Blind steganalysis : a countermeasure for binary image steganography

In this paper, we propose a new blind steganalytic method to detect the presence of secret messages embedded in black and white images using the steganographic techniques. We start by extracting several sets of matrix, such as run length matrix, gap length matrix and pixel difference. We also apply characteristic function on these matrices to enhance their discriminative capabilities. Then we calculate the statistics which include mean, variance, kurtosis and skewness to form our feature sets. The presented empirical works demonstrate our proposed method can effectively detect three different types of steganography. This proves the universality of our proposed method as a blind steganalysis. In addition, the experimental results show our proposed method is capable of detecting small amount of the embedded message.

Radiotherapy Assessment Using Diffusion Weighted MRI

Purpose: There are two goals of this study. The first goal of this study is to investigate the feasibility of using classic textural feature extraction in radiotherapy response assessment among a unique cohort of early stage breast cancer patients who received the single-dose preoperative radiotherapy. The second goal of this study is to investigate the clinical feasibility of using classic texture features as potential biomarkers which are supplementary to regional apparent diffusion coefficient in gynecological cancer radiotherapy response assessment.

Methods and Materials: For the breast cancer study, 15 patients with early stage breast cancer were enrolled in this retrospective study. Each patient received a single-fraction radiation treatment, and DWI and DCE-MRI scans were conducted before and after the radiotherapy. DWI scans were acquired using a spin-echo EPI sequence with diffusion weighting factors of b = 0 and b = 500 mm2/s, and the apparent diffusion coefficient (ADC) maps were calculated. DCE-MRI scans were acquired using a T1-weighted 3D SPGR sequence with a temporal resolution of about 1 minute. The contrast agent (CA) was intravenously injected with a 0.1 mmol/kg bodyweight dose at 2 ml/s. Two parameters, volume transfer constant (Ktrans) and kep were analyzed using the two-compartment Tofts pharmacokinetic model. For pharmacokinetic parametric maps and ADC maps, 33 textural features were generated from the clinical target volume (CTV) in a 3D fashion using the classic gray level co-occurrence matrix (GLCOM) and gray level run length matrix (GLRLM). Wilcoxon signed-rank test was used to determine the significance of each texture feature’s change after the radiotherapy. The significance was set to 0.05 with Bonferroni correction.

For the gynecological cancer study, 12 female patients with gynecologic cancer treated with fractionated external beam radiotherapy (EBRT) combined with high dose rate (HDR) intracavitary brachytherapy were studied. Each patient first received EBRT treatment followed by five fractions of HDR treatment. Before EBRT and before each fraction of brachytherapy, Diffusion Weighted MRI (DWI-MRI) and CT scans were acquired. DWI scans were acquired in sagittal plane utilizing a spin-echo echo-planar imaging sequence with weighting factors of b = 500 s/mm2 and b = 1000 s/mm2, one set of images of b = 0 s/mm2 were also acquired. ADC maps were calculated using linear least-square fitting method. Distributed diffusion coefficient (DDC) maps and stretching parameter α were calculated. For ADC and DDC maps, 33 classic texture features were generated utilizing the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from high-risk clinical target volume (HR-CTV). Wilcoxon signed-rank statistics test was applied to determine the significance of each feature’s numerical value change after radiotherapy. Significance level was set to 0.05 with multi-comparison correction if applicable.

Results: For the breast cancer study, regarding ADC maps calculated from DWI-MRI, 24 out of 33 CTV features changed significantly after the radiotherapy. For DCE-MRI pharmacokinetic parameters, all 33 CTV features of Ktrans and 33 features of kep changed significantly.

For the gynecological cancer study, regarding ADC maps, 28 out of 33 HR-CTV texture features showed significant changes after the EBRT treatment. 28 out of 33 HR-CTV texture features indicated significant changes after HDR treatments. The texture features that indicated significant changes after HDR treatments are the same as those after EBRT treatment. 28 out of 33 HR-CTV texture features showed significant changes after whole radiotherapy treatment process. The texture features that indicated significant changes for the whole treatment process are the same as those after HDR treatments.

Conclusion: Initial results indicate that certain classic texture features are sensitive to radiation-induced changes. Classic texture features with significant numerical changes can be used in monitoring radiotherapy effect. This might suggest that certain texture features might be used as biomarkers which are supplementary to ADC and DDC for assessment of radiotherapy response in breast cancer and gynecological cancer.

Particulate texture image analysis with applications

Texture analysis and textural cues have been applied for image classification, segmentation and pattern recognition. Dominant texture descriptors include directionality, coarseness, line-likeness etc. In this dissertation a class of textures known as particulate textures are defined, which are predominantly coarse or blob-like. The set of features that characterise particulate textures are different from those that characterise classical textures. These features are micro-texture, macro-texture, size, shape and compaction. Classical texture analysis techniques do not adequately capture particulate texture features. This gap is identified and new methods for analysing particulate textures are proposed. The levels of complexity in particulate textures are also presented ranging from the simplest images where blob-like particles are easily isolated from their back- ground to the more complex images where the particles and the background are not easily separable or the particles are occluded. Simple particulate images can be analysed for particle shapes and sizes. Complex particulate texture images, on the other hand, often permit only the estimation of particle dimensions. Real life applications of particulate textures are reviewed, including applications to sedimentology, granulometry and road surface texture analysis. A new framework for computation of particulate shape is proposed. A granulometric approach for particle size estimation based on edge detection is developed which can be adapted to the gray level of the images by varying its parameters. This study binds visual texture analysis and road surface macrotexture in a theoretical framework, thus making it possible to apply monocular imaging techniques to road surface texture analysis. Results from the application of the developed algorithm to road surface macro-texture, are compared with results based on Fourier spectra, the auto- correlation function and wavelet decomposition, indicating the superior performance of the proposed technique. The influence of image acquisition conditions such as illumination and camera angle on the results was systematically analysed. Experimental data was collected from over 5km of road in Brisbane and the estimated coarseness along the road was compared with laser profilometer measurements. Coefficient of determination R2 exceeding 0.9 was obtained when correlating the proposed imaging technique with the state of the art Sensor Measured Texture Depth (SMTD) obtained using laser profilometers.

Time delay to firing of a triggered vacuum gap with barium titanate in trigger gap

The time delay to the firing of a triggered vacuum gap (t.v.g.) containing barium titanate in the trigger gap is investigated as a function of the main gap voltage, main gap length, trigger pulse duration, trigger current and trigger voltage. The time delay decreases steadily with increasing trigger current and trigger voltage until it reaches saturation. The effect of varying the main gap length and voltage on the time delay is not strong. Before `conditioning�¿ the t.v.g. two groups of time delays, long (>100�¿s) and short (<10�¿s), are simultaneously observed when a large number of trials are conducted. After conditioning, only the group of short time delays are present. This is attributed to the marked reduction of the resistance of the trigger gap across the surface of the solid dielectric resulting directly from the conditioning effect.

Content Based Image Retrieval Using Low Level Features of Automatically Extracted Regions of Interest

This paper proposes a region based image retrieval system using the local colour and texture features of image sub regions. The regions of interest (ROI) are roughly identified by segmenting the image into fixed partitions, finding the edge map and applying morphological dilation. The colour and texture features of the ROIs are computed from the histograms of the quantized HSV colour space and Gray Level co- occurrence matrix (GLCM) respectively. Each ROI of the query image is compared with same number of ROIs of the target image that are arranged in the descending order of white pixel density in the regions, using Euclidean distance measure for similarity computation. Preliminary experimental results show that the proposed method provides better retrieving result than retrieval using some of the existing methods.

An improved estimate of leaf area index based on the histogram analysis of hemispherical photographs

Leaf area index (LAI) is a key parameter that affects the surface fluxes of energy, mass, and momentum over vegetated lands, but observational measurements are scarce, especially in remote areas with complex canopy structure. In this paper we present an indirect method to calculate the LAI based on the analyses of histograms of hemispherical photographs. The optimal threshold value (OTV), the gray-level required to separate the background (sky) and the foreground (leaves), was analytically calculated using the entropy crossover method (Sahoo, P.K., Slaaf, D.W., Albert, T.A., 1997. Threshold selection using a minimal histogram entropy difference. Optical Engineering 36(7) 1976-1981). The OTV was used to calculate the LAI using the well-known gap fraction method. This methodology was tested in two different ecosystems, including Amazon forest and pasturelands in Brazil. In general, the error between observed and calculated LAI was similar to 6%. The methodology presented is suitable for the calculation of LAI since it is responsive to sky conditions, automatic, easy to implement, faster than commercially available software, and requires less data storage. (C) 2008 Elsevier B.V. All rights reserved.

Effect of thermo-mechanical load cycling on silorane-based composite restorations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

In vitro study on radiographic gray levels of biomaterials using two digital image methods

PURPOSE: To compare the direct and indirect radiographic methods for assessing the gray levels of biomaterials employing the Digora for Windows and the Adobe Photoshop CS2 systems. METHODS: Specimens of biomaterials were made following manusfacturer's instructions and placed on phosphor storage plates (PSP) and on radiographic film for subsequent gray level assessment using the direct and indirect radiographic method, respectively. The radiographic density of each biomaterial was analyzed using Adobe Photoshop CS2 and Digora for Windows software. RESULTS: The distribution of gray levels found using the direct and indirect methods suggests that higher exposure times are correlated to lower reproducibility rates between groups. CONCLUSION: The indirect method is a feasible alternative to the direct method in assessing the radiographic gray levels of biomaterials, insofar as significant reproducibility was observed between groups for the exposure times of 0.2 to 0.5 seconds.

Transverse drainages of the Susquehanna River basin, Pennsylvania, USA

While large-scale transverse drainages (TDs) such as those of the Susquehanna River above Harrisburg, PA, have been recognized since the 19th century, there have been no systematic surveys done of TDs since that of Ver Steeg's in 1930. Here, the results are presented of a topographic and statistical analysis of TDs in the Susquehanna River basin using Google Earth and associated overlays. 653 TDs were identified in the study area, 95% of which contain streams with discharges of less than 10 m3/s. TD depths ranged from a 23 m deep water gap near Blain, PA, to the 539 m deep gorge of the Juniata River through Jacks Mountain. Although TD depth tended to increase with stream size, many small streams were located in deep gaps, and eight streams with discharges of 10 m3/s or less were found in gorges whose depths matched or exceeded the deepest TD of the Susquehanna, the largest stream in the basin. Streams of less than 10 m3/s made up the majority of TDs regardless of the rock type capping the breached structure. Overall, TDs through sandstone-capped ridges were deeper than those topped by shales, and TDs in both sandstones and shales displayed a lognormal distribution of depths, which may be indicative of a preferred value. Stream flow direction was primarily perpendicular to local structural strike, with 47% of streams flowing NW and 53% flowing SE. 19% of the TDs were found to be in alignment with at least one other TD, with aligned segment lengths ranging from .5 to 14.8 km. The majority of TDs were in rocks of Paleozoic age. The techniques described here allow the frequency and distribution of TDs to be quantified so that they can be integrated into models of basin evolution.

Level Set Segmentation with Shape and Appearance Models Using Affine Moment Descriptors

We propose a level set based variational approach that incorporates shape priors into edge-based and region-based models. The evolution of the active contour depends on local and global information. It has been implemented using an efficient narrow band technique. For each boundary pixel we calculate its dynamic according to its gray level, the neighborhood and geometric properties established by training shapes. We also propose a criterion for shape aligning based on affine transformation using an image normalization procedure. Finally, we illustrate the benefits of the our approach on the liver segmentation from CT images.

1 + 1 = 3? EU-US voting cohesion in the United Nations General Assembly. EU Diplomacy Paper 07/2012, September 2012

This paper investigates the factors that explain the voting cohesion of the United States (US) and the European Union (EU) on foreign policy issues in the United Nations General Assembly (UNGA). It is often argued that the EU and the US are simply too different to cooperate within international organizations and thus to vote the same way, for example, in the UNGA. However, there is still a lack of research on this point and, more importantly, previous studies have not analyzed which factors explain EU-US voting cohesion. In this paper, I try to fill this gap by studying voting cohesion from 1980 until 2011 on issues of both ‘high’ politics (security) and ‘low’ politics (human rights) not only as regards EU-US voting cohesion, but also concerning voting cohesion among EU member states. I test six hypotheses derived from International Relations theories, and I argue that EU-US voting cohesion is best explained by the topic of the issue voted upon, whether an issue is marked as ‘important’ by the US government, and by the type of resolution. On the EU level, the length of Union membership and transaction costs matter most.

A study of magnetic non-linearity and finite length effects in solid iron subjected to a travelling MMF wave

This thesis describes an experimental and analytic study of the effects of magnetic non-linearity and finite length on the loss and field distribution in solid iron due to a travelling mmf wave. In the first half of the thesis, a two-dimensional solution is developed which accounts for the effects of both magnetic non-linearity and eddy-current reaction; this solution is extended, in the second half, to a three-dimensional model. In the two-dimensional solution, new equations for loss and flux/pole are given; these equations contain the primary excitation, the machine parameters and factors describing the shape of the normal B-H curve. The solution applies to machines of any air-gap length. The conditions for maximum loss are defined, and generalised torque/frequency curves are obtained. A relationship between the peripheral component of magnetic field on the surface of the iron and the primary excitation is given. The effects of magnetic non-linearity and finite length are combined analytically by introducing an equivalent constant permeability into a linear three-dimensional analysis. The equivalent constant permeability is defined from the non-linear solution for the two-dimensional magnetic field at the axial centre of the machine to avoid iterative solutions. In the linear three-dimensional analysis, the primary excitation in the passive end-regions of the machine is set equal to zero and the secondary end faces are developed onto the air-gap surface. The analyses, and the assumptions on which they are based, were verified on an experimental machine which consists of a three-phase rotor and alternative solid iron stators, one with copper end rings, and one without copper end rings j the main dimensions of the two stators are identical. Measurements of torque, flux /pole, surface current density and radial power flow were obtained for both stators over a range of frequencies and excitations. Comparison of the measurements on the two stators enabled the individual effects of finite length and saturation to be identified, and the definition of constant equivalent permeability to be verified. The penetration of the peripheral flux into the stator with copper end rings was measured and compared with theoretical penetration curves. Agreement between measured and theoretical results was generally good.

Wireless power charger for light electric vehicles

Wireless power transmission technology is gaining more and more attentions in city transportation applications due to its commensurate power level and efficiency with conductive power transfer means. In this paper, an inductively coupled wireless charging system for 48V light electric vehicle is proposed. The power stages of the system is evaluated and designed, including the high frequency inverter, the resonant network, full bridge rectifier, and the load matching converter. Small signal modeling and linear control technology is applied to the load matching converter for input voltage control, which effectively controls the wireless power flow. The prototype is built with a dsPIC digital signal controller; the experiments are carried out, and the results reveal nature performances of a series-series resonant inductive power charger in terms of frequency, air-gap length, power flow control, and efficiency issues.

A new approach for finding an appropriate combination of texture parameters for classification

This paper suggests an approach for finding an appropriate combination of various parameters for extracting texture features (e.g. choice of spectral band for extracting texture feature, size of the moving window, quantization level of the image, and choice of texture feature etc.) to be used in the classification process. Gray level co-occurrence matrix (GLCM) method has been used for extracting texture from remotely sensed satellite image. Results of the classification of an Indian urban environment using spatial property (texture), derived from spectral and multi-resolution wavelet decomposed images have also been reported. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyze the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. In case of texture features derived using wavelet decomposed image, the parameter ‘decomposition level’ has almost equal relative importance as the size of moving window and the decomposition of images up to level one is sufficient and there is no need to go for further decomposition. It was also observed that the classification incorporating texture features improves the overall classification accuracy in a statistically significant manner in comparison to pure spectral classification.

Evaluation of spectral and texture features for object-based vegetation species classification using Support Vector Machines

The use of appropriate features to characterize an output class or object is critical for all classification problems. This paper evaluates the capability of several spectral and texture features for object-based vegetation classification at the species level using airborne high resolution multispectral imagery. Image-objects as the basic classification unit were generated through image segmentation. Statistical moments extracted from original spectral bands and vegetation index image are used as feature descriptors for image objects (i.e. tree crowns). Several state-of-art texture descriptors such as Gray-Level Co-Occurrence Matrix (GLCM), Local Binary Patterns (LBP) and its extensions are also extracted for comparison purpose. Support Vector Machine (SVM) is employed for classification in the object-feature space. The experimental results showed that incorporating spectral vegetation indices can improve the classification accuracy and obtained better results than in original spectral bands, and using moments of Ratio Vegetation Index obtained the highest average classification accuracy in our experiment. The experiments also indicate that the spectral moment features also outperform or can at least compare with the state-of-art texture descriptors in terms of classification accuracy.