Scale Texture Research Articles

Face presentation attack detection using guided scale texture

Aiming to counter presentation attack (also known as spoofing attack) in face recognition system, a face presentation attack detection (also known as spoofing detection or liveness detection) scheme based on guided scale texture is proposed. In order to minimize the influence of the redundant noise contamination, guided scale space is proposed to reduce the redundancy of the original facial texture and to extract more powerful facial edges. Based on the guided scale space, two guided scale texture descriptors are proposed to extract liveness detection features, and they are guided scale based local binary pattern (GS-LBP) and local guided binary pattern (LGBP). GS-LBP takes advantage of the edge-preserving property of the guided scale space, and joint quantization is used in LGBP to encode the neighboring relationships of the original face and the guided scale face without using additional features. With the guided scale texture features, presentation attack detection is accomplished by the use of a linear support vector machine classifier. Experiments are done with public MSU MFSD, CASIA FASD, Replay-Attack and Replay-Mobile databases, and the results indicate its effectiveness. The proposed method can effectively be applied for countering photo attack and video attack in face recognition systems.

Multispectral and joint colour-texture feature extraction for ore-gangue separation

Ore sorting is a useful tool to remove gangue material from the ore and increase the quality of the ore. The vast developments in the area of artificial intelligence allow fast processing of full color digital images for the preferred investigations. Three different approaches to color texture analysis were used for the classification of associated gangue from limestone and iron ore. All the methods were based on extensions of the co-occurrence matrix method. The first approach was a correlation method, in which co-occurrence matrices are computed both between and within the color bands. In the second approach, joint color-texture features, where color features were extracted from chrominance information and texture features were extracted from luminance information of the color bands. The last approach used grey scale texture features computed on a quantized color image. Results showed that the joint color-texture method was 98% accurate for limestone and 98.4% for iron ore gangue classification. It was further observed that the features showed better accuracy with 64 grey levels quantization.

Performance Analysis of Anisotropic Diffusion Based Colour Texture Descriptors in Industrial Applications

A novel method of colour texture analysis based on anisotropic diffusion for industrial applications is proposed and the performance analysis of colour texture descriptors is examined. The objective of the study is to explore different colour spaces for their suitability in automatic classification of certain textures in industrial applications, namely, granite tiles and wood textures, using computer vision. The directional subbands of digital image of material samples obtained using wavelet transform are subjected to anisotropic diffusion to obtain the texture components. Further, statistical features are extracted from the texture components. The linear discriminant analysis is employed to achieve class separability. The texture descriptors are evaluated on RGB, HSV, YCbCr, Lab colour spaces and compared with gray scale texture descriptors. The k-NN classifier is used for texture classification. For the experimentation, benchmark databases, namely, MondialMarmi and Parquet are considered. The experimental results are encouraging as compared to the state-of-the-art-methods.

Swallowing outcomes for patients with oropharyngeal squamous cell carcinoma treated with primary (chemo)radiation therapy receiving either prophylactic gastrostomy or reactive nasogastric tube: A prospective cohort study.

There is currently no consensus on the optimal feeding route for an oropharyngeal squamous cell cancer (OPSCC) patient without pre-existing dysphagia undergoing chemoradiotherapy. This study aimed to compare the swallowing outcomes for OPSCC patients fed via either prophylactic RIG (pRIG) or reactive nasogastric tube (rNGT). A prospective cohort study. Four head and neck cancer centres in the North of England Cancer Network. Fifty-three participants with OPSCC, on a normal diet pre-(chemo) radiotherapy. Swallowing outcomes for patients with rNGT and pRIG were compared using the following outcome measures administered prospectively at pre-treatment, three and 12 months post-treatment: MD Anderson Dysphagia Inventory (MDADI), Performance Status Scales (Normalcy of Diet), timed water swallow test. Twenty-three patients received pRIG while 30 were planned for a rNGT. No differences in demographics were found between the groups. The rNGT group had a clinically significant higher score on MDADI at 12 months post-treatment. No significant difference was found on a timed water swallow test or diet texture scale. There is no statistical difference for swallowing outcomes in either group. However, patients' in the rNGT group reported a clinically meaningful difference at 1 year, with a trend for them to do better across all measures. Neither group returned to their baseline swallowing function. Further research with a larger sample size is indicated.

Effect of the surface texturing scale on the self-clean function: Correlation between mechanical response and wetting behavior

Two approaches have been established to study the effect of texturing scales on the anti-fingerprint and self-clean performances. In the first, we have analyzed the mechanical response of a dry finger when it is loaded over different textures. A contact model was developed to measure the real touched area. The second approach aims to highlight the effect of texturing on the interaction between fingerprint liquids and textured surfaces. A wetting model was performed to examine the wetting behavior of the previously simulated textures. The results issued from the two approaches were discussed and correlated with each other. It clearly shows the potential effect of texture scales on the achievement of anti-fingerprint functions and delineates the superior functionality of hierarchical textures.

中国新区规划的空间形态与尺度肌理研究

中国新区规划的空间形态与尺度肌理研究

Evaluación de patologías en el concreto usando microscopía óptica

Algunos ensayos tradicionales como la resistencia a la compresión, porosidad total, infiltración de agua, entre otros, resultan útiles a la hora de realizar un análisis de patologías en concretos que han sido atacados por agentes agresores, los cuales van en contra de su durabilidad. Sin embargo, estas pruebas clásicas carecen de herramientas para analizar cómo fue el cambio estructural e interno de la muestra después de ser atacada. Lo que evidencia la necesidad de pensar en otras alternativas y tener en cuenta herramientas más directas como la microscopía, la cual permite hacer un análisis completo tanto macro como micro acerca de la mineralogía, estructura y textura, observando en detalle la composición, fracturas, alteraciones, deformaciones y señales particulares de las muestras. Así,en este trabajo se presenta la aplicabilidad de la petrografía mediante microscopía óptica convencional en el estudio de la degradación del concreto producida por el ataque de agentes agresores. Se muestran resultados como el cambio de color en los agregados, distorsión entre contactos de grano, y cambios en la isotropía de la matriz cementante ante el ataque por fuego. Formación de fases secundarias producto del reemplazo de iones en la matriz que generan fracturamiento y expansión en las probetas expuestas a ataques por sulfato. La aparición de nuevas fases entre la matriz y los agregados y en las fracturas para las muestras sometidas a reacción álcali-sílice. Además, se pudo correlacionar todas estas transformaciones petrográficas con las pérdidas de desempeño mecánico de los concretos.

Rational Design of Hyperbranched Nanowire Systems for Tunable Superomniphobic Surfaces Enabled by Atomic Layer Deposition.

Superomniphobic surfaces display contact angles of θ* > 150° and low contact angle hysteresis with virtually all high and low surface tension liquids. The introduction of hierarchical scales of texture can increase the contact angles and decrease the contact angle hysteresis of superomniphobic surfaces by reducing the solid-liquid contact area. Thus far, it has not been possible to fabricate superomniphobic surfaces with three or more hierarchical scales of texture where the size, spacing, and angular orientation of features within each scale of texture can be independently varied and controlled. Here, we report a method for tunable control of geometry in hyperbranched ZnO nanowire (NW) structures, which in turn enables the rational design and fabrication of superomniphobic surfaces. Branched NWs with tunable density and orientation were grown via a sequential hydrothermal process, in which atomic layer deposition was used for NW seeding, disruption of epitaxy, and selective blocking of NW nucleation. This approach allows for the rational design and optimization of three-level hierarchical structures, in which the geometric parameters of each level of hierarchy can be individually controlled. We demonstrate the coupled relationships between geometry and contact angles for a variety of liquids, which is supported by mathematical models. The highest performing superomniphobic surface was designed with three levels of hierarchy and achieved the following advancing/receding contact angles with water 172°/170°, hexadecane 166°/156°, octane 162°/145°, and heptane 160°/130°.

An evaluation of the effectiveness of low-cost UAVs and structure from motion for geomorphic change detection

The measurement of topography and of topographic change is essential for the study of many geomorphic processes. In recent years, structure from motion (SfM) techniques applied to photographs taken by camera-equipped unmanned aerial vehicles (UAVs) has become a powerful new tool for the generation of high resolution topography. The variety of available UAV systems continues to increase rapidly, but it is not clear whether increased UAV sophistication translates into improved quality of the calculated topography. To evaluate the lower end of the UAV spectrum, a simple low cost UAV was deployed to calculate high resolution topography in the Daan River gorge in western Taiwan, a site with a complicated 3D morphology and a wide range of surface types, making it a challenging site for topographic measurement. Terrestrial lidar surveys were conducted in parallel with UAV surveys in both June and November 2014, enabling an assessment of the reliability of the UAV survey to detect geomorphic changes in the range of 30cm to several meters. A further UAV survey was conducted in June 2015 in order to quantify changes resulting from the 2015 spring monsoon. To evaluate the accuracy of the UAV derived topography, it was compared to terrestrial lidar data collected during the same survey period using the cloud-to-cloud comparison algorithm M3C2. The UAV-generated point clouds match the lidar point clouds well, with RMS errors of 30–40cm; however, the accuracy of the SfM point clouds depends strongly on the characteristics of the surface being considered, with vegetation, water, and small scale texture causing inaccuracies. The lidar and SfM data yield similar maps of change from June to November 2014, with the same areas of geomorphic change detected by both methods. The SfM-generated change map for November 2014 to June 2015 indicates that the 2015 spring monsoon caused erosion throughout the gorge and highlights the importance of event-driven erosion in the Daan River. The results suggest that even very basic UAVs can yield data suitable for measuring geomorphic change on the scale of a channel reach.

Quantitative CT texture analysis for evaluating histologic grade of urothelial carcinoma.

To investigate the feasibility of using CT texture analysis (CTTA) to differentiate between low- versus high-grade urothelial carcinoma. A total of 105 patients with high-grade urothelial carcinoma (HGUC, n=106) and low-grade urothelial carcinoma (LGUC, n=18) were included in this retrospective study. Both unenhanced and enhanced CT images representing the largest cross-sectional area of the tumor were chosen for CTTA performed using TexRAD software. Comparison of texture parameters, mean gray-level intensity (Mean), standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis were made for the objective. Receiver operating characteristic (ROC) analysis was performed and the area under the ROC curve was calculated for texture parameters that were significantly different (P<0.05) for the purpose. Sensitivity (Se), specificity (Sp), positive predictive value, negative predictive value, and accuracy were calculated using the cut-off value of texture parameter with the highest AUC. Compared to HGUC, LGUC had significantly lower Mean (P=0.001), Entropy (P=0.002), and MPP (P<0.001) on unenhanced and enhanced images and lower SD (P=0.048) on enhanced images. There was no significant difference in skewness or kurtosis at any texture scale on unenhanced and enhanced images. A MPP<24.13 at fine texture scale on unenhanced images identified LGUC from HGUC with the highest AUC of 0.779±0.065 (Se=72.2%, Sp=84.9%, PPV=44.8%, NPV=94.7%, and accuracy=83.1%). CTTA proved to be a feasible tool for differentiating LGUC from HGUC. MPP quantified from fine texture scale on unenhanced images was the optimal diagnostic parameter for estimating histologic grade of urothelial carcinoma.

Effect of colistin and tylosin used as feed additives on the performance, diarrhea incidence, and immune response of nursery pigs

For the last several decades, antimicrobial compounds have been used as feed additives to promote piglet growth at weaning, through the prevention of subclinical and clinical disease. However, few studies have assessed the influence of these antibiotics on the immune response of nursery pigs, as well as the relation between performance, health, and immunity of animals that receive feed additives. Therefore, the present study aimed to evaluate the effects of colistin and tylosin when used as feed additives on the performance, incidence of diarrhea, and immune response of nursery pigs. In this study, 72 weaned pigs (average age, 28 days) were allotted into one of three treatment groups: a control group (feed with no antibiotics), tylosin group (feed containing 22 ppm tylosin), and colistin group (feed containing 20 ppm colistin). Weekly, during a five week period, the average daily feed intake, average daily gain, and feed conversion ratio of the pigs were evaluated. Stools were scored daily, in accordance with a fecal texture scale. Blood samples were collected on the day of housing (d0) and on d7, d21, d28, and d35 for immune cell phenotyping. The results of this study showed that piglets in both the colistin and tylosin groups exhibited a significantly higher average daily feed intake, resulting in a higher body weight at the end of the experimental period (d35) when compared with piglets from the control group. Colistin and tylosin also significantly reduced the incidence of diarrhea. Colistin and tylosin modulated the piglets’ immune responses, particularly on d28, by changing the percentage of circulating B lymphocytes, CD4+CD8+ T cells, and the CD4:CD8 ratio.

Multiphase static droplet simulations in hierarchically structured super-hydrophobic surfaces

The surface of first part of study is textured with microscopic pillars of prototypical top geometries as a rectangle. The second one is textured with a hierarchical structure, composed of secondary pillar structures added on the primary texture. The length ratio between two scales of texture is 1:16. We evaluated the non-wetting characteristics of two types of surfaces by measuring CAs as well as the transition from the Wenzel’s to Cassie’s regimes. We measure the Contact angles (CAs), using the Lattice Boltzmann model (LBM), for two different surface configurations. We evaluated the effect of the hierarchical structure; the robustness of the Cassie regime is enhanced and the apparent contact angle is increased by the secondary structures. This is achieved by increasing the energy barrier against the transition between wetting and non-wetting regimes.

Multi-scale MRI spectrum detects differences in myelin integrity between MS lesion types

Background: Lesions with different extents of myelin pathology are found at autopsy in multiple sclerosis (MS), but the differences are not discernible in magnetic resonance imaging (MRI). Objective: To determine whether analysis of the local spectrum in MRI is sensitive to lesion differences in myelin integrity. Methods: We imaged fresh brain slices from 21 MS patients using 1.5T scanners. White matter lesions were identified in T2-weighted MRI, matched to corresponding specimens, and then classified into five categories in histology: pre-active (intact myelin); active, chronic active, chronic inactive (complete demyelination); and remyelinated lesions. Voxel-based frequency spectrum was calculated using T2-weighted MRI to characterize lesion structure (image texture). Results: MRI texture heterogeneity resulting from all spectral scales was greater in completely demyelinated lesions than in myelin-preserved lesions (p = 0.02) and normal-appearing white matter (p < 0.01). Moreover, the spectral distribution pattern over low-frequency scales differentiated demyelinated lesions from remyelinated and pre-active lesions (p < 0.01), where different lesion types also showed distinct texture scales. Conclusion: Using multi-scale spectral analysis, it may be possible for standard MRI to evaluate myelin integrity in MS lesions. This can be critical for monitoring disease activity and assessing remyelination therapies for MS patients.

Friction and wear durability study of epoxy-based polymer (SU-8) composite coatings with talc and graphite as fillers

SU-8, an epoxy-based polymer, is industrially very useful material for fabricating microsystems such as micro-electro-mechanical systems. However, for optimal performance, it is necessary to further improve the mechanical and tribological properties of SU-8. Different weight percentages (wt%) of graphite and talc particles are added to SU-8 for the enhancement of mechanical as well as tribological properties. The composite with the optimized composition of SU-8+15wt% graphite+15wt% talc has shown superior properties compared with pure SU-8 and other composites tested. This composite shows ~4 times lesser steady-state coefficient of friction (~ 0.2), ~3 times higher elastic modulus (~7.97GPa) and ~2 times greater hardness (~0.52GPa) over those of pure SU-8. Also, there is a decrease in the wear rate by ~103 times. This optimized composite, which showed nano to micron scale texturing on the surface, has performed better in comparison with single or mixed fillers with different wt% ratios. The wear mechanism for filler content up to 10wt% was found to be fatigue and delamination, whereas for higher filler content the abrasive wear mechanism was dominant.

Remote sensing image fusion method based on multiscale morphological component analysis

A remote sensing image (RSI) fusion method based on multiscale morphological component analysis (m-MCA) is presented. Our contribution describes a new multiscale sparse image decomposition algorithm called m-MCA, which we apply to RSI fusion. Building on MCA, m-MCA combines curvelet transform bases and local discrete cosine transform bases to build a multiscale decomposition dictionary, and controls the entries of the dictionary to decompose the image into texture components and cartoon components with different scales. The effective scale texture component of high-resolution RSI and the cartoon component of multispectral RSI are selected to reconstruct the fusion image. Compared with state-of-the-art fusion methods, the proposed fusion method obtains higher spatial resolution and lower spectral distortion with reduced computation load in numerical experiments.

Design of periodic nano- and macro-scale textures for high-performance thin-film multi-junction solar cells

Surface textures in thin-film silicon multi-junction solar cells play an important role in gaining the photocurrent of the devices. In this paper, a design of the textures is carried out for the case of amorphous silicon/micro-crystalline silicon (a-Si:H/μc-Si:H) solar cells, employing advanced modelling to determine the textures for defect-free silicon layer growth and to increase the photocurrent. A model of non-conformal layer growth and a hybrid optical modelling approach are used to perform realistic 3D simulations of the structures. The hybrid optical modelling includes rigorous modelling based on the finite element method and geometrical optics models. This enables us to examine the surface texture scaling from nano- to macro-sized (several tens or hundreds of micrometers) texturisation features. First, selected random and periodic nanotextures are examined with respect to critical positions of defect-region formation in Si layers. We show that despite careful selection of a well-suited semi-ellipsoidal periodic texture for defect-free layer growth, defective regions in Si layers of a-Si:H/μc-Si:H cell cannot be avoided if the lateral and vertical dimensions of the nano features are optimised only for high gain in photocurrent. Macro features are favourable for defect-free layer growth, but do not render the photocurrent gains as achieved with light-scattering properties of the optimised nanotextures. Simulation results show that from the optical point of view the semi-ellipsoidal periodic nanotextures with lateral features smaller than 0.4 μm and vertical peak-to-peak heights around or above 0.3 μm are required to achieve a gain in short-circuit current of the top cell with respect to the state-of-the-art random texture (>16% increase), whereas lateral dimensions around 0.8 μm and heights around 0.6 μm lead to a >6% gain in short-circuit current of the bottom cell.

Rotation, scaling and translation invariant texture recognition by Bessel-Fourier moments

The ideal of Bessel-Fourier moments (BFMs) for image analysis and only rotation invariant image cognition has been proposed recently. In this paper, we extend the previous work and propose a new method for rotation, scaling and translation (RST) invariant texture recognition using Bessel-Fourier moments. Compared with the others moments based methods, the radial polynomials of Bessel-Fourier moments have more zeros and these zeros are more evenly distributed. It makes Bessel-Fourier moments more suitable for invariant texture recognition as a generalization of orthogonal complex moments. In the experiment part, we got three testing sets of 16, 24 and 54 texture images by way of translating, rotating and scaling them separately. The correct classification percentages (CCPs) are compared with that of orthogonal Fourier-Mellin moments and Zernike moments based methods in both noise-free and noisy condition. Experimental results validate the conclusion of theoretical derivation: BFM performs better in recognition capability and noise robustness in terms of RST texture recognition under both noise-free and noisy condition when compared with orthogonal Fourier-Mellin moments and Zernike moments based methods.

Bayesian non-parametric gradient histogram estimation for texture-enhanced image deblurring

Image deblurring aims to restore the latent clean image with textures and details from the blurry observation, and is a classical yet active inverse problem in image processing and low level vision. Even though various methods based on image priors have been proposed, the deblurring results by the existing methods usually tend to be over-smoothed and cannot recover fine scale textures. On the other hand, gradient histogram prior has been introduced for texture-enhanced image denoising but the gradient histogram estimation model cannot be used to estimate reference histogram from blurry image. In this paper, we first suggest a gradient histogram preserving (GHP) based image deblurring method, where the reference histogram is parameterized by Hyper-Laplacian distribution. Considering the complexity of blurring process, a Bayesian non-parametric method, Gaussian Processes regression, is utilized for estimating histogram parameters. The experiments demonstrate that, the histogram parameter estimation method is effective, and the proposed GHP based image deblurring method can well restore image textures and improve image quality.

Exploration of Imaging Biomarkers for Predicting Survival of Patients With Advanced Non-Small Cell Lung Cancer Treated With Antiangiogenic Chemotherapy.

The objective of this study was to compare imaging biomarkers, including (18)F-FDG PET, CT perfusion (CTP), and CT texture analysis (CTTA), in predicting the survival of patients with advanced non-small cell lung cancer (NSCLC) treated with antiangiogenic chemotherapy. A total of 35 patients (17 men and 18 women; median age, 64.0 years) with advanced NSCLC treated with antiangiogenic chemotherapy were evaluated. CTP and FDG PET were performed before the therapy, and blood flow, blood volume, mean transit time, and the maximum standardized uptake value (SUV max) of the tumor were measured. Texture parameters, including the mean value of pixels with positive values (MPP) and entropy (a measure of irregularity), were also measured on pretherapeutic unenhanced CT images, using CTTA software with a medium texture scale filtration. The best percent change in the tumor burden was also measured. These image-derived tumor parameters were then compared with progression-free survival (PFS) and overall survival (OS). In univariate Cox regression analysis, MPP and entropy were significantly correlated with PFS (p = 0.01 and p = 0.01, respectively), whereas SUV max, MPP, and entropy were significantly correlated with OS (p = 0.03, p = 0.04, and p = 0.0008, respectively). In Kaplan-Meier analysis, high MPP and low entropy were significantly associated with favorable PFS (p < 0.0001 and p = 0.03, respectively) and OS (p = 0.0009 and p = 0.005, respectively), and low SUV max was significantly associated with favorable OS (p = 0.01). CTP parameters and the best change in the tumor burden had no associations with survival. In multivariate analysis, only entropy was identified as an independent prognostic factor for OS (p = 0.02). CTTA is the optimal imaging biomarker for predicting the survival of patients with advanced NSCLC treated with antiangiogenic chemotherapy.

Novel Methods for Separation of Gangue from Limestone and Coal using Multispectral and Joint Color-Texture Features

Ore sorting is a useful tool to remove gangue material from the ore and increase the quality of the ore. The vast developments in the area of artificial intelligence allow fast processing of full-color digital images for the preferred investigations. The associated gangue minerals from limestone and coal mines were identified using three different approaches. All the methods were based on extensions of the co-occurrence matrix method. In the first method, the color features were extracted from RGB color planes and texture features were extracted using a multispectral extension, in which co-occurrence matrices were computed both between and within the color bands. The second method used joint color-texture features where color features were added to gray scale texture features. The last method used gray scale texture features computed on a quantized color image. Results showed that the accuracy for separation of gangue from limestone, a joint color-texture method was 98 % and for separation of gangue from coal, multispectral method with correlation and joint color-texture method were 100 % respectively. Combined multispectral and joint color-texture methods gave good accuracy with 64 gray levels quantization for separation of gangue from limestone and coal.