Pixel Value Differencing Research Articles

Pseudo CT Image Synthesis and Bone Segmentation From MR Images Using Adversarial Networks With Residual Blocks for MR-Based Attenuation Correction of Brain PET Data

For photon attenuation correction, current positron emission tomography systems combined with magnetic resonance imaging (PET/MR) imaging systems typically use methods based on MR image segmentation with subsequent assignment of empirical attenuation coefficients in PET image reconstruction. Delineation of bone in MR images has been challenging, especially in the head and neck areas, due to the difficulty of separating bone from air. In this article, we study deep learning techniques that assist the MR-based attenuation correction (MRAC) process for PET/MR systems, with focus on the brain region. We use a generative adversarial network (GAN) with residual blocks in a conditional setting for this task. We studied the performance of the designed network on image translation and segmentation tasks, which are essential for MRAC. For both tasks, the network generates pseudo CT images that resemble real CT images with normalized pixel value difference of around 5% and structural similarity (SSIM) index of around 0.8.

Steganographic on Pixel Value Differencing in Iris Biometric

Biometric technology was widely used in more than decade ago and become convenient since human uses their own physical traits and behaviour rather than using keys and IDs to enter the systems. As the arising of biometric use, the issues of security in biometric data and the system points exist. The security and integrity of biometric data presents a major challenge as many benefits of biometric may quite easily become impediment. Every point of vulnerability in the biometrics system consist of specific defend techniques to prevent the misidentification of the real person. In biometric security system, techniques such as watermarking and steganography have been used in attempt to improve security of biometric data. Steganography has become one of the technique used in defending data and system in biometric security The techniques of steganography is divided into two embedding methods which are the least significant bits (LBS) and pixel value differencing (PVD). LBS is most popular techniques for data hiding field and data embedding since it embeds the fixed-length secret bits in the same fixed-length of pixel. While, PVD works better by providing a high quality stego image, besides the high capacity of concealed information. PVD provides high capacity and produces a stego image with good pixels value. PVD technique is also resistant to statistical attacks. It embeds the secret data in the difference as well as in the sum of the two contiguous pixels. In steganography technique, standard measurement to test the performance of stego image quality due to the hiding of message by using the Peak Signal-to-Noise Ratio (PSNR) and Mean Squared Error (MSE). The aim is to achieve higher value of PSNR that indicates a better reconstruction. The expected findings shows a better results of stego image quality based on PSNR and MSE. As a conclusion, the study of the project brings a good impact of higher security towards steganography field in biometrics applications.

Adaptive PVD and LSB based high capacity data hiding scheme

In this paper, a new data hiding scheme using a mixture of adaptive pixel value differencing (PVD) and least significant bit substitution (LSB) is proposed for increasing the data hiding capacity. The scheme is a generalization of Jung (J Real-Time Image Proc. 14:127–36, 2018) which is the first work to use PVD and LSB methods simultaneously on a single image. However, the PVD used by Jung (J Real-Time Image Proc. 14:127–36, 2018) is not an adaptive method means it does not consider the vertical and diagonal edges of the image for hiding the secret data. In the proposed scheme, the vertical and diagonal edges in addition to horizontal edges are used for hiding the secret data so that a large amount of secret data is hidden without any perceived change. Experimental results show that the performance of the proposed scheme is superior to the existing schemes in terms of both data hiding capacity and image quality. Moreover, it is very simple as it does not require much computation for embedding the secret data.

Image Steganography Built on Pixel Value Difference in Spatial Domain using Range Table

With the increase of digital transactions, providing security for the network and its devices is a big challenge today. Sensitive information that has more value in the network is to be protected from unauthorized users in accessing it. Various algorithms are being developed to provide security services for the data. In this paper security is provided by using pixel value differencing technique. Valuable data is embedded in each of the component of color like red, blue and green of a pixel in a color image. In addition to that in providing additional security pixel value has been updated conditionally, that would be more complex to trace the incremented or decremented bits in a pixel of the stegoimage. From this experiment the proposed method provides better visual quality of stego image. This proposed algorithm is suitable for small business applications where small size data is important and threats are more common.

A Steganographic Method with an Overlapping of Three Pixel Block of Image

In this paper a new image steganographic technique has been proposed which is capable of hiding data and produces a stego image that is totally indistinguishable from the original image by the human eye. To estimate the contrast and smoothness of pixels we check the relation between neighboring pixels. Our method first arranges the pixel in ascending manner, then takes the highest pixel value common with the other two pixels and then applies the pixel value differencing (PVD) method. To hide the secret data PVD technique is used in each pixel block. The two overlapping blocks are readjusted to attain the modified three-pixel components. Then calculate the new stego pixel block. In this way, take the middle and lowest pixel as the common pixel and apply the same procedure. In comparison, we get that if the highest value pixel value takes as a common one then the data hiding capacity is increased. The embedding capacity of the cover image is increased by using the pixel block overlapping mechanism. It has been tested on a set of images and also maintains the visual quality of the image.

KAJIAN METODE METODE STEGANOGRAFI PADA DOMAIN SPASIAL

This paper contains a review of the spatial domain steganographic literature. The purpose of this paper is to provide knowledge about techniques or methods that exist in the spatial domain of steganography. Steganography is the science or technique for hiding secret messages in other messages so that the existence of the secret message cannot be accessed by others who do not have authority. There are several popular spatial domains of steganographic techniques, namely LSB (Least Significant Bit), which is mapping secret message bits in the rightmost bit (LSB) of each color pixel and PVD (Pixel Value Differencing) which in this method offers a larger message storage capacity , with better image quality compared to other methods in the spatial domain. Because privacy issues continue to develop along with various digital communication technologies, and increasingly strong security threats, steganography can play a role in society to maintain the confidentiality of both picture, voice and video messages. For this reason it is important for us to be aware of steganographic technology and its implications.

A PVD based high capacity steganography algorithm with embedding in non-sequential position

Modern research in Steganography focuses on increasing the capacity without keeping any perceptible signature into the stego-media. In this work, we present a pixel value difference (PVD) based high capacity methodology. Embedding is not restricted only to high contrast pixel pairs. Low contrast pairs are also considered to enhance the capacity. Embedding process varies depending on the local contrast of the pair. Secret message is encrypted before embedding and pixels pairs are chosen in a non-sequential manner, rendering the methodology more secure. Experiment is performed on more than two hundred images. It is observed that embedding by proposed technique is visually imperceptible and can withstand various types of attacks. The benchmark test like StirMark analysis also indicates the strength of the work. Comparison of performance with a number of other methods shows that proposed methodology maintains high PSNR with enhanced capacity.

Using Daily Observations from Planet Labs Satellite Imagery to Separate the Surface Deformation between the 4 July Mw 6.4 Foreshock and 5 July Mw 7.1 Mainshock during the 2019 Ridgecrest Earthquake Sequence

Abstract On 4 July 2019, the Ridgecrest earthquake sequence began with a series of foreshocks including an Mw 6.4 event near Searles Valley, California. This was then followed 34 hr later by an Mw 7.1 mainshock located just 15 km to the north, with the earthquake sequence resulting in a complex array of intersecting faults. This earthquake sequence poses several interesting questions including, did the stress changes induced by the Mw 6.4 foreshock trigger the Mw 7.1 mainshock and what possible mechanism(s) could explain the occurrence of widespread secondary faulting surrounding both surface ruptures? However, most of the geodetic data (such as Interferometric Synthetic Aperture Radar, light detection and ranging, and optical satellite imagery) were acquired after both events had occurred making it difficult to discern which surface fractures happened when and their possible triggering mechanism. Here, we provide a dataset composed of high-resolution optical imagery, pixel-value difference maps, .kmz fracturing mapping, and horizontal deformation maps derived from subpixel image correlation, which can uniquely separate the surface fracturing and deformation between the foreshock and mainshock events that can help answer these questions. Separate imaging of the events is made possible by the daily acquisition of optical imagery by the Planet Labs cubesat constellation, which acquired data between the two earthquakes, in the morning of 4 and 5 July, at 11.13 a.m. and 05.12 p.m. PST, respectively, with the images acquired just 40 min after the foreshock and 56 min before the mainshock, respectively. Analysis from this optical imagery reveals the location of surface faulting that allows us to map their spatial extent and determine their timing. These data which we provide here can help guide and validate field survey observations to help understand which faults ruptured when, and constrain slip inversion models for more accurate estimates of stress changes induced by the foreshock imposed on the surrounding faults.

Comparison of image-based methods for determining the inline mixing uniformity of pesticides in direct nozzle injection systems

Seven image-based methods to determine mixing uniformity in inline mixers by image processing were compared using viscous pesticides mixtures with gradually increasing uniformity. After obtaining initial optimal methods and calculation parameters, they were further evaluated by a jet mixer and a layered mixer. Results showed that quantitative descriptions for uniformity inside the tube by grey level co-occurrence matrix (GLCM) and concentration difference within time sequence (CVT) failed to reflect accurately the changing-trends in uniformity. A histogram information entropy (HIE)-based method tended to underestimate changes, while coefficient of variance based on each single frame (CVS) which calculated differences in pixel values underestimated it when mixtures showed stratification, indicating that both methods were not suitable. However, the accuracy of methods using explicit features such as second-order moments of grey-scale histogram (HSM) and optimised area-weighted uniformity index (OAU), as well as implicit methods such as principal components analysis (PCA) were suitable, and the normalised index > 80% can be suitable because no non-scattered pesticide remained. Single-viewing images were adequate for evaluating the uniformity produced by mixers although small errors between horizontal and vertical-viewing images existed. During evaluations by mixers, OAU and PCA proved to be more advantageous than HSM because these methods do not only rely on pixel probability distributions of grey-scale histograms, but the positional information of the pesticide distribution, even though the HSM is more time-efficient than them.

Dual Steganography Approach Using 3D Playfair Cipher and Pixel Value Differencing Method

In this paper we attempted to incorporate a text encoding technique 3D Playfair Cipher with Pixel Value Differencing (PVD) approach to achieve dual steganography. Dual steganography is very demanding in the present scenario, because steganography is only playing a role to stealth intruder, but sometimes existence of secret data got recognized, in such scenarios dual steganography can only protect our secret exchange. In steganography hiding capability is equally concerned as much as security, so compression of secret message is preferable before imparting it in cover medium. These requirements pushed us to implement a fast, secure, effective and handy steganographic approach to solve secure information exchange problems. In this research we took the advantage of 3D Playfair cipher not to only encode our secret message but also to reduce its size. Here dual steganography is formed using 3D Playfair cipher with PVD method. PVD method implements the concept that edge areas are more vulnerable that smooth areas in images to conceal secrets,which makes it a powerful approach in the field of image steganography due to its stegoimage quality and data hiding capabilities. PVD method hides data in cover image based on the difference of pixel value in the pixel pairs (nonoverlapping consecutive pixels). Proposed approach is much secure and better in data hiding capability along with ensuring better quality stego image quality, it also solves the problem of falling the boundary of the pixels presents in PVD method. Produced Stegoimage of proposed technique is secure enough against the RS detection attack and totally indistinguishable by human eyes.

A novel high capacity turtle shell-based data hiding with location table free

In this paper, we design a novel turtle shell based data hiding scheme. The proposed scheme starts by constructing a novel reference matrix based on the original turtle shell matrix. Without any overhead messages, the secret data can be concealed in the pixel pairs selected from the cover image and would be correctly extracted according to the characteristic of the reference matrix in a 4 × 5 block. Experimental results demonstrate that the proposed scheme can achieve a high embedding capacity of 2 bit per pixel (bpp). The experimental comparison also reveals that the proposed scheme is superior to some existing data hiding schemes subject to the peak signal-to-noise ratio measurement. Meanwhile, it has good performance on resisting the statistical attack of pixel-value differencing (PVD) histogram.

Enhanced payload and trade-off for image steganography via a novel pixel digits alteration

Many high capacity image steganography algorithms have been proposed but at the cost of lower imperceptibility. To fill the gap, this paper proposes a novel RGB image steganography technique that not only enhances the hiding capacity but also largely improves the trade-off between capacity and imperceptibility on maximum embedding rate. The technique encrypts the secret data (text, grayscale or a color image) into a sequence of two-digit decimal values. A digit in the sequence is hidden in a cover pixel by altering the pixel’s digits to the nearest pixel value possible. Most common spatial hiding techniques are the Least Significant Bit (LSB) substitution and Pixel Value Differencing (PVD) which hide data in the form of bits. The proposed linear time digit based hiding technique outperforms LSB substitution, PVD or their variants in terms of both capacity and imperceptibility. It also outperforms the existing digit hiding methods in color images. Moreover, the method is secure against the two detection schemes of Weighted Stego-Image steganalysis.

Steganography using Spatial Domain Techniques

In present world data transfer using the internet is growing. It is very easy and fast way to transfer information like confidential documents, economic transactions, business applications and other covert information over internet. With the advent and growth of internet, people are more concerned about security of information. Data Security is important while data is transferred over internet because any illegal user can access important and private data also make it worthless. Research in data security area will help government agencies, military organization and private companies to securely transmit their confidential data over internet. From past few years various steganography techniques have been developed to hide secret message using various multimedia objects having large amount of redundant data to support steganography. In this paper introduction about steganography, related concepts and implementation of commonly used spatial domain techniques like LSB(Least Significant Bit Technique) with modulus, PVD(Pixel Value Difference) with LSB replacement and adaptive data hiding over edges with LSB are considered. It is observed(while visual, statistical analysis and experiments were carried out) with benchmark cover and stego objects that embedding same amount of secret data in each pixel leads to more visible distortions in a stego image because all pixels do not bear same amount of changes and this effect is more observed in smooth area then edges. Improving stego image imperceptibility and adjusting hiding capacity adaptively are major related research challenges about spatial domain techniques.

IMPLEMENTASI METODE PIXEL VALUE DIFFERENCING UNTUK PENYEMBUNYIAN PESAN PADA CITRA DIGITAL

The development of information technology is very fast, causing a lot of security holes that can be misused by people who are not responsible so that it can harm certain parties. Digital images are chosen as a container for inserting messages because digital images have sufficient size to hold the message and digital images are often used in information exchange so as not to invite suspicion from irresponsible parties. The information to be sent is hidden in a digital image, then the digital image is sent as normal data, so that third parties do not suspect that there is confidential information inside. Information that is hidden in the digital image can be extracted again by the recipient of the message. Pixel Value Differencing (PVD) works on a pair of adjacent pixel values (adjacent pixels). The advantage of the Pixel Value Differencing (PVD) method is that the capacity of the image generated to insert a message can be smaller than its original size, the processing time of this method is quite fast, after the message is inserted, the image quality has good quality. But this method also has disadvantages, because it is not resistant to manipulation.Keywords: Steganography, Digital Image, Pixel Value Differencing

A reversible water marking algorithm for multimedia images using two-dimensional non-causal prediction and ESPVD

Reversible image watermarking algorithm is an important branch of information hiding, which can protect the integrity of data. Therefore, it is of great practical significance and practical value to study the reversible image water marking algorithm. A multimedia image watermarking algorithm based on two-dimensional non-causal prediction and edge based sorted pixel value difference (ESPVD) is proposed in this paper, which is used to protect the security of multimedia information. Firstly, the optimum prediction coefficients in the horizontal and vertical directions of image are calculated. Then, two-dimensional non-causal prediction of image is carried out according to raster scanning sequence, and prediction pixels and prediction errors are calculated. Finally, the morphological edge (ME) operator is used to identify edge pixel positions, and the ESPVD technology is used to embed the watermarking information. The experimental results show that the proposed algorithm has better performance than those of other image watermarking algorithms under the same embedding ability.

Traceable Quantum Steganography Scheme Based on Pixel Value Differencing

A novel and traceable quantum steganography scheme based on pixel value differencing (PVD) is proposed. In the proposed scheme, a quantum cover image is divided into non-overlapping blocks of two consecutive pixels. Then, by a series of reversible logic circuits, we calculate the difference value based on the values of the two pixels in each block and classify it as one of a set of continuous ranges. The secret image and operator information are embedded in the cover image by using the new obtained difference value to replace the original one. The number of bits of secret image that can be embedded in a block is determined, and the number of bits of operator information is decided by the range of the difference value belongs to. Moreover, when the embedded data is extracted from a stego image, it is not necessary to refer to the original cover image. The performance of the proposed scheme is based on the analysis of several categories of simulation results, such as visual quality, capacity, and robustness.

Strategies for accurate response assessment of radiochromic film using flatbed scanner for beam quality assurance

Radiochromic film is a useful tool for beam quality assurance, but accurate response assessment of the film is still a problem. In this study, the response uncertainties of HDV2 film were investigated using a flatbed scanner from both the scanning settings and interscan variability. Scanning settings are fixed conditions for scanning, including scanning resolution and focus setting. In this study, multipeak distributions of pixel values were found under some dots-per-inch values, which should be avoided, and the optimal setting of 2000 dpi without this problem was selected. By changing the focus setting, the relative standard deviation of pixel values was reduced by 36–50%. The influence of the interscan variability induced by three factors was investigated, including the outside illumination intensity, film homogeneity, and operating temperature. Scanning the film before and after irradiation at the same position was recommended. Moreover, the suitable operating temperature range for the scanner was found to be 15–24 °C, which results in stable film responses. Regarding the studied factors, correction methods and strategies were proposed, and the accurate response assessment of HDV2 film was realized. Finally, a standard operating procedure for response assessment of films was introduced. It can help other researchers study more scanners, films, and particle types.

Cross-Validation and Blind Feature Analysis of 25 Percent Embedding on JPEG Image Format using SVM

This paper provides a result assessment of traditional JPEG picture extraction function steganalysis compared to a cross-validation picture. Four distinct algorithms are used as steganographic systems in the spatial and transform domain. They are LSB Matching, LSB Replacement, Pixel Value Differencing and F5.A 25 percentage of embedding with text embedding information is considered in this paper. The characteristics regarded for evaluation are the First Order, Second Order, Extended DCT characteristics, and Markov characteristics. Support Vector Machine is the classifier used here. In statistical recovery, six distinct kernels and four distinct sampling techniques are used for evaluation.

Blind Steganalysis for JPEG Images using SVM and SVM-PSO Classifiers

Blind steganalysis or the universal steganalysis helps to identify hidden information without previous knowledge of the content or the embedding technique. The Support Vector Machine (SVM) and SVM- Particle Swarm Optimization (SVM-PSO) classifiers are adopted for the proposed blind steganalysis. The important features of the JPEG images are extracted using Discrete Cosine Transform (DCT). The kernel functions used for the classifiers in the proposed work are the linear, epanechnikov, multi-quadratic, radial, ANOVA and polynomial. The proposed work uses linear, shuffle, stratified and automatic sampling techniques. The proposed work employs four techniques for image embedding namely, Least Significant Bit (LSB) Matching, LSB replacement, Pixel Value Differencing (PVD) and F5 and applies 25% embedding. The data to the classifier is split as 80:20 for training and testing and 10-fold cross validation is carried out.

A High Quality Steganography Method with Twenty Five-Pixel Value Differencing

The fundamental objectives of image steganography algorithm are to simultaneously achieve high payload or embedding capacity, good visual imperceptibility and security. This paper presents a new approach to improve the embedding capacity and provide an imperceptible visual quality, a novel steganography method based on algorithm twenty five pixel value differencing and modified interval table (TFPVD). The cover image is made into 5×5 blocks that don’t overlap and TFPVD method with modified interval is used to embed and extract secret information. The results showed that the proposed TFPVD steganography algorithm has a higher steganographic capacity, which is 1,764 times that of the PBVD algorithm.