Difference Histogram Research Articles

PENDEKATAN STEGO-KRIPTO MODE CIPHER BLOCK CHAINING UNTUK PENGAMANAN INFORMASI PADA CITRA DIGITAL

The digital image can be one of the media for information security. The contents of information have an important value of effectiveness, one of which is as a support in decision making. Then the information needs to be done to safeguard the authority of parties who are not responsible. Such security can utilize Steganography and Cryptography (Stego-Crypto). The method used combines Stego-Crypto by randomizing information using Cipher Block Chaining (CBC) then the encryption results are secured through digital images. Based on the test results by measuring the capacity of information on the image produces test data if CBC can process characters in uppercase, spaces and other characters and the results of plaintext and ciphertext produce a ratio of 1: 2, but the LSB performance only accommodates characters depending on the number of sizes on digital image. Testing by evaluating the difference in pixel histogram, when viewed with an invisible not very visible difference, but the insertion of messages with 100-200 characters causes the addition of the average image size on stego images larger than 1: 4, the value of 1 from the original image. Besides, testing with the help of communication media, stego images or encrypted images is able to use email to send stego images because LSB is sensitive to the process of resizing images

Image retrieval based on gradient-structures histogram

Color perception and orientation selection are very important mechanisms of the human brain that have close relationships with feature extraction and representation. However, extracting low-level features by mimicking these mechanisms remains challenging. To address this problem, we present the gradient-structures histogram as a novel method of content-based image retrieval (CBIR). Its main highlights are: (1) a novel and easy-to-calculate local structure detector, the gradient-structures, which simulates the orientation selection mechanism based on the opponent-color space and connects it with low-level features, (2) a novel discriminative representation method that describes color, intensity and orientation features. It is convenient, as it does not require weight coefficients for color, intensity and orientation. (3) The proposed representation method has the advantages of being histogram-based and having the power to discriminate spatial layout, color and edge cues. The proposed method provides efficient CBIR performance, as demonstrated by comparative experiments in which it significantly outperformed some state-of-the-art methods, including the Bow method, local binary pattern histogram, perceptual uniform descriptor, color volume histogram, color difference histogram, some improved LBP methods and the Tree2Vector method in terms of precision/recall and AUC metrics.

Exploring Polarimetric Phase of Microwave Backscatter from Typha Wetlands

Despite their natural and societal importance, wetlands are becoming increasingly threatened. The goal of this study is to investigate the potential of polarimetric synthetic aperture radar (SAR) for monitoring one important vegetation constituent of wetlands: Typha. An idealized cylindrical scattering model is developed to portray double bounce microwave scattering from Typha stalks. Then a thin cylinder Brewster angle is introduced; relating the co-pol phase difference (CPD) of Typha to its relative permittivity. Full polarization Radarsat-2 data were acquired for a variety of dates and incidence angle ranges in order to validate the scattering model. The dependence of CPD on incidence angle is found to be consistent with the model. The evolution of CPD with seasonal senescence was also investigated. Despite some agreement with expected trends in vegetation moisture, there are anomalies that remain unexplained; possibly due to ecosystem change. This suggests the need for radar scatterometer experiments in a controlled environment to better explore the dependence of CPD on incidence angle and seasonal change. Last, cross-pol phase difference (XPD) histograms support other research in demonstrating the existence of coherent depolarization in Typha scattering. Additional modeling, entailing the detailed structure of the vegetation, will be necessary to understand this behavior.

Separable Reversible Data Hiding Scheme in Homomorphic Encrypted Domain Based on NTRU

NTRU (Number Theory Research Unit) has the characteristics of resistance to quantum computing attacks, fast encryption and decryption, and high security. It is very suitable for wireless confidential data networks and authentication systems. Combined with reversible data hiding technology, a separable reversible data hiding scheme in homomorphic encrypted domain based on NTRU is proposed. The image owner directly divides the cover-image into groups of a reference pixel and T adjacent pixels. Then, the grouped image is encrypted by NTRU. Finally, the encrypted image is uploaded to the data hider. The encrypted image is divided into groups by the same grouping method as the image owner. After that, the data hider calculates T absolute differences of adjacent pixels in each group to obtain histogram of the absolute differences. The additional data can be embedded into the encrypted image by shifting histogram of the absolute differences. After receiving the encrypted image with hidden data, the receiver can either use the data hiding key to directly extract the additional data from encrypted domain to obtain the encrypted image, or use the private key and data hiding key to extract the additional data from plaintext domain to get the cover-image. Experimental results show that our scheme has higher security and better embedding performance comparing with other state-of-the-art works.

New High Capacity Reversible Data Hiding Using the Second-Order Difference Shifting

Reversible data hiding (RDH) algorithm is developing rapidly for many years. Usually, the histogram shifting (HS) based RDH algorithm has two main steps: Firstly, a steep difference histogram is generated with some effective methods for difference. Secondly, by extending and shifting some differences in the histogram, bits of information can be embedded into the cover image which can be restored reversibly. In this paper, we proposed the second-order difference to obtain a steeper difference histogram. Firstly, we slide a window with size 2 × 2 through the image. For each block, we can get the two first-order differences by calculating the absolute values of the two differences for its two columns. Thus, the second-order difference of each block, which is the absolute values of the difference of the two first-order differences, can be obtained. By extending and shifting the second-order difference, a bit may be embedded into the block finally. Experiments reveal that the proposed algorithm outperforms the previous state-of-the-art RDH methods in terms of the computational complexity, image distortion and the embedding performance.

Clinical radiotherapy application of N-vinylpyrrolidone-containing 3D polymer gel dosimeters with remote external MR-reading

PurposeAdvanced 3D dosimetry is required for verifications of complex dose distributions in modern radiotherapy. Two 3D polymer gel dosimeters, coupled with magnetic resonance (MR) imaging (3 T MRI) readout and data processing with polyGeVero® software, were tested for the verification of calculated 3D dose distributions by a treatment planning system (TPS) and ArcCHECK®–3DVH®, related to eradication of a lung tumour. MethodsN-vinylpyrrolidone-containing 3D polymer gel dosimeters were used: VIC (containing ascorbic acid and copper sulfate pentahydrate) and VIC-T (containing tetrakis(hydroxymethyl)phosphonium chloride). Three remote centers were involved in the dosimeters preparation and irradiation (Poland), and MRI (Austria). Cross beam calibration of the dosimeters and verification of a 3D dose distribution calculated with an Eclipse External Beam TPS and ArcCHECK®–3DVH® were performed. The 3D-to-3D comparisons of the VIC and VIC-T with TPS and ArcCHECK®–3DVH® along with ArcCHECK®–3DVH® versus TPS dose matrixes were performed with the aid of the polyGeVero® by analyzing dose profiles, isodoses lines, gamma index, gamma angle, dose difference, and related histograms. ResultsThe measured MR-relaxation rate (R2 = 1/T2) for the dosimeters relates to the dose, as follows: R2 = 0.0928 ± 0.0008 [Gy−1 s−1] × D [Gy] + 2.985 ± 0.012 [s−1] (VIC) and 0.1839 ± 0.0044 [Gy−1 s−1] × D [Gy] + 2.519 ± 0.053 [s−1] (VIC-T). The 3D-to-3D comparisons revealed a good agreement between the measured and calculated 3D dose distributions. ConclusionsVIC and VIC-T with 3T MRI readout and polyGeVero® showed potential for verifications of calculated irradiation plans. The results obtained suggest the implementation of the irradiation plan for eradication of the lung tumour.

Channel State Discrimination Method Based on Multi-Structure Color Difference Histogram

The determination of channel characteristics has always been a research hotspot of wireless communication systems. It directly affects the correctness of channel state analysis. Channel feature extraction methods are endless, but most of the existing extraction methods are limited by specific environments. The methods are complex, the system analysis is not comprehensive enough, the applicability is not extensive, and it is affected by external interference. This paper avoids the disadvantages of direct extraction and innovatively introduces an image construction method that can analyze the channel state in real time. In addition, an improved image feature extraction algorithm is proposed for the state images proposed in this paper, which verifies high robust performance of the algorithm. In the end, a model capable of efficiently and accurately predicting real-time conditions of short-wave fading channel states is constructed. First, channel state images are constructed, including time domain image, frequency domain image, and related domain image. The three state images reflect the channel state in all aspects. Then, the multi-texton image feature extraction method is optimized and improved, and the multi-structure color difference (MSC) extraction method is constructed to extract the channel state image information. Then, through the experimental simulation, the method of channel state division is specified, and the performance advantage of the improved algorithm MSC relative to the original algorithm is verified. Finally, discriminating channel state based on SVM algorithm. A series of experiments on rotation invariance test, immunity from interference test and illumination variation test verify that the proposed method has high robustness and the recognition accuracy is between 80% and 100%, which can effectively identify Instantaneous channel advantages and disadvantages.

A Reversible Steganography Method With Statistical Features Maintained Based on the Difference Value

Reversible data hiding (RDH) is a technique that slightly alters digital media (e.g. images or videos) to embed secret messages while the original digital media can be completely recovered without any error after the hidden messages have been extracted. In the past more than one decade, hundreds of RDH algorithms have been reported, and among these algorithms, the difference histogram shifting (DHS) based methods have attracted much attention. With DHS-based RDH, high capacity and low distortion can be achieved efficiently. But there occurs one problem that, with DHS, the difference values to embed secret bits are explored, and the other difference values are shifted to create vacant spaces, it will cause the difference value histogram changing significantly and draw the attention of steganalyzers. So, this paper proposed a new idea for RDH based on the difference value and with statistical features maintained (SFM) with simple implementation and high scalability, we embed the secret messages by keeping the difference values that need to be modified in the original range, and the other difference values would not be shifted. In addition, we need the original difference values as the key to extract the secret messages. In order to expand the embedding capacity further, we designed two algorithms that embed message in two different difference values and four different difference values, and these two methods are named SFM_A and SFM_B respectively. SFM_B can support greater amount of embedded message than SFM_A, but brings greater changes to the original image, which could lead to the decline of PSNR and SSIM. The experimental results show that through our method, the histogram of difference values is well maintained, and the degree of distortion of the image is improved at the same time.

A Defect Detection Method for the Image With Intersecting Feature

Since the intersecting feature between the defect and the background of the image, the defect detection often results in under-segmentation or over-segmentation. To solve this problem, we propose a new defect extraction method by calculating the maximum mutual information of intersecting features. Firstly, we construct a new two-dimensional histogram according to the defect features. The new histogram is called Gray Level and Local Spatial Difference histogram (GLSD), which is constructed by grayscale and the improved local gray difference with the spatial relationship. Secondly, considering the geometric distribution of high-probability background events, we improve the segmentation shape of the background event distribution and divide the GLSD histogram preliminary. Finally, we calculate the maximum mutual information of the intersecting feature between the defect and the background. At this point, the boundary of the intersecting feature interval of the GLSD histogram is determined. To verify the effectiveness of the proposed method, we used two sets of databases for performance evaluation. The experimental results show that the proposed method is suitable for non-obvious defect detection under the local uniform background. Meanwhile, it can improve the sensitivity, specificity, and accuracy of defect detection compared with the classical threshold segmentation methods.

Unsupervised key frame selection using information theory and colour histogram difference

Key frame selection is one of the important research issues in video content analysis, as it helps effective video browsing and retrieval as well as efficient storage. Key frames would typically be...

Reversible Image Steganography Using Dual-Layer LSB Matching

Recently, reversible information hiding (RIH) methods have drawn substantial attention in many privacy-sensitive real-time applications, such as the Internet of Things (IoT) enabled communications, electronic health care infrastructure, and military applications. The RIH methods are proven to be competent in such hyper-sensitive infrastructures where the loss of a single bit of information is not acceptable. In this paper, dual-layered based RIH method using modified least significant bit (LSB) matching has been proposed. The objective of the proposed work is to enhance the embedding efficiency (EE) using dual-layer based embedding strategy and to curtail the distortion caused to the stego-image to improve its quality. At the first layer of embedding, each pixel conceals two bits of information using the proposed modified LSB matching method to produce the intermediate pixel pair (IPP). Further, the IPP is utilized to conceal four bits of information during the next layer of embedding. Experimental study reveals that, the proposed method can embed 1,572,864 bits of secret data with peak signal-to-noise ratio (PSNR) of 47.86 dB, 48.05 dB, 46.51 dB and 48.14 dB, for the respective images. Further, the image quality assessment parameters like structural similarity (SSIM) index and universal image quality index (Q) are as good as the existing literature. Additionally, the proposed method shows excellent anti-steganalysis ability to regular and singular (RS) and pixel difference histogram (PDH) analysis.

Knowledge-based automated planning with three-dimensional generative adversarial networks.

To develop a knowledge-based automated planning pipeline that generates treatment plans without feature engineering, using deep neural network architectures for predicting three-dimensional (3D) dose. Our knowledge-based automated planning (KBAP) pipeline consisted of a knowledge-based planning (KBP) method that predicts dose for a contoured computed tomography (CT) image followed by two optimization models that learn objective function weights and generate fluence-based plans, respectively. We developed a novel generative adversarial network (GAN)-based KBP approach, a 3D GAN model, which predicts dose for the full 3D CT image at once and accounts for correlations between adjacent CT slices. Baseline comparisons were made against two state-of-the-art deep learning-based KBP methods from the literature. We also developed an additional benchmark, a two-dimensional (2D) GAN model which predicts dose to each axial slice independently. For all models, we investigated the impact of multiplicatively scaling the predictions before optimization, such that the predicted dose distributions achieved all target clinical criteria. Each KBP model was trained on 130 previously delivered oropharyngeal treatment plans. Performance was tested on 87 out-of-sample previously delivered treatment plans. All KBAP plans were evaluated using clinical planning criteria and compared to their corresponding clinical plans. KBP prediction quality was assessed using dose-volume histogram (DVH) differences from the corresponding clinical plans. The best performing KBAP plans were generated using predictions from the 3D GAN model that were multiplicatively scaled. These plans satisfied 77% of all clinical criteria, compared to the clinical plans, which satisfied 67% of all criteria. In general, multiplicatively scaling predictions prior to optimization increased the fraction of clinical criteria satisfaction by 11% relative to the plans generated with nonscaled predictions. Additionally, these KBAP plans satisfied the same criteria as the clinical plans 84% and 8% more frequently as compared to the two benchmark methods, respectively. We developed the first knowledge-based automated planning framework using a 3D generative adversarial network for prediction. Our results, based on 217 oropharyngeal cancer treatment plans, demonstrated superior performance in satisfying clinical criteria and generated more realistic plans as compared to the previous state-of-the-art approaches.

Blind and robust watermarking scheme combining bimodal distribution structure with iterative selection method

To protect the ownership, a blind and robust watermarking scheme is devised by the coefficients of the discrete cosine transform. In the embedding process, the absolute differences of discrete cosine transform coefficients are divided into two groups according to the watermark. That’s to say, the shape of the absolute difference histogram is modulated to build a bimodal structure. In the extraction process, an adaptive threshold is calculated with an iterative selection method. To our knowledge, it is the first time to take advantage of the robust characteristic in a particular shape. Besides, several attack experiments including JPEG compression, cropping, resizing and blurring are performed. The results in attack experiments and comparison experiments demonstrate the superiority of the proposed blind watermarking scheme.

Design of Digital Video Watermarking Technique Based on Motion Frames

The availability of high internet bandwidth instantaneously transfer the digital video multimedia object between two or work workstations. Additionally, the advent of digital technology can be mistreating by malicious user to replicate multiple identical copies of the original video illegally. These capabilities introduce the issue of developing the methods for protecting the copyright of video multimedia objects. The proposed technique suggested detecting the motion part of the video by applying heuristic method of histogram difference between two consecutive frames. Then powerful transformations, Singular Value Decomposition (SVD), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are used to insert the different segment of the scrambled watermarks into different motion frames of the video. The experimental results show that the scheme is robust to unintentional and intentional video specific attacks which considered being frequently occurring attacks. The proposed algorithm has been contrasted with an existing DWT, DCT or hybrid-based approaches and is found to exhibit better robustness.

An efficient multiple-bit reversible data hiding scheme without shifting

For the past few years, the data-hiding schemes are growing rapidly. Generally, data hiding performs well on common images but it does not provide satisfying results on distortion sensitive images such as medical, military, or forensic images. This is because embedding data into an image can cause permanent distortion after extraction (irreversible). As a solution, a certain scheme is required for the process of embedding data into an image, such as reversible data hiding (RDH). One well-known RDH scheme is difference expansion (DE), which is simple, easy to implement. Due to the local correlation between two neighboring pixels, conventional DE-based schemes utilize some empirical criteria to embed one bit into one of the pixels, which does not fully consider the correlations of pixels in neighborhood. In this study, an efficient multiple-bit reversible data hiding scheme without shifting (EMRDH), is proposed, focusing on increasing capacity and visual quality of data hiding. Firstly, a pixel is taken as an embeddable pixel (EP)or a non-embeddable pixel (NEP) according to its relations with the left and right neighbors, and then the EP is substituted with a new pixel consisting of flag-bits, offset-bits and embedding bits, without the difference histogram and expansion processes. With the flag-bits and embedding bits, the embedded data can be extracted without any error while the EP or NEP can be losslessly recovered with the flag-bits, offset-bits. Experimental results show that the proposed scheme has higher capacity, better visual quality and lower computational complexity compared with previous works.

A novel and rapid approach to estimate patient-specific distortions based on mDIXON MRI

While MRI-only radiation treatment planning (RTP) is becoming more widespread, a robust clinical solution for patient-specific distortion corrections is not available. This work explores B0 mapping based on mDIXON imaging, often performed for MR-only RTP, as an alternative to separate dual-acquisition gradient-recalled echo imaging, with the overarching goal of developing an efficient and robust approach for patient-specific distortion correction. Initial benchmarking was conducted by scanning a phantom and generating B0 field maps with two approaches: (1) conventional B0 mapping and (2) experimental mDIXON imaging. Distortion maps were derived from the field maps and compared. The head and neck regions, including brain, of ten healthy volunteers were then evaluated at 1.5 T and 3 T. Distortion maps were again compared between approaches, using difference maps and histogram analysis. Overall, conventional B0 mapping was well approximated by mDIXON imaging: The distortions of 95% of the voxels in the phantom estimated by mDIXON and conventional B0 mapping differed by <0.02 mm (1.5 T) and <0.04 mm (3 T), while the 95-percentiles of the distortions estimated by conventional B0 mapping were <0.06 mm (1.5 T) and <0.12 mm (3 T). In head and neck the distortions of 99% of the voxels were within ±0.2 mm at 1.5 T for both approaches and within ±0.4 mm and ±0.5 mm at 3 T for mDIXON imaging and conventional B0 mapping, respectively. The majority of differences in vivo were confined to regions with high spatial variation of the B0 field, mostly around internal air cavities. For 1.5 T, the mDIXON imaging-based correction alone reduced the 95-percentile of distortions from 0.15 mm to 0.03 mm and within the brain from 0.06 mm to 0.02 mm. Slightly lower reductions were observed at 3 T. In conclusion, mDIXON imaging closely approximated conventional B0 mapping for patient-specific distortion assessment. Estimates in the brain were in good agreement, and slight differences were observed near air/tissue interfaces in the head and neck. Overall, mDIXON imaging-based B0 field maps may be advantageous for rapid patient-specific distortion correction without additional imaging.

A New Automatic Visual Scene Segmentation Algorithm for Flash Movie

Flash movie retrieval system can improve the utilization of Flash movie on the Internet. The key step of a content-based Flash movie retrieval system is visual scene segmentation that directly affects the retrieval effect. In this paper, an adaptive threshold method for visual scene segmentation based on frame difference of color histogram is proposed. Firstly, all key frame sequences of a Flash movie are obtained; then the region-weighted color histogram difference of adjacent key frames is calculated; lastly, the visual scene is classified by comparing the result with the average difference. In the process of visual scene segmentation, the spatial characteristics of color are considered and the regional weighting coefficient of key frames is determined by comparing the experiments. The proposed algorithm replaces the traditional fixed global threshold with a variable adaptive threshold. The experiments show that the proposed algorithm has a better detection effect than the fixed threshold algorithm. This algorithm can easily be implemented with moderate computational complexity. The proposed algorithm can be used to extract visual features of the visual scene, generate dynamic summary, and finally can be applied to content-based Flash animation retrieval system. Moreover, the proposed algorithm can also be used in non-flash applications.

High fidelity based reversible data hiding using modified LSB matching and pixel difference

Owing to the inefficiency to hide large volume of secret data for the reversible data hiding (RDH) image steganography approaches, we propose two improved RDH based approaches, such as (1) improved dual image based least significant bit (LSB) matching with reversibility, and (2) n-rightmost bit replacement (n-RBR) and modified pixel value differencing (MPVD). The first approach extends the ability of LSB matching with reversibility using dual images. Whereas the second approach utilizes four identical cover images for secret data embedding using two phases, such as (1) n-rightmost bit replacement (n-RBR) and (2) modified pixel value differencing (MPVD). In the n-RBR phase, n bits of secret data are embedded in the pair of two neighboring pixels of the first two identical images, where 1 ≤ n ≤ 4. Correspondingly, the MPVD phase uses the third and fourth identical images for hiding the secret data. Experimental results with respect to peak signal-to-noise ratio (PSNR), embedding capacity (EC), structural similarity index (SSIM), and the comparative analysis with recently proposed state-of-art approaches exhibit the superiority of the proposed approach. Besides reversibility, the proposed approach ensures high fidelity to salt and pepper (S&P) noise, RS analysis, and pixel difference histogram (PDH) analysis.

A Framework for Clinical Validation of Automatic Contour Propagation: Standardizing Geometric and Dosimetric Evaluation

PurposeThe objective of this work was to outline and demonstrate a standardized framework for evaluating automatically propagated contour quality against expert contours. A 2-pronged approach is used to evaluate contour quality: a geometric evaluation to identify geometric and spatial discrepancies between propagated and expert contours, and a comprehensive dosimetric comparison to provide clinical context for the results. Methods and MaterialsThe standardized framework requires a primary image, with reference contours and a radiation therapy treatment plan, and a secondary image. Reference contours are automatically propagated onto the secondary image anatomy and compared with expert contours obtained in an interobserver study. The standardized framework outlines geometric and dosimetric evaluation methodologies for determining indistinguishability between propagated and expert contours in a cohort analysis. Propagated contours are geometrically compared with expert contours in terms of the Dice similarity coefficient and the mean distance to agreement. Statistical analysis is performed on the central tendency and variability of Dice similarity coefficient and mean distance to agreement values over the patient cohort. Dosimetric evaluation involves computing the mean and 95% confidence intervals for the differences in cumulative dose-volume histograms for propagated and expert contours. A case study in accelerated partial breast irradiation was shown to demonstrate the framework. ResultsThe standardized framework was applied to a case study of 24 patient data sets with 3 radiation oncologists providing the expert contours. Cohort analysis indicated that propagated contours were geometrically indistinguishable and dosimetrically distinguishable from expert contours. ConclusionsThe recommended framework standardizes the comparison of geometric and dosimetric parameters to demonstrate indistinguishability of propagated contours from expert contours. Adoption of this framework is vital for consistent and comprehensive validation of automatic contour propagation for use in large-scale cohort analyses.

AnalisaCAEN, a simple software suite to reduce and analyze coincidence data collected using CAEN v1724 digitizer

In this work a small software suite for the reduction and analysis of coincidence data collected using CAEN’s proprietary software was developed. These software check the output files for coincidences, generate a single list mode file with the coincident events, build histograms for each input, plus a time difference histogram and a 2-detector data matrix, perform time gates and allows for the subtraction of accidental coincidences, and perform energy gating on the final data matrices, generating histograms with the gated spectra. Moreover, the suite has an integrator that guides the user through all the required steps.