel-value differencing on block expansion. A consecutive embedding technique for a sub-block is proposed to maintain a higher embedding capacity, and a neighboring pixel-value referencing is also proposed to maintain a good visual quality in stego-images. The results of experiment demonstrate that the proposed method has higher capacity and maintains a better image quality than previous reversible data hiding methods.

Semivariogram Analysis of Bone Images Implemented on FPGA Architectures.

Osteoporotic fractures are a major concern for the healthcare of elderly and female populations. Early diagnosis of patients with a high risk of osteoporotic fractures can be enhanced by introducing second-order statistical analysis of bone image data using techniques such as variogram analysis. Such analysis is computationally intensive thereby creating an impediment for introduction into imaging machines found in common clinical settings. This paper investigates the fast implementation of the semivariogram algorithm, which has been proven to be effective in modeling bone strength, and should be of interest to readers in the areas of computer-aided diagnosis and quantitative image analysis. The semivariogram is a statistical measure of the spatial distribution of data, and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas. Recently, applications in the area of medical imaging have been investigated, resulting in the need for efficient real time implementation of the algorithm. A semi-variance, γ(h), is defined as the half of the expected squared differences of pixel values between any two data locations with a lag distance of h. Due to the need to examine each pair of pixels in the image or sub-image being processed, the base algorithm complexity for an image window with n pixels is O (n2) Field Programmable Gate Arrays (FPGAs) are an attractive solution for such demanding applications due to their parallel processing capability. FPGAs also tend to operate at relatively modest clock rates measured in a few hundreds of megahertz. This paper presents a technique for the fast computation of the semivariogram using two custom FPGA architectures. A modular architecture approach is chosen to allow for replication of processing units. This allows for high throughput due to concurrent processing of pixel pairs. The current implementation is focused on isotropic semivariogram computations only. The algorithm is benchmarked using VHDL on a Xilinx XUPV5-LX110T development Kit, which utilizes the Virtex5 FPGA. Medical image data from DXA scans are utilized for the experiments. Implementation results show that a significant advantage in computational speed is attained by the architectures with respect to implementation on a personal computer with an Intel i7 multi-core processor.

A Review on LSB Substitution and PVD Based Image Steganography Techniques

<p>There has been a tremendous growth in Information and Communication technologies during the last decade. Internet has become the dominant media for data communication. But the secrecy of the data is to be taken care. Steganography is a technique for achieving secrecy for the data communicated in Internet. This paper presents a review of the steganography techniques based on least significant bit (LSB) substitution and pixel value differencing (PVD). The various techniques proposed in the literature are discussed and possible comparison is done along with their respective merits. The comparison parameters considered are, (i) hiding capacity, (ii) distortion measure, (iii) security, and (iv) computational complexity.</p>

Chaotic Pixel Value Differencing

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.

A Steganographic Method Combining LSB Substitution and PVD in a Block

In the recent past some steganography techniques by combining least significant bit (LSB) substitution and pixel value differencing (PVD) have been proposed to improve upon the hiding capacity and peak signal-to-noise ratio (PSNR). This paper proposes a steganographic technique by using both LSB substitution and PVD with in a block. The image is partitioned into 2×2 pixel blocks in a non-overlapping fashion. For every 2×2 pixel block the upper-left pixel is embedded with k-bits of data using LSB substitution. Then the new value of this pixel is used to calculate three pixel value differences with the upper-right, bottom-left, and bottom-right pixels of the block. Then data bits are hidden using these three difference values in three directions. Both horizontal and vertical edges are considered. There are two variants proposed by using two different range tables. In the first variant (Type 1) the PSNR is improved and in the second variant (Type 2) both PSNR and hiding capacity are improved.