Forest Classification Based on Forest texture in Northwest Yunnan Province

International Nuclear Information System (INIS)

Wang, Jinliang; Gao, Yan; Fu, Lei; Wang, Xiaohua

2014-01-01

Forest texture is an intrinsic characteristic and an important visual feature of a forest ecological system. Full utilization of forest texture will be a great help in increasing the accuracy of forest classification based on remote sensed data. Taking Shangri-La as a study area, forest classification has been based on the texture. The results show that: (1) From the texture abundance, texture boundary, entropy as well as visual interpretation, the combination of Grayscale-gradient co-occurrence matrix and wavelet transformation is much better than either one of both ways of forest texture information extraction; (2) During the forest texture information extraction, the size of the texture-suitable window determined by the semi-variogram method depends on the forest type (evergreen broadleaf forest is 3×3, deciduous broadleaf forest is 5×5, etc.). (3)While classifying forest based on forest texture information, the texture factor assembly differs among forests: Variance Heterogeneity and Correlation should be selected when the window is between 3×3 and 5×5; Mean, Correlation, and Entropy should be used when the window in the range of 7×7 to 19×19; and Correlation, Second Moment, and Variance should be used when the range is larger than 21×21

Adaptive Matrices for Color Texture Classification

NARCIS (Netherlands)

Bunte, Kerstin; Giotis, Ioannis; Petkov, Nicolai; Biehl, Michael; Real, P; DiazPernil, D; MolinaAbril, H; Berciano, A; Kropatsch, W

2011-01-01

In this paper we introduce an integrative approach towards color texture classification learned by a supervised framework. Our approach is based on the Generalized Learning Vector Quantization (GLVQ), extended by an adaptive distance measure which is defined in the Fourier domain and 2D Gabor

Texture classification using non-Euclidean Minkowski dilation

Science.gov (United States)

Florindo, Joao B.; Bruno, Odemir M.

2018-03-01

This study presents a new method to extract meaningful descriptors of gray-scale texture images using Minkowski morphological dilation based on the Lp metric. The proposed approach is motivated by the success previously achieved by Bouligand-Minkowski fractal descriptors on texture classification. In essence, such descriptors are directly derived from the morphological dilation of a three-dimensional representation of the gray-level pixels using the classical Euclidean metric. In this way, we generalize the dilation for different values of p in the Lp metric (Euclidean is a particular case when p = 2) and obtain the descriptors from the cumulated distribution of the distance transform computed over the texture image. The proposed method is compared to other state-of-the-art approaches (such as local binary patterns and textons for example) in the classification of two benchmark data sets (UIUC and Outex). The proposed descriptors outperformed all the other approaches in terms of rate of images correctly classified. The interesting results suggest the potential of these descriptors in this type of task, with a wide range of possible applications to real-world problems.

A Color-Texture-Structure Descriptor for High-Resolution Satellite Image Classification

Directory of Open Access Journals (Sweden)

Huai Yu

2016-03-01

Full Text Available Scene classification plays an important role in understanding high-resolution satellite (HRS remotely sensed imagery. For remotely sensed scenes, both color information and texture information provide the discriminative ability in classification tasks. In recent years, substantial performance gains in HRS image classification have been reported in the literature. One branch of research combines multiple complementary features based on various aspects such as texture, color and structure. Two methods are commonly used to combine these features: early fusion and late fusion. In this paper, we propose combining the two methods under a tree of regions and present a new descriptor to encode color, texture and structure features using a hierarchical structure-Color Binary Partition Tree (CBPT, which we call the CTS descriptor. Specifically, we first build the hierarchical representation of HRS imagery using the CBPT. Then we quantize the texture and color features of dense regions. Next, we analyze and extract the co-occurrence patterns of regions based on the hierarchical structure. Finally, we encode local descriptors to obtain the final CTS descriptor and test its discriminative capability using object categorization and scene classification with HRS images. The proposed descriptor contains the spectral, textural and structural information of the HRS imagery and is also robust to changes in illuminant color, scale, orientation and contrast. The experimental results demonstrate that the proposed CTS descriptor achieves competitive classification results compared with state-of-the-art algorithms.

Digitisation of films and texture analysis for digital classification of pulmonary opacities

International Nuclear Information System (INIS)

Desaga, J.F.; Dengler, J.; Wolf, T.; Engelmann, U.; Scheppelmann, D.; Meinzer, H.P.

1988-01-01

The study aimed at evaluating the effect of different methods of digitisation of radiographic films on the digital classification of pulmonary opacities. Test sets from the standard of the International Labour Office (ILO) Classification of Radiographs of Pneumoconiosis were prepared by film digitsation using a scanning microdensitometer or a video digitiser based on a personal computer equipped with a real time digitiser board and a vidicon or a Charge Coupled Device (CCD) camera. Seven different algorithms were used for texture analysis resulting in 16 texture parameters for each region. All methods used for texture analysis were independent of the mean grey value level and the size of the image analysed. Classification was performed by discriminant analysis using the classes from the ILO classification. A hit ratio of at least 85% was achieved for a digitisation by scanner digitisation or the vidicon, while the corresponding results of the CCD camera were significantly less good. Classification by texture analysis of opacities of chest X-rays of pneumoconiosis digitised by a personal computer based video digitiser and a vidicon are of equal quality compared to digitisation by a scanning microdensitometer. Correct classification of 90% was achieved via the described statistical approach. (orig.) [de

Heterogeneous patterns enhancing static and dynamic texture classification

International Nuclear Information System (INIS)

Silva, Núbia Rosa da; Martinez Bruno, Odemir

2013-01-01

Some mixtures, such as colloids like milk, blood, and gelatin, have homogeneous appearance when viewed with the naked eye, however, to observe them at the nanoscale is possible to understand the heterogeneity of its components. The same phenomenon can occur in pattern recognition in which it is possible to see heterogeneous patterns in texture images. However, current methods of texture analysis can not adequately describe such heterogeneous patterns. Common methods used by researchers analyse the image information in a global way, taking all its features in an integrated manner. Furthermore, multi-scale analysis verifies the patterns at different scales, but still preserving the homogeneous analysis. On the other hand various methods use textons to represent the texture, breaking texture down into its smallest unit. To tackle this problem, we propose a method to identify texture patterns not small as textons at distinct scales enhancing the separability among different types of texture. We find sub patterns of texture according to the scale and then group similar patterns for a more refined analysis. Tests were performed in four static texture databases and one dynamical one. Results show that our method provide better classification rate compared with conventional approaches both in static and in dynamic texture.

Classification of interstitial lung disease patterns with topological texture features

Science.gov (United States)

Huber, Markus B.; Nagarajan, Mahesh; Leinsinger, Gerda; Ray, Lawrence A.; Wismüller, Axel

2010-03-01

Topological texture features were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honey-combing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. A set of 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and three Minkowski Functionals (MFs, e.g. MF.euler). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions and the significance thresholds were adjusted for multiple comparisons by the Bonferroni correction. The best classification results were obtained by the MF features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers. The highest accuracy was found for MF.euler (97.5%, 96.6%; for the k-NN and RBFN classifier, respectively). The best standard texture features were the GLCM features 'homogeneity' (91.8%, 87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced topological texture features can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

Textural features for image classification

Science.gov (United States)

Haralick, R. M.; Dinstein, I.; Shanmugam, K.

1973-01-01

Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

Non-Hodgkin lymphoma response evaluation with MRI texture classification

Directory of Open Access Journals (Sweden)

Heinonen Tomi T

2009-06-01

Full Text Available Abstract Background To show magnetic resonance imaging (MRI texture appearance change in non-Hodgkin lymphoma (NHL during treatment with response controlled by quantitative volume analysis. Methods A total of 19 patients having NHL with an evaluable lymphoma lesion were scanned at three imaging timepoints with 1.5T device during clinical treatment evaluation. Texture characteristics of images were analyzed and classified with MaZda application and statistical tests. Results NHL tissue MRI texture imaged before treatment and under chemotherapy was classified within several subgroups, showing best discrimination with 96% correct classification in non-linear discriminant analysis of T2-weighted images. Texture parameters of MRI data were successfully tested with statistical tests to assess the impact of the separability of the parameters in evaluating chemotherapy response in lymphoma tissue. Conclusion Texture characteristics of MRI data were classified successfully; this proved texture analysis to be potential quantitative means of representing lymphoma tissue changes during chemotherapy response monitoring.

Adaptive Matrices and Filters for Color Texture Classification

NARCIS (Netherlands)

Giotis, Ioannis; Bunte, Kerstin; Petkov, Nicolai; Biehl, Michael

In this paper we introduce an integrative approach towards color texture classification and recognition using a supervised learning framework. Our approach is based on Generalized Learning Vector Quantization (GLVQ), extended by an adaptive distance measure, which is defined in the Fourier domain,

Median Robust Extended Local Binary Pattern for Texture Classification.

Science.gov (United States)

Liu, Li; Lao, Songyang; Fieguth, Paul W; Guo, Yulan; Wang, Xiaogang; Pietikäinen, Matti

2016-03-01

Local binary patterns (LBP) are considered among the most computationally efficient high-performance texture features. However, the LBP method is very sensitive to image noise and is unable to capture macrostructure information. To best address these disadvantages, in this paper, we introduce a novel descriptor for texture classification, the median robust extended LBP (MRELBP). Different from the traditional LBP and many LBP variants, MRELBP compares regional image medians rather than raw image intensities. A multiscale LBP type descriptor is computed by efficiently comparing image medians over a novel sampling scheme, which can capture both microstructure and macrostructure texture information. A comprehensive evaluation on benchmark data sets reveals MRELBP's high performance-robust to gray scale variations, rotation changes and noise-but at a low computational cost. MRELBP produces the best classification scores of 99.82%, 99.38%, and 99.77% on three popular Outex test suites. More importantly, MRELBP is shown to be highly robust to image noise, including Gaussian noise, Gaussian blur, salt-and-pepper noise, and random pixel corruption.

Support Vector Machine and Parametric Wavelet-Based Texture Classification of Stem Cell Images

National Research Council Canada - National Science Library

Jeffreys, Christopher

2004-01-01

.... Since colony texture is a major discriminating feature in determining quality, we introduce a non-invasive, semi-automated texture-based stem cell colony classification methodology to aid researchers...

Texture-based classification for characterizing regions on remote sensing images

Science.gov (United States)

Borne, Frédéric; Viennois, Gaëlle

2017-07-01

Remote sensing classification methods mostly use only the physical properties of pixels or complex texture indexes but do not lead to recommendation for practical applications. Our objective was to design a texture-based method, called the Paysages A PRIori method (PAPRI), which works both at pixel and neighborhood level and which can handle different spatial scales of analysis. The aim was to stay close to the logic of a human expert and to deal with co-occurrences in a more efficient way than other methods. The PAPRI method is pixelwise and based on a comparison of statistical and spatial reference properties provided by the expert with local properties computed in varying size windows centered on the pixel. A specific distance is computed for different windows around the pixel and a local minimum leads to choosing the class in which the pixel is to be placed. The PAPRI method brings a significant improvement in classification quality for different kinds of images, including aerial, lidar, high-resolution satellite images as well as texture images from the Brodatz and Vistex databases. This work shows the importance of texture analysis in understanding remote sensing images and for future developments.

Texture Feature Extraction and Classification for Iris Diagnosis

Science.gov (United States)

Ma, Lin; Li, Naimin

Appling computer aided techniques in iris image processing, and combining occidental iridology with the traditional Chinese medicine is a challenging research area in digital image processing and artificial intelligence. This paper proposes an iridology model that consists the iris image pre-processing, texture feature analysis and disease classification. To the pre-processing, a 2-step iris localization approach is proposed; a 2-D Gabor filter based texture analysis and a texture fractal dimension estimation method are proposed for pathological feature extraction; and at last support vector machines are constructed to recognize 2 typical diseases such as the alimentary canal disease and the nerve system disease. Experimental results show that the proposed iridology diagnosis model is quite effective and promising for medical diagnosis and health surveillance for both hospital and public use.

Analysis of the effect of spatial resolution on texture features in the classification of breast masses in mammograms

International Nuclear Information System (INIS)

Rangayyan, R.M.; Nguyen, T.M.; Ayres, F.J.; Nandi, A.K.

2007-01-01

The present study investigates the effect of spatial resolution on co-occurrence matrix-based texture features in discriminating breast lesions as benign masses or malignant tumors. The highest classification result, in terms of the area under the receiver operating characteristics (ROC) curve, of A z 0.74, was obtained at the spatial resolution of 800 μm using all 14 of Haralick's texture features computed using the margins, or ribbons, of the breast masses as seen on mammograms. Furthermore, our study indicates that texture features computed using the ribbons resulted in higher classification accuracy than the same texture features computed using the corresponding regions of interest within the mass boundaries drawn by an expert radiologist. Classification experiments using each single texture feature showed that the texture F 8 , sum entropy, gives consistently high classification results with an average A z of 0.64 across all levels of resolution. At certain levels of resolution, the textures F 5 , F 9 , and F 11 individually gave the highest classification result with A z = 0.70. (orig.)

Texture classification by texton: statistical versus binary.

Directory of Open Access Journals (Sweden)

Zhenhua Guo

Full Text Available Using statistical textons for texture classification has shown great success recently. The maximal response 8 (Statistical_MR8, image patch (Statistical_Joint and locally invariant fractal (Statistical_Fractal are typical statistical texton algorithms and state-of-the-art texture classification methods. However, there are two limitations when using these methods. First, it needs a training stage to build a texton library, thus the recognition accuracy will be highly depended on the training samples; second, during feature extraction, local feature is assigned to a texton by searching for the nearest texton in the whole library, which is time consuming when the library size is big and the dimension of feature is high. To address the above two issues, in this paper, three binary texton counterpart methods were proposed, Binary_MR8, Binary_Joint, and Binary_Fractal. These methods do not require any training step but encode local feature into binary representation directly. The experimental results on the CUReT, UIUC and KTH-TIPS databases show that binary texton could get sound results with fast feature extraction, especially when the image size is not big and the quality of image is not poor.

Cellular automata rule characterization and classification using texture descriptors

Science.gov (United States)

Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.

2018-05-01

The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

Science.gov (United States)

Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

2018-04-01

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

TextureCam Field Test Results from the Mojave Desert, California: Autonomous Instrument Classification of Sediment and Rock Surfaces

Science.gov (United States)

Castano, R.; Abbey, W. J.; Bekker, D. L.; Cabrol, N. A.; Francis, R.; Manatt, K.; Ortega, K.; Thompson, D. R.; Wagstaff, K.

2013-12-01

TextureCam is an intelligent camera that uses integrated image analysis to classify sediment and rock surfaces into basic visual categories. This onboard image understanding can improve the autonomy of exploration spacecraft during the long periods when they are out of contact with operators. This could increase the number of science activities performed in each command cycle by, for example, autonomously targeting science features of opportunity with narrow field of view remote sensing, identifying clean surfaces for autonomous placement of arm-mounted instruments, or by detecting high value images for prioritized downlink. TextureCam incorporates image understanding directly into embedded hardware with a Field Programmable Gate Array (FPGA). This allows the instrument to perform the classification in real time without taxing the primary spacecraft computing resources. We use a machine learning approach in which operators train a statistical model of surface appearance using examples from previously acquired images. A random forest model extrapolates from these training cases, using the statistics of small image patches to characterize the texture of each pixel independently. Applying this model to each pixel in a new image yields a map of surface units. We deployed a prototype instrument in the Cima Volcanic Fields during a series of experiments in May 2013. We imaged each environment with a tripod-mounted RGB camera connected directly to the FPGA board for real time processing. Our first scenario assessed ground surface cover on open terrain atop a weathered volcanic flow. We performed a transect consisting of 16 forward-facing images collected at 1m intervals. We trained the system to categorize terrain into four classes: sediment, basalt cobbles, basalt pebbles, and basalt with iron oxide weathering. Accuracy rates with regards to the fraction of the actual feature that was labeled correctly by the automated system were calculated. Lower accuracy rates were

Quantitative Characterisation of Surface Texture

DEFF Research Database (Denmark)

De Chiffre, Leonardo; Lonardo, P.M.; Trumpold, H.

2000-01-01

This paper reviews the different methods used to give a quantitative characterisation of surface texture. The paper contains a review of conventional 2D as well as 3D roughness parameters, with particular emphasis on recent international standards and developments. It presents new texture...

Magnetic resonance imaging texture analysis classification of primary breast cancer

International Nuclear Information System (INIS)

Waugh, S.A.; Lerski, R.A.; Purdie, C.A.; Jordan, L.B.; Vinnicombe, S.; Martin, P.; Thompson, A.M.

2016-01-01

Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

Magnetic resonance imaging texture analysis classification of primary breast cancer

Energy Technology Data Exchange (ETDEWEB)

Waugh, S.A.; Lerski, R.A. [Ninewells Hospital and Medical School, Department of Medical Physics, Dundee (United Kingdom); Purdie, C.A.; Jordan, L.B. [Ninewells Hospital and Medical School, Department of Pathology, Dundee (United Kingdom); Vinnicombe, S. [University of Dundee, Division of Imaging and Technology, Ninewells Hospital and Medical School, Dundee (United Kingdom); Martin, P. [Ninewells Hospital and Medical School, Department of Clinical Radiology, Dundee (United Kingdom); Thompson, A.M. [University of Texas MD Anderson Cancer Center, Department of Surgical Oncology, Houston, TX (United States)

2016-02-15

Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

Parametric classification of handvein patterns based on texture features

Science.gov (United States)

Al Mahafzah, Harbi; Imran, Mohammad; Supreetha Gowda H., D.

2018-04-01

In this paper, we have developed Biometric recognition system adopting hand based modality Handvein,which has the unique pattern for each individual and it is impossible to counterfeit and fabricate as it is an internal feature. We have opted in choosing feature extraction algorithms such as LBP-visual descriptor, LPQ-blur insensitive texture operator, Log-Gabor-Texture descriptor. We have chosen well known classifiers such as KNN and SVM for classification. We have experimented and tabulated results of single algorithm recognition rate for Handvein under different distance measures and kernel options. The feature level fusion is carried out which increased the performance level.

Influence of surface roughness on the friction property of textured surface

OpenAIRE

Yuankai Zhou; Hua Zhu; Wenqian Zhang; Xue Zuo; Yan Li; Jianhua Yang

2015-01-01

In contrast with dimple textures, surface roughness is a texture at the micro-scale, essentially which will influence the load-bearing capacity of lubricant film. The numerical simulation was carried out to investigate the influence of surface roughness on friction property of textured surface. The lubricant film pressure was obtained using the method of computational fluid dynamics according to geometric model of round dimple, and the renormalization-group k–ε turbulent model was adopted in ...

Woven fabric defects detection based on texture classification algorithm

International Nuclear Information System (INIS)

Ben Salem, Y.; Nasri, S.

2011-01-01

In this paper we have compared two famous methods in texture classification to solve the problem of recognition and classification of defects occurring in a textile manufacture. We have compared local binary patterns method with co-occurrence matrix. The classifier used is the support vector machines (SVM). The system has been tested using TILDA database. The results obtained are interesting and show that LBP is a good method for the problems of recognition and classifcation defects, it gives a good running time especially for the real time applications.

A statistical-textural-features based approach for classification of solid drugs using surface microscopic images.

Science.gov (United States)

Tahir, Fahima; Fahiem, Muhammad Abuzar

2014-01-01

The quality of pharmaceutical products plays an important role in pharmaceutical industry as well as in our lives. Usage of defective tablets can be harmful for patients. In this research we proposed a nondestructive method to identify defective and nondefective tablets using their surface morphology. Three different environmental factors temperature, humidity and moisture are analyzed to evaluate the performance of the proposed method. Multiple textural features are extracted from the surface of the defective and nondefective tablets. These textural features are gray level cooccurrence matrix, run length matrix, histogram, autoregressive model and HAAR wavelet. Total textural features extracted from images are 281. We performed an analysis on all those 281, top 15, and top 2 features. Top 15 features are extracted using three different feature reduction techniques: chi-square, gain ratio and relief-F. In this research we have used three different classifiers: support vector machine, K-nearest neighbors and naïve Bayes to calculate the accuracies against proposed method using two experiments, that is, leave-one-out cross-validation technique and train test models. We tested each classifier against all selected features and then performed the comparison of their results. The experimental work resulted in that in most of the cases SVM performed better than the other two classifiers.

Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm.

Science.gov (United States)

Al Ajmi, Eiman; Forghani, Behzad; Reinhold, Caroline; Bayat, Maryam; Forghani, Reza

2018-06-01

There is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm. Forty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set. Using multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis. Multi-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours. • We present and validate a paradigm for texture analysis of DECT scans. • Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis. • DECT texture analysis has high accura\\cy for diagnosis of benign parotid tumours. • DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.

Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses

Science.gov (United States)

Agüera, Francisco; Aguilar, Fernando J.; Aguilar, Manuel A.

The area occupied by plastic-covered greenhouses has undergone rapid growth in recent years, currently exceeding 500,000 ha worldwide. Due to the vast amount of input (water, fertilisers, fuel, etc.) required, and output of different agricultural wastes (vegetable, plastic, chemical, etc.), the environmental impact of this type of production system can be serious if not accompanied by sound and sustainable territorial planning. For this, the new generation of satellites which provide very high resolution imagery, such as QuickBird and IKONOS can be useful. In this study, one QuickBird and one IKONOS satellite image have been used to cover the same area under similar circumstances. The aim of this work was an exhaustive comparison of QuickBird vs. IKONOS images in land-cover detection. In terms of plastic greenhouse mapping, comparative tests were designed and implemented, each with separate objectives. Firstly, the Maximum Likelihood Classification (MLC) was applied using five different approaches combining R, G, B, NIR, and panchromatic bands. The combinations of the bands used, significantly influenced some of the indexes used to classify quality in this work. Furthermore, the quality classification of the QuickBird image was higher in all cases than that of the IKONOS image. Secondly, texture features derived from the panchromatic images at different window sizes and with different grey levels were added as a fifth band to the R, G, B, NIR images to carry out the MLC. The inclusion of texture information in the classification did not improve the classification quality. For classifications with texture information, the best accuracies were found in both images for mean and angular second moment texture parameters. The optimum window size in these texture parameters was 3×3 for IK images, while for QB images it depended on the quality index studied, but the optimum window size was around 15×15. With regard to the grey level, the optimum was 128. Thus, the

Three-dimensional textural features of conventional MRI improve diagnostic classification of childhood brain tumours.

Science.gov (United States)

Fetit, Ahmed E; Novak, Jan; Peet, Andrew C; Arvanitits, Theodoros N

2015-09-01

The aim of this study was to assess the efficacy of three-dimensional texture analysis (3D TA) of conventional MR images for the classification of childhood brain tumours in a quantitative manner. The dataset comprised pre-contrast T1 - and T2-weighted MRI series obtained from 48 children diagnosed with brain tumours (medulloblastoma, pilocytic astrocytoma and ependymoma). 3D and 2D TA were carried out on the images using first-, second- and higher order statistical methods. Six supervised classification algorithms were trained with the most influential 3D and 2D textural features, and their performances in the classification of tumour types, using the two feature sets, were compared. Model validation was carried out using the leave-one-out cross-validation (LOOCV) approach, as well as stratified 10-fold cross-validation, in order to provide additional reassurance. McNemar's test was used to test the statistical significance of any improvements demonstrated by 3D-trained classifiers. Supervised learning models trained with 3D textural features showed improved classification performances to those trained with conventional 2D features. For instance, a neural network classifier showed 12% improvement in area under the receiver operator characteristics curve (AUC) and 19% in overall classification accuracy. These improvements were statistically significant for four of the tested classifiers, as per McNemar's tests. This study shows that 3D textural features extracted from conventional T1 - and T2-weighted images can improve the diagnostic classification of childhood brain tumours. Long-term benefits of accurate, yet non-invasive, diagnostic aids include a reduction in surgical procedures, improvement in surgical and therapy planning, and support of discussions with patients' families. It remains necessary, however, to extend the analysis to a multicentre cohort in order to assess the scalability of the techniques used. Copyright © 2015 John Wiley & Sons, Ltd.

The structure of surface texture knowledge

International Nuclear Information System (INIS)

Yan Wang; Scott, Paul J; Jiang Xiangqian

2005-01-01

This research aims to create an intelligent knowledge-based system for engineering and bio-medical engineering surface texture, which will provide expert knowledge of surface texture to link surface function, specification of micro- and nano-geometry through manufacture, and verification. The intelligent knowledge base should be capable of incorporating knowledge from multiple sources (standards, books, experts, etc), adding new knowledge from these sources and still remain a coherent reliable system. A new data model based on category theory will be adopted to construct this system

Application of texture analysis method for mammogram density classification

Science.gov (United States)

Nithya, R.; Santhi, B.

2017-07-01

Mammographic density is considered a major risk factor for developing breast cancer. This paper proposes an automated approach to classify breast tissue types in digital mammogram. The main objective of the proposed Computer-Aided Diagnosis (CAD) system is to investigate various feature extraction methods and classifiers to improve the diagnostic accuracy in mammogram density classification. Texture analysis methods are used to extract the features from the mammogram. Texture features are extracted by using histogram, Gray Level Co-Occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), Gray Level Difference Matrix (GLDM), Local Binary Pattern (LBP), Entropy, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT), Gabor transform and trace transform. These extracted features are selected using Analysis of Variance (ANOVA). The features selected by ANOVA are fed into the classifiers to characterize the mammogram into two-class (fatty/dense) and three-class (fatty/glandular/dense) breast density classification. This work has been carried out by using the mini-Mammographic Image Analysis Society (MIAS) database. Five classifiers are employed namely, Artificial Neural Network (ANN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Experimental results show that ANN provides better performance than LDA, NB, KNN and SVM classifiers. The proposed methodology has achieved 97.5% accuracy for three-class and 99.37% for two-class density classification.

Reliable Fault Classification of Induction Motors Using Texture Feature Extraction and a Multiclass Support Vector Machine

Directory of Open Access Journals (Sweden)

Jia Uddin

2014-01-01

Full Text Available This paper proposes a method for the reliable fault detection and classification of induction motors using two-dimensional (2D texture features and a multiclass support vector machine (MCSVM. The proposed model first converts time-domain vibration signals to 2D gray images, resulting in texture patterns (or repetitive patterns, and extracts these texture features by generating the dominant neighborhood structure (DNS map. The principal component analysis (PCA is then used for the purpose of dimensionality reduction of the high-dimensional feature vector including the extracted texture features due to the fact that the high-dimensional feature vector can degrade classification performance, and this paper configures an effective feature vector including discriminative fault features for diagnosis. Finally, the proposed approach utilizes the one-against-all (OAA multiclass support vector machines (MCSVMs to identify induction motor failures. In this study, the Gaussian radial basis function kernel cooperates with OAA MCSVMs to deal with nonlinear fault features. Experimental results demonstrate that the proposed approach outperforms three state-of-the-art fault diagnosis algorithms in terms of fault classification accuracy, yielding an average classification accuracy of 100% even in noisy environments.

Laser surface textured titanium alloy (Ti–6Al–4V): Part 1 – Surface characterization

Energy Technology Data Exchange (ETDEWEB)

Pfleging, Wilhelm [Karlsruhe Institute of Technology, IAM-AWP, P.O. Box 3640, 76021 Karlsruhe (Germany); Karlsruhe Nano Micro Facility, H.-von-Helmholtz-Pl. 1, 76344 Egg.-Leopoldshafen (Germany); Kumari, Renu [Department of Metal. and Maters. Eng., I. I. T. Kharagpur, WB 721302 (India); Besser, Heino [Karlsruhe Institute of Technology, IAM-AWP, P.O. Box 3640, 76021 Karlsruhe (Germany); Scharnweber, Tim [Karlsruhe Institute of Technology, IBG-1, P.O. Box 3640, 76021 Karlsruhe (Germany); Majumdar, Jyotsna Dutta, E-mail: jyotsna@metal.iitkgp.ernet.in [Department of Metal. and Maters. Eng., I. I. T. Kharagpur, WB 721302 (India)

2015-11-15

Highlights: • Texturing of Ti–6Al–4V with linear and dimple patterns are developed with ArF laser. • Linear textures have width of 25 μm and are at an interval of 20 μm. • Dimple textures are equi-spaced and have a diameter of 60 μm. • Significant refinement of microstructure in textured zone as compared to substrate. • Increased wettability of the textured surface against simulated body fluid. - Abstract: In the present study, a detailed study of the characterization of laser-surface textured titanium alloy (Ti–6Al–4V) with line and dimple geometry developed by using an ArF excimer laser operating at a wavelength of 193 nm with a pulse length of 5 ns is undertaken. The characterization of the textured surface (both the top surface and cross section) is carried out by scanning electron microscopy, electron back scattered diffraction (EBSD) technique and X-ray diffraction techniques. There is refinement of microstructure along with presence of titanium oxides (rutile, anatase and few Ti{sub 2}O{sub 3} phase) in the textured surface as compared to as-received one. The area fractions of linear texture and dimple texture measured by image analysis software are 45% and 20%, respectively. The wettability is increased after laser texturing. The total surface energy is decreased due to linear (29.6 mN/m) texturing and increased due to dimple (67.6 mN/m) texturing as compared to as-received Ti–6Al–4V (37 mN/m). The effect of polar component is more in influencing the surface energy of textured surface.

Laser surface textured titanium alloy (Ti–6Al–4V): Part 1 – Surface characterization

International Nuclear Information System (INIS)

Pfleging, Wilhelm; Kumari, Renu; Besser, Heino; Scharnweber, Tim; Majumdar, Jyotsna Dutta

2015-01-01

Highlights: • Texturing of Ti–6Al–4V with linear and dimple patterns are developed with ArF laser. • Linear textures have width of 25 μm and are at an interval of 20 μm. • Dimple textures are equi-spaced and have a diameter of 60 μm. • Significant refinement of microstructure in textured zone as compared to substrate. • Increased wettability of the textured surface against simulated body fluid. - Abstract: In the present study, a detailed study of the characterization of laser-surface textured titanium alloy (Ti–6Al–4V) with line and dimple geometry developed by using an ArF excimer laser operating at a wavelength of 193 nm with a pulse length of 5 ns is undertaken. The characterization of the textured surface (both the top surface and cross section) is carried out by scanning electron microscopy, electron back scattered diffraction (EBSD) technique and X-ray diffraction techniques. There is refinement of microstructure along with presence of titanium oxides (rutile, anatase and few Ti_2O_3 phase) in the textured surface as compared to as-received one. The area fractions of linear texture and dimple texture measured by image analysis software are 45% and 20%, respectively. The wettability is increased after laser texturing. The total surface energy is decreased due to linear (29.6 mN/m) texturing and increased due to dimple (67.6 mN/m) texturing as compared to as-received Ti–6Al–4V (37 mN/m). The effect of polar component is more in influencing the surface energy of textured surface.

Study on tribological properties of multi-layer surface texture on Babbitt alloys surface

Science.gov (United States)

Zhang, Dongya; Zhao, Feifei; Li, Yan; Li, Pengyang; Zeng, Qunfeng; Dong, Guangneng

2016-12-01

To improve tribological properties of Babbitt alloys, multi-layer surface texture consisted of the main grooves and secondary micro-dimples are fabricated on the Babbitt substrate through laser pulse ablation. The tribological behaviors of multi-layer surface texture are investigated using a rotating type pin-on-disc tribo-meter under variation sliding speeds, and the film pressure distributions on the textured surfaces are simulated using computational fluid dynamics (CFD) method for elucidating the possible mechanisms. The results suggest that: (i) the multi-layer surface texture can reduce friction coefficient of Babbitt alloy, which has lowest friction coefficient of 0.03, in case of the groove parameter of 300 μm width and 15% of area density; (ii) the improvement effect may be more sensitive to the groove area density and the siding speed, and the textured surface with lower area density has lower friction coefficient under high sliding speed. Based on the reasons of (i) the secondary micro-dimples on Babbitt alloy possesses a hydrophobicity surface and (ii) the CFD analysis indicates that main grooves enhancing hydrodynamic effect, thus the multi-layer surface texture is regarded as dramatically improve the lubricating properties of the Babbitt alloy.

A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data

Directory of Open Access Journals (Sweden)

Salman Qadri

2016-01-01

Full Text Available The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land. A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately. Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image. The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI. Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data. For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class. By implementing a cross validation method (80-20, we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively.

Influence of surface roughness on the friction property of textured surface

Directory of Open Access Journals (Sweden)

Yuankai Zhou

2015-02-01

Full Text Available In contrast with dimple textures, surface roughness is a texture at the micro-scale, essentially which will influence the load-bearing capacity of lubricant film. The numerical simulation was carried out to investigate the influence of surface roughness on friction property of textured surface. The lubricant film pressure was obtained using the method of computational fluid dynamics according to geometric model of round dimple, and the renormalization-group k–ε turbulent model was adopted in the computation. The numerical simulation results suggest that there is an optimum dimensionless surface roughness, and near this value, the maximum load-bearing capacity can be achieved. The load-bearing capacity is determined by the surface texture, the surface roughness, and the interaction between them. To get information of friction coefficient, the experiments were conducted. This experiment was used to evaluate the simulation. The experimental results show that for the frequency of 4 and 6 Hz, friction coefficient decreases at first and then increases with decreasing surface roughness, which indicates that there exists the optimum region of surface roughness leading to the best friction reduction effect, and it becomes larger when area fractions increase from 2% to 10%. The experimental results agree well with the simulation results.

Control and characterization of textured, hydrophobic ionomer surfaces

Science.gov (United States)

Wang, Xueyuan

Polymer thin films are of increasing interest in many industrial and technological applications. Superhydrophobic, self-cleaning surfaces have attracted a lot of attention for their application in self-cleaning, anti-sticking coatings, stain resistance, or anti-contamination surfaces in diverse technologies, including medical, transportation, textiles, electronics and paints. This thesis focuses on the preparation of nanometer to micrometer-size particle textured surfaces which are desirable for super water repellency. Textured surfaces consisting of nanometer to micrometer-sized lightly sulfonated polystyrene ionomer (SPS) particles were prepared by rapid evaporation of the solvent from a dilute polymer solution cast onto silica. The effect of the solvent used to spin coat the film, the molecular weight of the ionomer, and the rate of solvent evaporation were investigated. The nano-particle or micron-particle textured ionomer surfaces were prepared by either spin coating or solution casting ionomer solutions at controlled evaporation rates. The surface morphologies were consistent with a spinodal decomposition mechanism where the surface first existed as a percolated-like structure and then ripened into droplets if molecular mobility was retained for sufficient time. The SPS particles or particle aggregates were robust and resisted deformation even after annealing at 120°C for one week. The water contact angles on as-prepared surfaces were relatively low, ~ 90° since the polar groups in ionomer reduce the surface hydrophobicity. After chemical vapor deposition of 1H,1H,2H,2H-perfluorooctyltrichlorosilane, the surface contact angles increased to ~ 109° on smooth surfaces and ~140° on the textured surfaces. Water droplets stuck to these surfaces even when tilted 90 degrees. Superhydrophobic surfaces were prepared by spraying coating ionomer solutions and Chemical Vapor Deposition (CVD) of 1H,1H,2H,2H-perfluorooctyltrichlorosilane onto textured surfaces. The

Friction behavior of nano-textured polyimide surfaces measured by AFM colloidal probe

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiaoliang [College of Equipment Manufacturing, Hebei University of Engineering, Handan 056038 (China); State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000 (China); Wu, Chunxia; Che, Hongwei; Hou, Junxian [College of Equipment Manufacturing, Hebei University of Engineering, Handan 056038 (China); Jia, Junhong, E-mail: jhjia@licp.cas.cn [State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000 (China)

2014-11-30

Highlights: • Flat PI film and nano-textured PI film were prepared by spin-coating process. • The nano-textured PI surface has effectively reduced the adhesion and friction. • Friction increased with the increasing of contact area and adhesion. • The growth rate of friction decreased with the increasing of applied load. - Abstract: Flat polyimide (PI) film and silicon dioxide nanoparticle-textured PI film were prepared by means of the spin-coating technique. The adhesion and friction properties of the flat PI surface and nano-textured PI surface were investigated by a series of Atomic force microscope (AFM) colloidal probes. Experimental results revealed that the nano-textured PI surface can significantly reduce the adhesive force and friction force, compared with the flat PI surface. The main reason is that the nano-textures can reduce the contact area between the sample surface and colloidal probe. The effect of colloidal probe size on the friction behavior of the flat and nano-textured PI surfaces was evaluated. The adhesive force and friction force of nano-textured PI surface were increased with the increasing of the size of interacting pairs (AFM colloidal probe) due to the increased contact area. Moreover, the friction forces of flat and nano-textured PI surfaces were increased with applied load and sliding velocity.

A Study of Hand Back Skin Texture Patterns for Personal Identification and Gender Classification

Directory of Open Access Journals (Sweden)

Jin Xie

2012-06-01

Full Text Available Human hand back skin texture (HBST is often consistent for a person and distinctive from person to person. In this paper, we study the HBST pattern recognition problem with applications to personal identification and gender classification. A specially designed system is developed to capture HBST images, and an HBST image database was established, which consists of 1,920 images from 80 persons (160 hands. An efficient texton learning based method is then presented to classify the HBST patterns. First, textons are learned in the space of filter bank responses from a set of training images using the -minimization based sparse representation (SR technique. Then, under the SR framework, we represent the feature vector at each pixel over the learned dictionary to construct a representation coefficient histogram. Finally, the coefficient histogram is used as skin texture feature for classification. Experiments on personal identification and gender classification are performed by using the established HBST database. The results show that HBST can be used to assist human identification and gender classification.

Wettability transition of laser textured brass surfaces inside different mediums

Science.gov (United States)

Yan, Huangping; Abdul Rashid, Mohamed Raiz B.; Khew, Si Ying; Li, Fengping; Hong, Minghui

2018-01-01

Hydrophobic surface on brass has attracted intensive attention owing to its importance in scientific research and practical applications. Laser texturing provides a simple and promising method to achieve it. Reducing wettability transition time from hydrophilicity to hydrophobicity or superhydrophobicity remains a challenge. Herein, wettability transition of brass surfaces with hybrid micro/nano-structures fabricated by laser texturing was investigated by immersing the samples inside different mediums. Scanning electron microscopy, energy-dispersive X-ray analysis, X-ray photoelectron spectroscopy and surface contact angle measurement were employed to characterize surface morphology, chemical composition and wettability of the fabricated surfaces of brass samples. Wettability transition time from hydrophilicity to hydrophobicity was shortened by immersion into isopropyl alcohol for a period of 3 h as a result of the absorption and accumulation of organic substances on the textured brass surface. When the textured brass sample was immersed into sodium bicarbonate solution, flower-like structures on the sample surface played a key role in slowing down wettability transition. Moreover, it had the smallest steady state contact angle as compared to the others. This study provides a facile method to construct textured surfaces with tunable wetting behaviors and effectively extend the industrial applications of brass.

Evaluation of Tire/Surfacing/Base Contact Stresses and Texture Depth

Directory of Open Access Journals (Sweden)

W.J.vdM. Steyn

2015-03-01

Full Text Available Tire rolling resistance has a major impact on vehicle fuel consumption. Rolling resistance is the loss of energy due to the interaction between the tire and the pavement surface. This interaction is a complicated combination of stresses and strains which depend on both tire and pavement related factors. These include vehicle speed, vehicle weight, tire material and type, road camber, tire inflation pressure, pavement surfacing texture etc. In this paper the relationship between pavement surface texture depth and tire/surfacing contact stress and area is investigated. Texture depth and tire/surfacing contact stress were measured for a range of tire inflation pressures on five different pavement surfaces. In the analysis the relationship between texture and the generated contact stresses as well as the contact stress between the surfacing and base layer are presented and discussed, and the anticipated effect of these relationships on the rolling resistance of vehicles on the surfacings, and subsequent vehicle fuel economy discussed.

Effect of surface texturing on friction properties of WC/Co cemented carbide

International Nuclear Information System (INIS)

Wu, Ze; Deng, Jianxin; Xing, Youqiang; Cheng, Hongwei; Zhao, Jun

2012-01-01

Highlights: ► Tribological properties of surface textured WC/Co cemented carbide were studied. ► Textured surfaces have better performance of antifriction and antiwear. ► Area density of textures has significant effect on tribological performance. -- Abstract: An experimental study was carried out to investigate the tribological properties of different surface textured WC/Co cemented carbide. The influence of applied load, sliding speed and area density of textures on frictional performance of surface textured patterns was investigated by Taguchi method. Results show that the textured surfaces filled with molybdenum disulfide solid lubricants can reduce the average friction coefficient, wear rates of Ti–6Al–4V alloy balls and adhesion of Ti–6Al–4V alloy materials on the worn track of cemented carbide compared with un-textured ones. Variance analysis of the experimental data indicates that the area density of textures plays major contribution of both average friction coefficient and wear rate of Ti–6Al–4V alloy balls. Higher area density of textures is beneficial to improve tribological performance of the cemented carbide samples. Sliding speed seems to have no effect on the tribological performance of textured surfaces within the reliability interval of 90%. Applied load has effect on both average friction coefficient and wear rate of Ti–6Al–4V alloy balls at the reliability interval of 95%.

Pure Surface Texture Mapping Technology and it's Application for Mirror Image

Directory of Open Access Journals (Sweden)

Wei Feng Wang

2013-02-01

Full Text Available Based on the study of pure surface texture mapping technology, pure texture surface rendering method is proposed. The method is combined pure surface texture rendering and view mirror, real-time rendering has an index of refraction, reflection, and the flow of water ripple effect. Through the experimental verification of the validity of the algorithm.

Importance of Surface Texture to Infrared Remote Sensing Interpretations

Science.gov (United States)

Kirkland, L. E.; Adams, P. M.; Herr, K. C.; Salisbury, J. W.

2001-11-01

Thermal infrared remote sensing may be used to identify minerals present on the surface using diagnostic spectral bands. As band depth (spectral contrast) exhibited by the mineral increases, the mineral is easier to detect. In order to determine the expected spectral contrast, thermal infrared spectra of typical mineral endmembers are commonly measured in the laboratory. For example, for calcite, well-crystalline limestone is commonly studied. However, carbonates occur in several forms, including thin coatings, indurated carbonate (calcrete), and hot springs deposits. Different formation pathways may cause different microstructures and surface textures. This in turn can also affect the surface texture of the weathered material. Different surface textures can affect the measured band contrast, through roughness that causes a cavity (hohlraum) effect, and particle size and roughness on a scale that causes volume scattering. Thus since detection limits vary with the spectral contrast, surface texture can be an important variable in how detectable a mineral is. To study these issues, we have examined limestone and calcrete deposits at Mormon Mesa, Nevada that have two distinctly different microstructures and surface texture [Kirkland et al., 2001]. The limestone studied has larger grains and the grains frequently have flat, smooth surfaces on the order of 10-50 microns in cross-section length. The calcrete has smaller, more angular calcite grains, which exhibit almost no flat surfaces longer than 5 microns in cross-section length. We will show scanning electron microscope images to compare the different microstructures and surface textures of both the fresh and weathered surfaces, and we will show corresponding thermal infrared spectra to illustrate the different spectral signatures. The results demonstrate the importance of understanding the microstructure of mineral deposits to accurately interpret infrared remote sensing data, especially for studies that lack ground

Ethnicity prediction and classification from iris texture patterns: A survey on recent advances

CSIR Research Space (South Africa)

Mabuza-Hocquet, Gugulethu

2017-03-01

Full Text Available The prediction and classification of ethnicity based on iris texture patterns using image processing, artificial intelligence and computer vision techniques is still a recent topic in iris biometrics. While the large body of knowledge and research...

An Active Patch Model for Real World Texture and Appearance Classification.

Science.gov (United States)

Mao, Junhua; Zhu, Jun; Yuille, Alan L

2014-09-06

This paper addresses the task of natural texture and appearance classification. Our goal is to develop a simple and intuitive method that performs at state of the art on datasets ranging from homogeneous texture (e.g., material texture), to less homogeneous texture (e.g., the fur of animals), and to inhomogeneous texture (the appearance patterns of vehicles). Our method uses a bag-of-words model where the features are based on a dictionary of active patches. Active patches are raw intensity patches which can undergo spatial transformations (e.g., rotation and scaling) and adjust themselves to best match the image regions. The dictionary of active patches is required to be compact and representative, in the sense that we can use it to approximately reconstruct the images that we want to classify. We propose a probabilistic model to quantify the quality of image reconstruction and design a greedy learning algorithm to obtain the dictionary. We classify images using the occurrence frequency of the active patches. Feature extraction is fast (about 100 ms per image) using the GPU. The experimental results show that our method improves the state of the art on a challenging material texture benchmark dataset (KTH-TIPS2). To test our method on less homogeneous or inhomogeneous images, we construct two new datasets consisting of appearance image patches of animals and vehicles cropped from the PASCAL VOC dataset. Our method outperforms competing methods on these datasets.

SURFACE TEXTURE ANALYSIS FOR FUNCTIONALITY CONTROL

DEFF Research Database (Denmark)

De Chiffre, Leonardo; Andreasen, Jan Lasson; Tosello, Guido

This document is used in connection with three exercises of 3 hours duration as a part of the course VISION ONLINE – One week course on Precision & Nanometrology. The exercises concern surface texture analysis for functionality control, in connection with three different case stories. This docume...... contains a short description of each case story, 3-D roughness parameters analysis and relation with the product’s functionality.......This document is used in connection with three exercises of 3 hours duration as a part of the course VISION ONLINE – One week course on Precision & Nanometrology. The exercises concern surface texture analysis for functionality control, in connection with three different case stories. This document...

Dropwise condensation on inclined textured surfaces

CERN Document Server

Khandekar, Sameer

2014-01-01

Dropwise Condensation on Textured Surfaces presents a holistic framework for understanding dropwise condensation through mathematical modeling and meaningful experiments. The book presents a review of the subject required to build up models as well as to design experiments. Emphasis is placed on the effect of physical and chemical texturing and their effect on the bulk transport phenomena. Application of the model to metal vapor condensation is of special interest. The unique behavior of liquid metals, with their low Prandtl number and high surface tension, is also discussed. The model predicts instantaneous drop size distribution for a given level of substrate subcooling and derives local as well as spatio-temporally averaged heat transfer rates and wall shear stress.

Friction reduction using discrete surface textures: principle and design

International Nuclear Information System (INIS)

Hsu, Stephen M; Jing, Yang; Hua, Diann; Zhang, Huan

2014-01-01

There have been many reports on the use of dimples, grooves, and other surface textures to control friction in sliding interfaces. The effectiveness of surface textures in friction reduction has been demonstrated in conformal contacts under high speed low load applications such as mechanical seals and automotive water pump seals, etc., resulting in reduced friction and longer durability. For sliding components with higher contact pressures or lower speeds, conflicting results were reported. Reasons for the inconsistency may be due to the differences in texture fabrication techniques, lack of dimple size and shape uniformity, and different tester used. This paper examines the basic principles on which surface textural patterns influence friction under the three principle lubrication regimes: hydrodynamic, elastohydrodynamic, and boundary lubrication regimes. Our findings suggest that each regime requires specific dimple size, shape, depth, and areal density to achieve friction reduction. Control experiments were also conducted to explore mechanisms of friction reduction. The dimple geometric shape and the dimple's orientation with respect to the sliding direction influence friction significantly. The underlying mechanisms for friction control via textures are discussed. (paper)

Deep neural networks for texture classification-A theoretical analysis.

Science.gov (United States)

Basu, Saikat; Mukhopadhyay, Supratik; Karki, Manohar; DiBiano, Robert; Ganguly, Sangram; Nemani, Ramakrishna; Gayaka, Shreekant

2018-01-01

We investigate the use of Deep Neural Networks for the classification of image datasets where texture features are important for generating class-conditional discriminative representations. To this end, we first derive the size of the feature space for some standard textural features extracted from the input dataset and then use the theory of Vapnik-Chervonenkis dimension to show that hand-crafted feature extraction creates low-dimensional representations which help in reducing the overall excess error rate. As a corollary to this analysis, we derive for the first time upper bounds on the VC dimension of Convolutional Neural Network as well as Dropout and Dropconnect networks and the relation between excess error rate of Dropout and Dropconnect networks. The concept of intrinsic dimension is used to validate the intuition that texture-based datasets are inherently higher dimensional as compared to handwritten digits or other object recognition datasets and hence more difficult to be shattered by neural networks. We then derive the mean distance from the centroid to the nearest and farthest sampling points in an n-dimensional manifold and show that the Relative Contrast of the sample data vanishes as dimensionality of the underlying vector space tends to infinity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Filtering Color Mapped Textures and Surfaces

OpenAIRE

Heitz , Eric; Nowrouzezahrai , Derek; Poulin , Pierre; Neyret , Fabrice

2013-01-01

International audience; Color map textures applied directly to surfaces, to geometric microsurface details, or to procedural functions (such as noise), are commonly used to enhance visual detail. Their simplicity and ability to mimic a wide range of realistic appearances have led to their adoption in many rendering problems. As with any textured or geometric detail, proper filtering is needed to reduce aliasing when viewed across a range of distances, but accurate and efficient color map filt...

Classification of mass and normal breast tissue: A convolution neural network classifier with spatial domain and texture images

International Nuclear Information System (INIS)

Sahiner, B.; Chan, H.P.; Petrick, N.; Helvie, M.A.; Adler, D.D.; Goodsitt, M.M.; Wei, D.

1996-01-01

The authors investigated the classification of regions of interest (ROI's) on mammograms as either mass or normal tissue using a convolution neural network (CNN). A CNN is a back-propagation neural network with two-dimensional (2-D) weight kernels that operate on images. A generalized, fast and stable implementation of the CNN was developed. The input images to the CNN were obtained form the ROI's using two techniques. The first technique employed averaging and subsampling. The second technique employed texture feature extraction methods applied to small subregions inside the ROI. Features computed over different subregions were arranged as texture images, which were subsequently used as CNN inputs. The effects of CNN architecture and texture feature parameters on classification accuracy were studied. Receiver operating characteristic (ROC) methodology was used to evaluate the classification accuracy. A data set consisting of 168 ROI's containing biopsy-proven masses and 504 ROI's containing normal breast tissue was extracted from 168 mammograms by radiologists experienced in mammography. This data set was used for training and testing the CNN. With the best combination of CNN architecture and texture feature parameters, the area under the test ROC curve reached 0.87, which corresponded to a true-positive fraction of 90% at a false positive fraction of 31%. The results demonstrate the feasibility of using a CNN for classification of masses and normal tissue on mammograms

Laser gas assisted texturing and formation of nitride and oxynitride compounds on alumina surface: Surface response to environmental dust

Science.gov (United States)

Yilbas, B. S.; Ali, H.; Al-Sharafi, A.; Al-Aqeeli, N.

2018-03-01

Laser gas assisted texturing of alumina surface is carried out, and formation of nitride and oxynitride compounds in the surface vicinity is examined. The laser parameters are selected to create the surface topology consisting of micro/nano pillars with minimum defect sites including micro-cracks, voids and large size cavities. Morphological and hydrophobic characteristics of the textured surface are examined using the analytical tools. The characteristics of the environmental dust and its influence on the laser textured surface are studied while mimicking the local humid air ambient. Adhesion of the dry mud on the laser textured surface is assessed through the measurement of the tangential force, which is required to remove the dry mud from the surface. It is found that laser texturing gives rise to micro/nano pillars topology and the formation of AlN and AlON compounds in the surface vicinity. This, in turn, lowers the free energy of the textured surface and enhances the hydrophobicity of the surface. The liquid solution resulted from the dissolution of alkaline and alkaline earth metals of the dust particles in water condensate forms locally scattered liquid islands at the interface of mud and textured surface. The dried liquid solution at the interface increases the dry mud adhesion on the textured surface. Some dry mud residues remain on the textured surface after the dry mud is removed by a pressurized desalinated water jet.

The Influence of the Tool Surface Texture on Friction and the Surface Layers Properties of Formed Component

Directory of Open Access Journals (Sweden)

Jana Šugárová

2018-03-01

Full Text Available The morphological texturing of forming tool surfaces has high potential to reduce friction and tool wear and also has impact on the surface layers properties of formed material. In order to understand the effect of different types of tool textures, produced by nanosecond fibre laser, on the tribological conditions at the interface tool-formed material and on the integrity of formed part surface layers, the series of experimental investigations have been carried out. The coefficient of friction for different texture parameters (individual feature shape, including the depth profile of the cavities and orientation of the features relative to the material flow was evaluated via a Ring Test and the surface layers integrity of formed material (surface roughness and subsurface micro hardness was also experimentally analysed. The results showed a positive effect of surface texturing on the friction coefficients and the strain hardening of test samples material. Application of surface texture consisting of dimple-like depressions arranged in radial layout contributed to the most significant friction reduction of about 40%. On the other hand, this surface texture contributed to the increase of surface roughness parameters, Ra parameter increased from 0.49 μm to 2.19 μm and the Rz parameter increased from 0.99 μm to 16.79 μm.

Modulation of dry tribological property of stainless steel by femtosecond laser surface texturing

Science.gov (United States)

Wang, Zhuo; Zhao, Quanzhong; Wang, Chengwei; Zhang, Yang

2015-06-01

We reported on the modification of tribological properties of stainless steel by femtosecond laser surface microstructuring. Regular arranged micro-grooved textures with different spacing were produced on the AISI 304L steel surfaces by an 800-nm femtosecond laser. The tribological properties of smooth surface and textured surface were investigated by carrying out reciprocating ball-on-flat tests against Al2O3 ceramic balls under dry friction. Results show that the spacing of micro-grooves had a significant impact on friction coefficient of textured surfaces. Furthermore, the wear behaviors of smooth and textured surface were also investigated. Femtosecond laser surface texturing had a marked potential for modulating friction and wear properties if the micro-grooves were distributed in an appropriate manner.

EUROMET SUPPLEMENTARY COMPARISON - SURFACE TEXTURE

DEFF Research Database (Denmark)

Koenders, L.; Andreasen, Jan Lasson; De Chiffre, Leonardo

At the length meeting in Prague in Oct. 1999 a new comparison was suggested on surface texture. The last comparison on this field was finished in 1989. In the meantime the instrumentation, the standards and the written standards have been improved including some software filters. The pilot labora...

Classification of Weed Species Using Artificial Neural Networks Based on Color Leaf Texture Feature

Science.gov (United States)

Li, Zhichen; An, Qiu; Ji, Changying

The potential impact of herbicide utilization compel people to use new method of weed control. Selective herbicide application is optimal method to reduce herbicide usage while maintain weed control. The key of selective herbicide is how to discriminate weed exactly. The HIS color co-occurrence method (CCM) texture analysis techniques was used to extract four texture parameters: Angular second moment (ASM), Entropy(E), Inertia quadrature (IQ), and Inverse difference moment or local homogeneity (IDM).The weed species selected for studying were Arthraxon hispidus, Digitaria sanguinalis, Petunia, Cyperus, Alternanthera Philoxeroides and Corchoropsis psilocarpa. The software of neuroshell2 was used for designing the structure of the neural network, training and test the data. It was found that the 8-40-1 artificial neural network provided the best classification performance and was capable of classification accuracies of 78%.

Stabilization of Leidenfrost vapour layer by textured superhydrophobic surfaces

KAUST Repository

Vakarelski, Ivan Uriev

2012-09-12

In 1756, Leidenfrost observed that water drops skittered on a sufficiently hot skillet, owing to levitation by an evaporative vapour film. Such films are stable only when the hot surface is above a critical temperature, and are a central phenomenon in boiling. In this so-called Leidenfrost regime, the low thermal conductivity of the vapour layer inhibits heat transfer between the hot surface and the liquid. When the temperature of the cooling surface drops below the critical temperature, the vapour film collapses and the system enters a nucleate-boiling regime, which can result in vapour explosions that are particularly detrimental in certain contexts, such as in nuclear power plants. The presence of these vapour films can also reduce liquid-solid drag. Here we show how vapour film collapse can be completely suppressed at textured superhydrophobic surfaces. At a smooth hydrophobic surface, the vapour film still collapses on cooling, albeit at a reduced critical temperature, and the system switches explosively to nucleate boiling. In contrast, at textured, superhydrophobic surfaces, the vapour layer gradually relaxes until the surface is completely cooled, without exhibiting a nucleate-boiling phase. This result demonstrates that topological texture on superhydrophobic materials is critical in stabilizing the vapour layer and thus in controlling-by heat transfer-the liquid-gas phase transition at hot surfaces. This concept can potentially be applied to control other phase transitions, such as ice or frost formation, and to the design of low-drag surfaces at which the vapour phase is stabilized in the grooves of textures without heating. © 2012 Macmillan Publishers Limited. All rights reserved.

Stabilization of Leidenfrost vapour layer by textured superhydrophobic surfaces

KAUST Repository

Vakarelski, Ivan Uriev; Patankar, Neelesh A.; Marston, Jeremy; Chan, Derek Y C; Thoroddsen, Sigurdur T

2012-01-01

In 1756, Leidenfrost observed that water drops skittered on a sufficiently hot skillet, owing to levitation by an evaporative vapour film. Such films are stable only when the hot surface is above a critical temperature, and are a central phenomenon in boiling. In this so-called Leidenfrost regime, the low thermal conductivity of the vapour layer inhibits heat transfer between the hot surface and the liquid. When the temperature of the cooling surface drops below the critical temperature, the vapour film collapses and the system enters a nucleate-boiling regime, which can result in vapour explosions that are particularly detrimental in certain contexts, such as in nuclear power plants. The presence of these vapour films can also reduce liquid-solid drag. Here we show how vapour film collapse can be completely suppressed at textured superhydrophobic surfaces. At a smooth hydrophobic surface, the vapour film still collapses on cooling, albeit at a reduced critical temperature, and the system switches explosively to nucleate boiling. In contrast, at textured, superhydrophobic surfaces, the vapour layer gradually relaxes until the surface is completely cooled, without exhibiting a nucleate-boiling phase. This result demonstrates that topological texture on superhydrophobic materials is critical in stabilizing the vapour layer and thus in controlling-by heat transfer-the liquid-gas phase transition at hot surfaces. This concept can potentially be applied to control other phase transitions, such as ice or frost formation, and to the design of low-drag surfaces at which the vapour phase is stabilized in the grooves of textures without heating. © 2012 Macmillan Publishers Limited. All rights reserved.

Experimental Study on Tribological Properties of Laser Textured 45 Steel Surface

Directory of Open Access Journals (Sweden)

Li Zhi Peng

2016-01-01

Full Text Available In order to study the influence of pits’ size parameters on the tribological properties of textured friction pairs, using the Nd:YAG laser micro machining system and the “single pulse at the same point, interval more times” processing technics to process the pits on the surface of 45 steel. The dimension parameters of pits texture were obtained by orthogonal experimental design. The tribological experiment of GCr15 pin/45 steel disc was carried out by UMT-2 test machine. The surface morphology of the specimens was analyzed by using scanning electron microscopy. The experimental results show that the pits texture on the surface of 45 steel can effectively reduce the friction coefficient and the wear on the condition of oil-rich lubrication. The textured specimen with diameter 60μm, depth 6μm and surface density 10% has the lowest friction coefficient, and the friction coefficient is reduced by 21% compared with the smooth specimen. By analyzing the wear morphology on the surface of 45 steel, it is found that the surface of pits texture can obviously reduce the wear.

Effect of environmental dust particles on laser textured yttria-stabilized zirconia surface in humid air ambient

Science.gov (United States)

Yilbas, B. S.; Ali, H.; Al-Sharafi, A.; Al-Sulaiman, F.; Karatas, C.

2018-05-01

Zirconium nitride is used as a selective surface for concentrated solar heating applications and one of the methods to form a zirconium nitride is texturing of zirconia surface by a high intensity laser beam under high pressure nitrogen gas environment. Laser texturing also provides hydrophobic surface characteristics via forming micro/nano pillars at the surface; however, environmental dust settlement on textured surface influences the surface characteristics significantly. In the present study, laser texturing of zirconia surface and effects of the dust particles on the textured surface in a humid air ambient are investigated. Analytical tools are used to assess the morphological changes on the laser textured surface prior and after the dust settlement in the humid air ambient. It is found that laser textured surface has hydrophobic characteristics. The mud formed during condensate of water on the dust particles alters the characteristics of the laser textured surface. The tangential force required to remove the dry mud from the textured surface remains high; in which case, the dried liquid solution at the mud-textured surface interface is responsible for the strong adhesion of the dry mud on the textured surface. The textured surface becomes hydrophilic after the dry mud was removed from the surface by a desalinated water jet.

Surface texture measurement for additive manufacturing

International Nuclear Information System (INIS)

Triantaphyllou, Andrew; Tomita, Ben; Milne, Katherine A; Giusca, Claudiu L; Macaulay, Gavin D; Roerig, Felix; Hoebel, Matthias; Leach, Richard K

2015-01-01

The surface texture of additively manufactured metallic surfaces made by powder bed methods is affected by a number of factors, including the powder’s particle size distribution, the effect of the heat source, the thickness of the printed layers, the angle of the surface relative to the horizontal build bed and the effect of any post processing/finishing. The aim of the research reported here is to understand the way these surfaces should be measured in order to characterise them. In published research to date, the surface texture is generally reported as an Ra value, measured across the lay. The appropriateness of this method for such surfaces is investigated here. A preliminary investigation was carried out on two additive manufacturing processes—selective laser melting (SLM) and electron beam melting (EBM)—focusing on the effect of build angle and post processing. The surfaces were measured using both tactile and optical methods and a range of profile and areal parameters were reported. Test coupons were manufactured at four angles relative to the horizontal plane of the powder bed using both SLM and EBM. The effect of lay—caused by the layered nature of the manufacturing process—was investigated, as was the required sample area for optical measurements. The surfaces were also measured before and after grit blasting. (paper)

Surface texture measurement for additive manufacturing

Science.gov (United States)

Triantaphyllou, Andrew; Giusca, Claudiu L.; Macaulay, Gavin D.; Roerig, Felix; Hoebel, Matthias; Leach, Richard K.; Tomita, Ben; Milne, Katherine A.

2015-06-01

The surface texture of additively manufactured metallic surfaces made by powder bed methods is affected by a number of factors, including the powder’s particle size distribution, the effect of the heat source, the thickness of the printed layers, the angle of the surface relative to the horizontal build bed and the effect of any post processing/finishing. The aim of the research reported here is to understand the way these surfaces should be measured in order to characterise them. In published research to date, the surface texture is generally reported as an Ra value, measured across the lay. The appropriateness of this method for such surfaces is investigated here. A preliminary investigation was carried out on two additive manufacturing processes—selective laser melting (SLM) and electron beam melting (EBM)—focusing on the effect of build angle and post processing. The surfaces were measured using both tactile and optical methods and a range of profile and areal parameters were reported. Test coupons were manufactured at four angles relative to the horizontal plane of the powder bed using both SLM and EBM. The effect of lay—caused by the layered nature of the manufacturing process—was investigated, as was the required sample area for optical measurements. The surfaces were also measured before and after grit blasting.

Experimental Study on Momentum Transfer of Surface Texture in Taylor-Couette Flow

Science.gov (United States)

Xue, Yabo; Yao, Zhenqiang; Cheng, De

2017-05-01

The behavior of Taylor-Couette (TC) flow has been extensively studied. However, no suitable torque prediction models exist for high-capacity fluid machinery. The Eckhardt-Grossmann-Lohse (EGL) theory, derived based on the Navier-Stokes equations, is proposed to model torque behavior. This theory suggests that surfaces are the significant energy transfer interfaces between cylinders and annular flow. This study mainly focuses on the effects of surface texture on momentum transfer behavior through global torque measurement. First, a power-law torque behavior model is built to reveal the relationship between dimensionless torque and the Taylor number based on the EGL theory. Second, TC flow apparatus is designed and built based on the CNC machine tool to verify the torque behavior model. Third, four surface texture films are tested to check the effects of surface texture on momentum transfer. A stereo microscope and three-dimensional topography instrument are employed to analyze surface morphology. Global torque behavior is measured by rotating a multi component dynamometer, and the effects of surface texture on the annular flow behavior are observed via images obtained using a high-speed camera. Finally, torque behaviors under four different surface conditions are fitted and compared. The experimental results indicate that surface textures have a remarkable influence on torque behavior, and that the peak roughness of surface texture enhances the momentum transfer by strengthening the fluctuation in the TC flow.

Texturing in titanium grade 2 surface irradiate with ultrashort pulse laser

International Nuclear Information System (INIS)

Nogueira, Alessandro Francelino

2015-01-01

The texturing laser micromachining is an important alternative to improve the bonding adhesion between composites and titanium, which are applied to structural components in the aerospace industry. The texturing running on titanium plates is due to the fact that the preferred joining technique for many composite materials is the adhesive bonding. In this work, titanium plates were texturized using laser ultrashort pulses temporal widths of femtoseconds. This process resulted in minimal heat transfer to the material, avoiding deformation of the titanium plate surface as well as the formation of resolidified material in the ablated region. These drawbacks have occurred with the use of nanoseconds pulses. Were performed three types of texturing using laser with femtosecond pulses, with variations in the distances between the machined lines. The analysis of the obtained surfaces found that the wettability increases when there is the increased distance between the texturing lines. Advancing in the analysis by optical profilometry of textured surfaces was observed that there is substantial increase in the volume available for penetration of structural adhesive when the distances between the textured lines are diminished. In tensile tests conducted it was observed that there is an increase in shear strength of the adhesive joint by reducing the distance between the textured lines. (author)

Texture segregation, surface representation and figure-ground separation.

Science.gov (United States)

Grossberg, S; Pessoa, L

1998-09-01

A widespread view is that most texture segregation can be accounted for by differences in the spatial frequency content of texture regions. Evidence from both psychophysical and physiological studies indicate, however, that beyond these early filtering stages, there are stages of 3-D boundary segmentation and surface representation that are used to segregate textures. Chromatic segregation of element-arrangement patterns--as studied by Beck and colleagues--cannot be completely explained by the filtering mechanisms previously employed to account for achromatic segregation. An element arrangement pattern is composed of two types of elements that are arranged differently in different image regions (e.g. vertically on top and diagonally on the bottom). FACADE theory mechanisms that have previously been used to explain data about 3-D vision and figure-ground separation are here used to simulate chromatic texture segregation data, including data with equiluminant elements on dark or light homogeneous backgrounds, or backgrounds composed of vertical and horizontal dark or light stripes, or horizontal notched stripes. These data include the fact that segregation of patterns composed of red and blue squares decreases with increasing luminance of the interspaces. Asymmetric segregation properties under 3-D viewing conditions with the equiluminant elements close or far are also simulated. Two key model properties are a spatial impenetrability property that inhibits boundary grouping across regions with non-collinear texture elements and a boundary-surface consistency property that uses feedback between boundary and surface representations to eliminate spurious boundary groupings and separate figures from their backgrounds.

Doping profile measurement on textured silicon surface

Science.gov (United States)

Essa, Zahi; Taleb, Nadjib; Sermage, Bernard; Broussillou, Cédric; Bazer-Bachi, Barbara; Quillec, Maurice

2018-04-01

In crystalline silicon solar cells, the front surface is textured in order to lower the reflection of the incident light and increase the efficiency of the cell. This texturing whose dimensions are a few micrometers wide and high, often makes it difficult to determine the doping profile measurement. We have measured by secondary ion mass spectrometry (SIMS) and electrochemical capacitance voltage profiling the doping profile of implanted phosphorus in alkaline textured and in polished monocrystalline silicon wafers. The paper shows that SIMS gives accurate results provided the primary ion impact angle is small enough. Moreover, the comparison between these two techniques gives an estimation of the concentration of electrically inactive phosphorus atoms.

Computer Texture Mapping for Laser Texturing of Injection Mold

Directory of Open Access Journals (Sweden)

Yongquan Zhou

2014-04-01

Full Text Available Laser texturing is a relatively new multiprocess technique that has been used for machining 3D curved surfaces; it is more flexible and efficient to create decorative texture on 3D curved surfaces of injection molds so as to improve the surface quality and achieve cosmetic surface of molded plastic parts. In this paper, a novel method of laser texturing 3D curved surface based on 3-axis galvanometer scanning unit has been presented to prevent the texturing of injection mold surface from much distortion which is often caused by traditional texturing processes. The novel method has been based on the computer texture mapping technology which has been developed and presented. The developed texture mapping algorithm includes surface triangulation, notations, distortion measurement, control, and numerical method. An interface of computer texture mapping has been built to implement the algorithm of texture mapping approach to controlled distortion rate of 3D texture math model from 2D original texture applied to curvature surface. Through a case study of laser texturing of a high curvature surface of injection mold of a mice top case, it shows that the novel method of laser texturing meets the quality standard of laser texturing of injection mold.

Dynamic air layer on textured superhydrophobic surfaces

KAUST Repository

Vakarelski, Ivan Uriev

2013-09-03

We provide an experimental demonstration that a novel macroscopic, dynamic continuous air layer or plastron can be sustained indefinitely on textured superhydrophobic surfaces in air-supersaturated water by a natural gas influx mechanism. This type of plastron is an intermediate state between Leidenfrost vapor layers on superheated surfaces and the equilibrium Cassie-Baxter wetting state on textured superhydrophobic surfaces. We show that such a plastron can be sustained on the surface of a centimeter-sized superhydrophobic sphere immersed in heated water and variations of its dynamic behavior with air saturation of the water can be regulated by rapid changes of the water temperature. The simple experimental setup allows for quantification of the air flux into the plastron and identification of the air transport model of the plastron growth. Both the observed growth dynamics of such plastrons and millimeter-sized air bubbles seeded on the hydrophilic surface under identical air-supersaturated solution conditions are consistent with the predictions of a well-mixed gas transport model. © 2013 American Chemical Society.

Statistical analysis of textural features for improved classification of oral histopathological images.

Science.gov (United States)

Muthu Rama Krishnan, M; Shah, Pratik; Chakraborty, Chandan; Ray, Ajoy K

2012-04-01

The objective of this paper is to provide an improved technique, which can assist oncopathologists in correct screening of oral precancerous conditions specially oral submucous fibrosis (OSF) with significant accuracy on the basis of collagen fibres in the sub-epithelial connective tissue. The proposed scheme is composed of collagen fibres segmentation, its textural feature extraction and selection, screening perfomance enhancement under Gaussian transformation and finally classification. In this study, collagen fibres are segmented on R,G,B color channels using back-probagation neural network from 60 normal and 59 OSF histological images followed by histogram specification for reducing the stain intensity variation. Henceforth, textural features of collgen area are extracted using fractal approaches viz., differential box counting and brownian motion curve . Feature selection is done using Kullback-Leibler (KL) divergence criterion and the screening performance is evaluated based on various statistical tests to conform Gaussian nature. Here, the screening performance is enhanced under Gaussian transformation of the non-Gaussian features using hybrid distribution. Moreover, the routine screening is designed based on two statistical classifiers viz., Bayesian classification and support vector machines (SVM) to classify normal and OSF. It is observed that SVM with linear kernel function provides better classification accuracy (91.64%) as compared to Bayesian classifier. The addition of fractal features of collagen under Gaussian transformation improves Bayesian classifier's performance from 80.69% to 90.75%. Results are here studied and discussed.

Influence of surface texturing on the performance of tilting pad thrust bearings

OpenAIRE

Gropper, Daniel; Wang, Ling; Harvey, Terry J.; Meck, Klaus-Dieter; Gviniashvili, Vladimir

2016-01-01

Surface textures have been shown to have the potential of enhancing the performance of hydrodynamic bearings and many other applications. However, a comprehensive literature review by the authors has revealed that the application of surface texturing is still limited due to major challenges, such as the complexity of computational models and the large variety of operating conditions encountered in conventional industrial applications. In the present work, the potential of surface texturing fo...

Assessing Asphalt and Concrete Pavement Surface Texture in the Field

Directory of Open Access Journals (Sweden)

Saad I. Sarsam

2016-06-01

Full Text Available The incorporation of safety characteristics into the traditional pavement structural design or in the functional evaluation of pavement condition has not been established yet. The design has focused on the structural capacity of the roadway so that the pavement can withstand specific level of repetitive loading over the design life. On the other hand, the surface texture condition was neither included in the AASHTO design procedure nor in the present serviceability index measurements. The pavement surface course should provide adequate levels of friction and ride quality and maintain low levels of noise and roughness. Many transportation departments perform routine skid resistant testing, the type of equipment used for testing varies depending on the preference of each transportation department. It was felt that modeling of the surface texture condition using different methods of testing may assist in solving such problem. In this work, Macro texture and Micro texture of asphalt and cement concrete pavement surface have been investigated in the field using four different methods (The Sand Patch Method, Outflow Time Method, British Pendulum Tester and Photogrammetry Technique. Two different grain sizes of sand have been utilized in conducting the Sand Patch while the Micro texture was investigated using the British Pendulum tester method at wet pavement surface conditions. The test results of the four methods were correlated to the skid number. It was concluded that such modeling could provide instant data in the field for pavement condition which may help in pavement maintenance management.

Fingerprint-Inspired Flexible Tactile Sensor for Accurately Discerning Surface Texture.

Science.gov (United States)

Cao, Yudong; Li, Tie; Gu, Yang; Luo, Hui; Wang, Shuqi; Zhang, Ting

2018-04-01

Inspired by the epidermal-dermal and outer microstructures of the human fingerprint, a novel flexible sensor device is designed to improve haptic perception and surface texture recognition, which is consisted of single-walled carbon nanotubes, polyethylene, and polydimethylsiloxane with interlocked and outer micropyramid arrays. The sensor shows high pressure sensitivity (-3.26 kPa -1 in the pressure range of 0-300 Pa), and it can detect the shear force changes induced by the dynamic interaction between the outer micropyramid structure on the sensor and the tested material surface, and the minimum dimension of the microstripe that can be discerned is as low as 15 µm × 15 µm (interval × width). To demonstrate the texture discrimination capability, the sensors are tested for accurately discerning various surface textures, such as the textures of different fabrics, Braille characters, the inverted pyramid patterns, which will have great potential in robot skins and haptic perception, etc. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Textural kinetics: a novel dynamic contrast-enhanced (DCE)-MRI feature for breast lesion classification.

Science.gov (United States)

Agner, Shannon C; Soman, Salil; Libfeld, Edward; McDonald, Margie; Thomas, Kathleen; Englander, Sarah; Rosen, Mark A; Chin, Deanna; Nosher, John; Madabhushi, Anant

2011-06-01

Dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) of the breast has emerged as an adjunct imaging tool to conventional X-ray mammography due to its high detection sensitivity. Despite the increasing use of breast DCE-MRI, specificity in distinguishing malignant from benign breast lesions is low, and interobserver variability in lesion classification is high. The novel contribution of this paper is in the definition of a new DCE-MRI descriptor that we call textural kinetics, which attempts to capture spatiotemporal changes in breast lesion texture in order to distinguish malignant from benign lesions. We qualitatively and quantitatively demonstrated on 41 breast DCE-MRI studies that textural kinetic features outperform signal intensity kinetics and lesion morphology features in distinguishing benign from malignant lesions. A probabilistic boosting tree (PBT) classifier in conjunction with textural kinetic descriptors yielded an accuracy of 90%, sensitivity of 95%, specificity of 82%, and an area under the curve (AUC) of 0.92. Graph embedding, used for qualitative visualization of a low-dimensional representation of the data, showed the best separation between benign and malignant lesions when using textural kinetic features. The PBT classifier results and trends were also corroborated via a support vector machine classifier which showed that textural kinetic features outperformed the morphological, static texture, and signal intensity kinetics descriptors. When textural kinetic attributes were combined with morphologic descriptors, the resulting PBT classifier yielded 89% accuracy, 99% sensitivity, 76% specificity, and an AUC of 0.91.

Evaluation of Wear on Macro-Surface Textures Generated by ns Fiber Laser

Science.gov (United States)

Harish, V.; Soundarapandian, S.; Vijayaraghavan, L.; Bharatish, A.

2018-03-01

The demand for improved performance and long term reliability of mechanical systems dictate the use of advanced materials and surface engineering techniques. A small change in the surface topography can lead to substantial improvements in the tribological behaviour of the contact surfaces. One way of altering the surface topography is by surface texturing by introducing dimples or channels on the surfaces. Surface texturing is already a successful technique which finds a wide area of applications ranging from heavy industries to small scale devices. This paper reports the effect of macro texture shapes generated using a nanosecond fiber laser on wear of high carbon chromium steel used in large size bearings having rolling contacts. Circular and square shaped dimples were generated on the surface to assess the effect of sliding velocities on friction coefficient. Graphite was used as solid lubricant to minimise the effect of wear on textured surfaces. The laser parameters such as power, scan speed and passes were optimised to obtain macro circular and square dimples which was characterised using a laser confocal microscope. The friction coefficients of the circular and square dimples were observed to lie in the same range due to minimum wear on the surface. On the contrary, at medium and higher sliding velocities, square dimples exhibited lower friction coefficient values compared to circular dimples. The morphology of textured specimen was characterised using Scanning Electron Microscope.

Control of crystallographic texture and surface morphology of Pt/Tio2 templates for enhanced PZT thin film texture.

Science.gov (United States)

Fox, Austin J; Drawl, Bill; Fox, Glen R; Gibbons, Brady J; Trolier-McKinstry, Susan

2015-01-01

Optimized processing conditions for Pt/TiO2/SiO2/Si templating electrodes were investigated. These electrodes are used to obtain [111] textured thin film lead zirconate titanate (Pb[ZrxTi1-x ]O3 0 ≤ x ≤ 1) (PZT). Titanium deposited by dc magnetron sputtering yields [0001] texture on a thermally oxidized Si wafer. It was found that by optimizing deposition time, pressure, power, and the chamber pre-conditioning, the Ti texture could be maximized while maintaining low surface roughness. When oxidized, titanium yields [100]-oriented rutile. This seed layer has as low as a 4.6% lattice mismatch with [111] Pt; thus, it is possible to achieve strongly oriented [111] Pt. The quality of the orientation and surface roughness of the TiO2 and the Ti directly affect the achievable Pt texture and surface morphology. A transition between optimal crystallographic texture and the smoothest templating surface occurs at approximately 30 nm of original Ti thickness (45 nm TiO2). This corresponds to 0.5 nm (2 nm for TiO2) rms roughness as determined by atomic force microscopy and a full-width at half-maximum (FWHM) of the rocking curve 0002 (200) peak of 5.5/spl degrees/ (3.1/spl degrees/ for TiO2). A Pb[Zr0.52Ti 0.48]O3 layer was deposited and shown to template from the textured Pt electrode, with a maximum [111] Lotgering factor of 87% and a minimum 111 FWHM of 2.4/spl degrees/ at approximately 30 nm of original Ti.

Macroscopic Rock Texture Image Classification Using a Hierarchical Neuro-Fuzzy Class Method

Directory of Open Access Journals (Sweden)

Laercio B. Gonçalves

2010-01-01

Full Text Available We used a Hierarchical Neuro-Fuzzy Class Method based on binary space partitioning (NFHB-Class Method for macroscopic rock texture classification. The relevance of this study is in helping Geologists in the diagnosis and planning of oil reservoir exploration. The proposed method is capable of generating its own decision structure, with automatic extraction of fuzzy rules. These rules are linguistically interpretable, thus explaining the obtained data structure. The presented image classification for macroscopic rocks is based on texture descriptors, such as spatial variation coefficient, Hurst coefficient, entropy, and cooccurrence matrix. Four rock classes have been evaluated by the NFHB-Class Method: gneiss (two subclasses, basalt (four subclasses, diabase (five subclasses, and rhyolite (five subclasses. These four rock classes are of great interest in the evaluation of oil boreholes, which is considered a complex task by geologists. We present a computer method to solve this problem. In order to evaluate system performance, we used 50 RGB images for each rock classes and subclasses, thus producing a total of 800 images. For all rock classes, the NFHB-Class Method achieved a percentage of correct hits over 73%. The proposed method converged for all tests presented in the case study.

Automatic detection and classification of breast tumors in ultrasonic images using texture and morphological features.

Science.gov (United States)

Su, Yanni; Wang, Yuanyuan; Jiao, Jing; Guo, Yi

2011-01-01

Due to severe presence of speckle noise, poor image contrast and irregular lesion shape, it is challenging to build a fully automatic detection and classification system for breast ultrasonic images. In this paper, a novel and effective computer-aided method including generation of a region of interest (ROI), segmentation and classification of breast tumor is proposed without any manual intervention. By incorporating local features of texture and position, a ROI is firstly detected using a self-organizing map neural network. Then a modified Normalized Cut approach considering the weighted neighborhood gray values is proposed to partition the ROI into clusters and get the initial boundary. In addition, a regional-fitting active contour model is used to adjust the few inaccurate initial boundaries for the final segmentation. Finally, three textures and five morphologic features are extracted from each breast tumor; whereby a highly efficient Affinity Propagation clustering is used to fulfill the malignancy and benign classification for an existing database without any training process. The proposed system is validated by 132 cases (67 benignancies and 65 malignancies) with its performance compared to traditional methods such as level set segmentation, artificial neural network classifiers, and so forth. Experiment results show that the proposed system, which needs no training procedure or manual interference, performs best in detection and classification of ultrasonic breast tumors, while having the lowest computation complexity.

Nanosecond laser textured superhydrophobic metallic surfaces and their chemical sensing applications

Science.gov (United States)

Ta, Duong V.; Dunn, Andrew; Wasley, Thomas J.; Kay, Robert W.; Stringer, Jonathan; Smith, Patrick J.; Connaughton, Colm; Shephard, Jonathan D.

2015-12-01

This work demonstrates superhydrophobic behavior on nanosecond laser patterned copper and brass surfaces. Compared with ultrafast laser systems previously used for such texturing, infrared nanosecond fiber lasers offer a lower cost and more robust system combined with potentially much higher processing rates. The wettability of the textured surfaces develops from hydrophilicity to superhydrophobicity over time when exposed to ambient conditions. The change in the wetting property is attributed to the partial deoxidation of oxides on the surface induced during laser texturing. Textures exhibiting steady state contact angles of up to ∼152° with contact angle hysteresis of around 3-4° have been achieved. Interestingly, the superhydrobobic surfaces have the self-cleaning ability and have potential for chemical sensing applications. The principle of these novel chemical sensors is based on the change in contact angle with the concentration of methanol in a solution. To demonstrate the principle of operation of such a sensor, it is found that the contact angle of methanol solution on the superhydrophobic surfaces exponentially decays with increasing concentration. A significant reduction, of 128°, in contact angle on superhydrophobic brass is observed, which is one order of magnitude greater than that for the untreated surface (12°), when percent composition of methanol reaches to 28%.

Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity

Science.gov (United States)

Paneque-Gálvez, Jaime; Mas, Jean-François; Moré, Gerard; Cristóbal, Jordi; Orta-Martínez, Martí; Luz, Ana Catarina; Guèze, Maximilien; Macía, Manuel J.; Reyes-García, Victoria

2013-08-01

Land use/cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land use/cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims at establishing an efficient classification approach to accurately map all broad land use/cover classes in a large, heterogeneous tropical area, as a basis for further studies (e.g., land use/cover change, deforestation and forest degradation). Specifically, we first compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbor and four different support vector machines - SVM), and hybrid (unsupervised-supervised) classifiers, using hard and soft (fuzzy) accuracy assessments. We then assess, using the maximum likelihood algorithm, what textural indices from the gray-level co-occurrence matrix lead to greater classification improvements at the spatial resolution of Landsat imagery (30 m), and rank them accordingly. Finally, we use the textural index that provides the most accurate classification results to evaluate whether its usefulness varies significantly with the classifier used. We classified imagery corresponding to dry and wet seasons and found that SVM classifiers outperformed all the rest. We also found that the use of some textural indices, but particularly homogeneity and entropy, can significantly improve classifications. We focused on the use of the homogeneity index, which has so far been neglected in land use/cover classification efforts, and found that this index along with reflectance bands significantly increased the overall accuracy of all the classifiers, but particularly of SVM. We observed that improvements in producer's and user's accuracies through the inclusion of homogeneity were different

Tribological Properties of Surface-Textured and Plasma-Nitrided Pure Titanium Under Oil Lubrication Condition

Science.gov (United States)

Zhang, Baosen; Dong, Qiangsheng; Ba, Zhixin; Wang, Zhangzhong; Shi, Hancheng; Xue, Yanting

2018-01-01

Plasma nitriding was conducted as post-treatment for surface texture on pure titanium to obtain a continuous nitriding layer. Supersonic fine particles bombarding (SFPB) was carried out to prepare surface texture. The surface morphologies and chemical composition were analyzed using scanning electron microscope and energy disperse spectroscopy. The microstructures of modified layers were characterized by transmission electron microscope. The tribological properties of surface-textured and duplex-treated pure titanium under oil lubrication condition were systematically investigated in the ball-on-plate reciprocating mode. The effects of applied load and sliding velocity on the tribological behavior were analyzed. The results show that after duplex treatments, the grains size in modified layer becomes slightly larger, and hardness is obviously improved. Wear resistance of duplex-treated pure titanium is significantly improved referenced to untreated and surface-textured pure titanium, which is 3.22 times as much as untreated pure titanium and 2.15 times of that for surface-textured pure titanium, respectively.

Spatial and Spectral Hybrid Image Classification for Rice Lodging Assessment through UAV Imagery

Directory of Open Access Journals (Sweden)

Ming-Der Yang

2017-06-01

Full Text Available Rice lodging identification relies on manual in situ assessment and often leads to a compensation dispute in agricultural disaster assessment. Therefore, this study proposes a comprehensive and efficient classification technique for agricultural lands that entails using unmanned aerial vehicle (UAV imagery. In addition to spectral information, digital surface model (DSM and texture information of the images was obtained through image-based modeling and texture analysis. Moreover, single feature probability (SFP values were computed to evaluate the contribution of spectral and spatial hybrid image information to classification accuracy. The SFP results revealed that texture information was beneficial for the classification of rice and water, DSM information was valuable for lodging and tree classification, and the combination of texture and DSM information was helpful in distinguishing between artificial surface and bare land. Furthermore, a decision tree classification model incorporating SFP values yielded optimal results, with an accuracy of 96.17% and a Kappa value of 0.941, compared with that of a maximum likelihood classification model (90.76%. The rice lodging ratio in paddies at the study site was successfully identified, with three paddies being eligible for disaster relief. The study demonstrated that the proposed spatial and spectral hybrid image classification technology is a promising tool for rice lodging assessment.

The application of slip length models to larger textures in turbulent flows over superhydrophobic surfaces

Science.gov (United States)

Fairhall, Chris; Garcia-Mayoral, Ricardo

2017-11-01

We present results from direct numerical simulations of turbulent flows over superhydrophobic surfaces. We assess the validity of simulations where the surface is modelled as homogeneous slip lengths, comparing them to simulations where the surface texture is resolved. Our results show that once the coherent flow induced by the texture is removed from the velocity fields, the remaining flow sees the surface as homogeneous. We then investigate how the overlying turbulence is modified by the presence of surface texture. For small textures, we show that turbulence is shifted closer to the wall due to the presence of slip, but otherwise remains essentially unmodified. For larger textures, the texture interacts with the turbulent lengthscales, thereby modifying the overlying turbulence. We also show that the saturation of the effect of the spanwise slip length (Fukagata et al. 2006, Busse & Sandham 2012, Seo & Mani 2016), which is drag increasing, is caused by the impermeability imposed at the surface. This work was supported by the Engineering and Physical Sciences Research Council.

Use of Textured Surfaces to Mitigate Sliding Friction and Wear of Lubricated and Non-Lubricated Contacts

Energy Technology Data Exchange (ETDEWEB)

Blau, Peter Julian [ORNL

2012-03-01

If properly employed, the placement of three-dimensional feature patterns, also referred to as textures, on relatively-moving, load-bearing surfaces can be beneficial to their friction and wear characteristics. For example, geometric patterns can function as lubricant supply channels or depressions in which to trap debris. They can also alter lubricant flow in a manner that produces thicker load-bearing films locally. Considering the area occupied by solid areas and spaces, textures also change the load distribution on surfaces. At least ten different attributes of textures can be specified, and their combinations offer wide latitude in surface engineering. By employing directional machining and grinding procedures, texturing has been used on bearings and seals for well over a half century, and the size scales of texturing vary widely. This report summarizes past work on the texturing of load-bearing surfaces, including past research on laser surface dimpling of ceramics done at ORNL. Textured surfaces generally show most pronounced effects when they are used in conformal or nearly conformal contacts, like that in face seals. Combining textures with other forms of surface modification and lubrication methods can offer additional benefits in surface engineering for tribology. As the literature and past work at ORNL shows, texturing does not always provide benefits. Rather, the selected pattern and arrangement of features must be matched to characteristics of the proposed application, bearing materials, and lubricants.

Using geometrical, textural, and contextual information of land parcels for classification of detailed urban land use

Science.gov (United States)

Wu, S.-S.; Qiu, X.; Usery, E.L.; Wang, L.

2009-01-01

Detailed urban land use data are important to government officials, researchers, and businesspeople for a variety of purposes. This article presents an approach to classifying detailed urban land use based on geometrical, textural, and contextual information of land parcels. An area of 6 by 14 km in Austin, Texas, with land parcel boundaries delineated by the Travis Central Appraisal District of Travis County, Texas, is tested for the approach. We derive fifty parcel attributes from relevant geographic information system (GIS) and remote sensing data and use them to discriminate among nine urban land uses: single family, multifamily, commercial, office, industrial, civic, open space, transportation, and undeveloped. Half of the 33,025 parcels in the study area are used as training data for land use classification and the other half are used as testing data for accuracy assessment. The best result with a decision tree classification algorithm has an overall accuracy of 96 percent and a kappa coefficient of 0.78, and two naive, baseline models based on the majority rule and the spatial autocorrelation rule have overall accuracy of 89 percent and 79 percent, respectively. The algorithm is relatively good at classifying single-family, multifamily, commercial, open space, and undeveloped land uses and relatively poor at classifying office, industrial, civic, and transportation land uses. The most important attributes for land use classification are the geometrical attributes, particularly those related to building areas. Next are the contextual attributes, particularly those relevant to the spatial relationship between buildings, then the textural attributes, particularly the semivariance texture statistic from 0.61-m resolution images.

Angle-dependent lubricated tribological properties of stainless steel by femtosecond laser surface texturing

Science.gov (United States)

Wang, Zhuo; Li, Yang-Bo; Bai, Feng; Wang, Cheng-Wei; Zhao, Quan-Zhong

2016-07-01

Lubricated tribological properties of stainless steel were investigated by femtosecond laser surface texturing. Regular-arranged micro-grooved textures with different spacing and micro-groove inclination angles (between micro-groove path and sliding direction) were produced on AISI 304L steel surfaces by an 800 nm femtosecond laser. The spacing of micro-groove was varied from 25 to 300 μm, and the inclination angles of micro-groove were measured as 90° and 45°. The tribological properties of the smooth and textured surfaces with micro-grooves were investigated by reciprocating ball-on-flat tests against Al2O3 ceramic balls under starved oil lubricated conditions. Results showed that the spacing of micro-grooves significantly affected the tribological property. With the increase of micro-groove spacing, the average friction coefficients and wear rates of textured surfaces initially decreased then increased. The tribological performance also depended on the inclination angles of micro-grooves. Among the investigated patterns, the micro-grooves perpendicular to the sliding direction exhibited the lowest average friction coefficient and wear rate to a certain extent. Femtosecond laser-induced surface texturing may remarkably improve friction and wear properties if the micro-grooves were properly distributed.

DNS of flows over superhydrophobic surfaces with small texture

Science.gov (United States)

Fairhall, Chris; Garcia-Mayoral, Ricardo

2015-11-01

We present results from direct numerical simulations of turbulent flows over superhydrophobic surfaces with small texture sizes, comparable to those of practical application. Textures studied with DNS are usually much larger, as the cost of the simulations would otherwise be prohibitive. For this reason, a multi-block code that allows for finer resolution near the walls has been developed. We focus particularly on the pressure distribution at the wall. This distribution can cause the deformation of the gas pockets, which can ultimately lead to their loss and that of the drag reduction effect. The layout of the texture causes stagnation pressures which can contribute substantially to the wall pressure signal (Seo et al. JFM, under review). We study a range of different textures and their influence on these pressures.

Surface texture generation during cylindrical milling in the aspect of cutting force variations

International Nuclear Information System (INIS)

Wojciechowski, S; Twardowski, P; Pelic, M

2014-01-01

The work presented here concentrates on surface texture analysis, after cylindrical milling of hardened steel. Cutting force variations occurring in the machining process have direct influence on the cutter displacements and thus on the generated surface texture. Therefore, in these experiments, the influence of active number of teeth (z c ) on the cutting force variations was investigated. Cutting forces and cutter displacements were measured during machining process (online) using, namely piezoelectric force dynamometer and 3D laser vibrometer. Surface roughness parameters were measured using stylus surface profiler. The surface roughness model including cutting parameters (f z , D) and cutting force variations was also developed. The research revealed that in cylindrical milling process, cutting force variations have immediate influence on surface texture generation

Improved Main Shaft Seal Life in Gas Turbines Using Laser Surface Texturing

Science.gov (United States)

McNickle, Alan D.; Etsion, Izhak

2002-10-01

This paper presents a general overview of the improved main shaft seal life in gas turbines using laser surface texturing (LST). The contents include: 1) Laser Surface Texturing System; 2) Seal Schematic with LST applied; 3) Dynamic Rig Tests; 4) Surface Finish Definitions; 5) Wear Test Rig; 6) Dynamic Test Rig; 7) Seal Cross Section-Rig Test; and 8) Typical Test Results. This paper is in viewgraph form.

Surface Texture-Based Surface Treatments on Ti6Al4V Titanium Alloys for Tribological and Biological Applications: A Mini Review

Directory of Open Access Journals (Sweden)

Naiming Lin

2018-03-01

Full Text Available Surface texture (ST has been confirmed as an effective and economical surface treatment technique that can be applied to a great range of materials and presents growing interests in various engineering fields. Ti6Al4V which is the most frequently and successfully used titanium alloy has long been restricted in tribological-related operations due to the shortcomings of low surface hardness, high friction coefficient, and poor abrasive wear resistance. Ti6Al4V has benefited from surface texture-based surface treatments over the last decade. This review begins with a brief introduction, analysis approaches, and processing methods of surface texture. The specific applications of the surface texture-based surface treatments for improving surface performance of Ti6Al4V are thoroughly reviewed from the point of view of tribology and biology.

Analysis of SURRGO Data and Obtaining Soil Texture Classifications for Simulating Hydrologic Processes

Science.gov (United States)

2016-07-01

the general texture classifications. 2. Another source for soil information, such as the Food and Agriculture Organization of the United Nations (FAO...is to use another soils dataset that contains soil properties for the areas of interest, such as the Digital Soil Map of the World provided by the...www.nrcs.usda.gov/wps/portal/nrcs/main/soils/survey/ NOTE: The contents of this technical note are not to be used for advertising

Controlling the stainless steel surface wettability by nanosecond direct laser texturing at high fluences

Science.gov (United States)

Gregorčič, P.; Šetina-Batič, B.; Hočevar, M.

2017-12-01

This work investigates the influence of the direct laser texturing at high fluences (DLT-HF) on surface morphology, chemistry, and wettability. We use a Nd:YAG laser ( λ = 1064 nm) with pulse duration of 95 ns to process stainless steel surface. The surface morphology and chemistry after the texturing is examined by using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and electron backscatter diffraction (EBSD), while the surface wettability is evaluated by measuring the static contact angle. Immediately after the texturing, the surface is superhydrophilic in a saturated Wenzel regime. However, this state is not stable and the superhydrophilic-to-superhydrophobic transition happens if the sample is kept in atmospheric air for 30 days. After this period, the laser-textured stainless steel surface expresses lotus-leaf-like behavior. By using a high-speed camera at 10,000 fps, we measured that the water droplet completely rebound from this superhydrophobic surface after the contact time of 12 ms.

Effect of strontium tantalate surface texture on nickel nanoparticle dispersion by electroless deposition

Energy Technology Data Exchange (ETDEWEB)

Compean-González, C.L. [Universidad Autónoma de Nuevo León, Facultad de Ingeniería Civil, Departamento de Ecomateriales y Energía, Av. Universidad s/n, Ciudad Universitaria, San Nicolás de los Garza, Nuevo León C.P. 66451 (Mexico); Arredondo-Torres, V.M. [Facultad de Químico Farmacobiología, Universidad Michoacana de San Nicolás de Hidalgo, Tzintzuntzan #173, Col. Matamoros, Morelia, Michoacán C.P. 58240 (Mexico); Zarazúa-Morin, M.E. [Universidad Autónoma de Nuevo León, Facultad de Ingeniería Civil, Departamento de Ecomateriales y Energía, Av. Universidad s/n, Ciudad Universitaria, San Nicolás de los Garza, Nuevo León C.P. 66451 (Mexico); Figueroa-Torres, M.Z., E-mail: m.zyzlila@gmail.com [Universidad Autónoma de Nuevo León, Facultad de Ingeniería Civil, Departamento de Ecomateriales y Energía, Av. Universidad s/n, Ciudad Universitaria, San Nicolás de los Garza, Nuevo León C.P. 66451 (Mexico)

2015-09-15

Highlights: • Efficient short-time procedure for nickel nanoparticles dispersion by electroless. • Nanoparticles are spherical in shape with an average size of 15 nm. • Influence of surface texture on deposition temperature and time was observed. • Nickel deposition can be done below 50 °C. - Abstract: The present work studies the effect of smooth and porous texture of Sr{sub 2}Ta{sub 2}O{sub 7} on its surface modification with nickel nanoparticles through electroless deposition technique. The influence of temperature to control Ni nanoparticles loading amount and dispersion were analyzed. Nitrogen adsorption isotherms were used to examine surface texture characteristics. The morphology was observed by scanning electron microscopy (MEB) equipped with an energy dispersive spectrometry system (EDS), which was used to determine the amount of deposited Ni. The material with smooth texture (SMT) consists of big agglomerates of semispherical shape particles of 400 nm. Whilst the porous texture (PRT) exhibit a pore-wall formed of needles shape particles of around 200 nm in size. Results indicated that texture characteristics strongly influence the deposition reaction rate; for PRT oxide, Ni deposition can be done from 20 °C while for SMT oxide deposition begins at 40 °C. Analysis of Sr{sub 2}Ta{sub 2}O{sub 7} surface indicated that in both textures, Ni nanoparticles with spherical shape in the range of 10–20 nm were obtained.

Ion beam texturing

Science.gov (United States)

Hudson, W. R.

1977-01-01

A microscopic surface texture was created by sputter-etching a surface while simultaneously sputter-depositing a lower sputter yield material onto the surface. A xenon ion-beam source was used to perform the texturing process on samples as large as 3-cm diameter. Textured surfaces have been characterized with SEM photomicrographs for a large number of materials including Cu, Al, Si, Ti, Ni, Fe, stainless steel, Au, and Ag. A number of texturing parameters are studied including the variation of texture with ion-beam powder, surface temperature, and the rate of texture growth with sputter etching time.

A CNN Based Approach for Garments Texture Design Classification

Directory of Open Access Journals (Sweden)

S.M. Sofiqul Islam

2017-05-01

Full Text Available Identifying garments texture design automatically for recommending the fashion trends is important nowadays because of the rapid growth of online shopping. By learning the properties of images efficiently, a machine can give better accuracy of classification. Several Hand-Engineered feature coding exists for identifying garments design classes. Recently, Deep Convolutional Neural Networks (CNNs have shown better performances for different object recognition. Deep CNN uses multiple levels of representation and abstraction that helps a machine to understand the types of data more accurately. In this paper, a CNN model for identifying garments design classes has been proposed. Experimental results on two different datasets show better results than existing two well-known CNN models (AlexNet and VGGNet and some state-of-the-art Hand-Engineered feature extraction methods.

Effect of Q-switched Laser Surface Texturing of Titanium on Osteoblast Cell Response

Science.gov (United States)

Voisey, K. T.; Scotchford, C. A.; Martin, L.; Gill, H. S.

Titanium and its alloys are important biomedical materials. It is known that the surface texture of implanted medical devices affects cell response. Control of cell response has the potential to enhance fixation of implants into bone and, in other applications, to prevent undesired cell adhesion. The potential use of a 100W Q-switched YAG laser miller (DMG Lasertec 60 HSC) for texturing titanium is investigated. A series of regular features with dimensions of the order of tens of micrometers are generated in the surface of titanium samples and the cell response to these features is determined. Characterisation of the laser milled features reveals features with a lengthscale of a few microns superposed on the larger scale structures, this is attributed to resolidification of molten droplets generated and propelled over the surface by individual laser pulses. The laser textured samples are exposed to osteoblast cells and it is seen that cells do respond to the features in the laser textured surfaces.

Forward impact extrusion of surface textured steel blanks using coated tooling

Science.gov (United States)

Hild, Rafael; Feuerhack, Andreas; Trauth, Daniel; Arghavani, Mostafa; Kruppe, Nathan C.; Brögelmann, Tobias; Bobzin, Kirsten; Klocke, Fritz

2017-10-01

A method to enable dry metal forming by the means of a self-lubricating coating and surface textures was researched using an innovative Pin-On-Cylinder-Tribometer. The experimental analysis was complemented by a numerical model of the complex contact conditions between coated tools and the surface textured specimen at the micro-level. Based on the results, the explanation of the tribological interactions between surface textured specimens and the tool in dry full forward extrusion is the objective of this work. Therefore, experimental dry extrusion tests were performed using a tool system. The extruded specimens were evaluated regarding their geometry as well as by the required punch force. Thereby, the effectiveness and the feasibility of dry metal forming on the example of full forward extrusion was evaluated. Thus, one more step towards the technical realization of dry metal forming of low alloy steels under industrial conditions was realized.

Characteristics of laser textured silicon surface and effect of mud adhesion on hydrophobicity

Energy Technology Data Exchange (ETDEWEB)

Yilbas, B.S., E-mail: bsyilbas@kfupm.edu.sa [ME Department, King Fahd University of Petroleum & Minerals, Kfupm box 1913, Dhahran 31261 (Saudi Arabia); Ali, H. [ME Department, King Fahd University of Petroleum & Minerals, Kfupm box 1913, Dhahran 31261 (Saudi Arabia); Khaled, M. [CHEM Department, King Fahd University of Petroleum & Minerals, Dhahran (Saudi Arabia); Al-Aqeeli, N.; Abu-Dheir, N. [ME Department, King Fahd University of Petroleum & Minerals, Kfupm box 1913, Dhahran 31261 (Saudi Arabia); Varanasi, K.K. [Mechanical Engineering, Massachusetts Institute of Technology, Boston, MA (United States)

2015-10-01

Highlights: • Laser treatment increases surface microhardness and slightly lowers surface fracture toughness. • Residual stress formed is compressive and self-annealing effect of laser tracks lowers residual stress. • Nitride species lowers surface energy and adhesion work required to remove dust. • Mud residues do not have notable effect on fracture toughness and microhardness of treated surface. • Mud residues lower surface hydrophobicity. - Abstract: Laser gas assisted texturing of silicon wafer surface is carried out. Morphological and metallurgical changes in the treated layer are examined using the analytical tools. Microhardness and fracture toughness of the laser treated surface are measured using the indentation technique while residual stress formed is determined from the X-ray diffraction data. The hydrophobicity of the textured surfaces are assessed incorporating the contact angle data and compared with those of as received workpiece surfaces. Environmental dust accumulation and mud formation, due to air humidity, at the laser treated and as received workpiece surfaces are simulated and the effect of the mud residues on the properties of the laser treated surface are studied. The adhesion work due to the presence of the mud on the laser treated surface is also measured. It is found that laser textured surface composes of micro/nano poles and fibers, which in turn improves the surface hydrophobicity significantly. In addition, formation of nitride species contributes to microhardness increase and enhancement of surface hydrophobicity due to their low surface energy. The mud residues do not influence the fracture toughness and microhardness of the laser textured surface; however, they reduced the surface hydrophobicity significantly.

Application des ondelettes à l'analyse de texture et à l'inspection de surface industrielle

Science.gov (United States)

Wolf, D.; Husson, R.

1993-11-01

This paper presents a method of texture analysis based on multiresolution wavelets analysis. We discuss the problem of theoretical and experimental choice of the wavelet. Statistical modelling of wavelet images is treated and it results in considering statistical distribution to be a generalized Gaussian law. An algorithm for texture classification is developed with respect of the variances of different wavelet images. An industrial application of this algorithm illustrates its quality and proves its aptitude for automation of certain tasks in industrial control. Nous présentons une méthode d'analyse de texture fondée sur l'analyse multirésolution par ondelettes. Nous discutons du problème du choix théorique et expérimental de l'ondelette. Le problème de la modélisation statistique des images d'ondelettes est traité et aboutit à considérer la distribution statistique comme une loi de Gauss généralisée. Un algorithme de classification de texture est construit à l'aide de la variance des différentes images d'ondelettes. Enfin, une application industrielle de cet algorithme illustre ses qualités et démontre son aptitude à l'automatisation de certaines tâches de contrôle industriel.

Conical surface textures formed by ion bombarding 2% Be-Cu alloy

International Nuclear Information System (INIS)

Panitz, J.K.G.

1991-01-01

A homogeneous, micrometer-sized conical surface texture forms on 2% Be-Cu alloy which is bombarded with an argon beam produced by a Kaufman ion source. The dimensions of the features that form depend strongly on argon energy (from 250 to 1500 eV); argon fluence (10 19 to 10 20 ions cm -2 ); and argon flux (0.1 to 1 mA cm -2 ). The texture morphology depends less strongly on the background ambient (Mo versus graphite), earlier alloy heat treatments and the temperature during bombardment (100 o C and 450 o C). As the texture matures with increasing fluence, the number of large features increases at the expense of the number of small features. The observed relationship between texture formation and ion flux suggests that the evolution of these features is not adequately described by theories predicting that the mature conical side-wall angle is related to the angle of the maximum sputtering yield. These textured surfaces can be coated with other metals for a variety of possible applications including pulsed power Li + beam anodes; cold cathode field emission devices; optical absorbers and catalysis supports. (author)

Conical surface textures formed by ion bombarding 2% Be Cu alloy

International Nuclear Information System (INIS)

Panitz, J.K.G.

1990-01-01

A homogeneous, micrometer-sized conical surface texture forms on 2% Be-Cu alloy which is bombarded with an argon beam produced by a Kaufman ion source. The dimensions of the features that form strongly depend on: (1) argon energy (from 250 to 1500 eV), (2) fluence (10 19 to 10 20 ions/cm 2 ), and (3) flux (0.1 to 1 mA/cm 2 ). The texture morphology depends less strongly on the background ambient (Mo vs graphite), earlier alloy heat treatments and the temperature during bombardment (100 degree C and 450 degree C). As the texture matures with increasing fluence, the number of large features increases at the expense of the number of small features. The observed relationship between texture formation and ion flux suggests that the evolution of these features is not adequately described by theories predicting that the mature conical sidewall angle is related to the angle of the maximum sputtering yield. These textured surfaces can be coated with other metals for a variety of possible applications including: (1) pulsed power Li+ beam anodes, (2) cold cathode field emission devices, (3) optical absorbers and (4) catalysis supports. 18 refs., 5 figs

Textured surface structures formed using new techniques on transparent conducting Al-doped zinc oxide films prepared by magnetron sputtering

International Nuclear Information System (INIS)

Minami, Tadatsugu; Miyata, Toshihiro; Uozaki, Ryousuke; Sai, Hitoshi; Koida, Takashi

2016-01-01

Surface-textured Al-doped ZnO (AZO) films formed using two new techniques based on magnetron sputtering deposition were developed by optimizing the light scattering properties to be suitable for transparent electrode applications in thin-film silicon solar cells. Scrambled egg-like surface-textured AZO films were prepared using a new texture formation technique that post-etched pyramidal surface-textured AZO films prepared under deposition conditions suppressing c-axis orientation. In addition, double surface-textured AZO films were prepared using another new texture formation technique that completely removed, by post-etching, the pyramidal surface-textured AZO films previously prepared onto the initially deposited low resistivity AZO films; simultaneously, the surface of the low resistivity films was slightly etched. However, the obtained very high haze value in the range from the near ultraviolet to visible light in the scrambled egg-like surface-textured AZO films did not contribute significantly to the obtainable photovoltaic properties in the solar cells fabricated using the films. Significant light scattering properties as well as a low sheet resistance could be achieved in the double surface-textured AZO films. In addition, a significant improvement of external quantum efficiency in the range from the near ultraviolet to visible light was achieved in superstrate-type n-i-p μc-Si:H solar cells fabricated using a double surface-textured AZO film prepared under optimized conditions as the transparent electrode. - Highlights: • Double surface-textured AZO films prepared using a new texture formation technique • Extensive light scattering properties with low sheet resistance achieved in the double surface-textured AZO films • Improved external quantum efficiency of μc-Si:H solar cells using a double surface-textured AZO film

Textured surface structures formed using new techniques on transparent conducting Al-doped zinc oxide films prepared by magnetron sputtering

Energy Technology Data Exchange (ETDEWEB)

Minami, Tadatsugu [Optoelectronic Device System R& D Center, Kanazawa Institute of Technology, Nonoichi, Ishikawa 921-8501 (Japan); Miyata, Toshihiro, E-mail: tmiyata@neptune.kanazawa-it.ac.jp [Optoelectronic Device System R& D Center, Kanazawa Institute of Technology, Nonoichi, Ishikawa 921-8501 (Japan); Uozaki, Ryousuke [Optoelectronic Device System R& D Center, Kanazawa Institute of Technology, Nonoichi, Ishikawa 921-8501 (Japan); Sai, Hitoshi; Koida, Takashi [Research Center for Photovoltaics, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8568 (Japan)

2016-09-01

Surface-textured Al-doped ZnO (AZO) films formed using two new techniques based on magnetron sputtering deposition were developed by optimizing the light scattering properties to be suitable for transparent electrode applications in thin-film silicon solar cells. Scrambled egg-like surface-textured AZO films were prepared using a new texture formation technique that post-etched pyramidal surface-textured AZO films prepared under deposition conditions suppressing c-axis orientation. In addition, double surface-textured AZO films were prepared using another new texture formation technique that completely removed, by post-etching, the pyramidal surface-textured AZO films previously prepared onto the initially deposited low resistivity AZO films; simultaneously, the surface of the low resistivity films was slightly etched. However, the obtained very high haze value in the range from the near ultraviolet to visible light in the scrambled egg-like surface-textured AZO films did not contribute significantly to the obtainable photovoltaic properties in the solar cells fabricated using the films. Significant light scattering properties as well as a low sheet resistance could be achieved in the double surface-textured AZO films. In addition, a significant improvement of external quantum efficiency in the range from the near ultraviolet to visible light was achieved in superstrate-type n-i-p μc-Si:H solar cells fabricated using a double surface-textured AZO film prepared under optimized conditions as the transparent electrode. - Highlights: • Double surface-textured AZO films prepared using a new texture formation technique • Extensive light scattering properties with low sheet resistance achieved in the double surface-textured AZO films • Improved external quantum efficiency of μc-Si:H solar cells using a double surface-textured AZO film.

An automated classification system for the differentiation of obstructive lung diseases based on the textural analysis of HRCT images

International Nuclear Information System (INIS)

Park, Seong Hoon; Seo, Joon Beom; Kim, Nam Kug; Lee, Young Kyung; Kim, Song Soo; Chae, Eun Jin; Lee, June Goo

2007-01-01

To develop an automated classification system for the differentiation of obstructive lung diseases based on the textural analysis of HRCT images, and to evaluate the accuracy and usefulness of the system. For textural analysis, histogram features, gradient features, run length encoding, and a co-occurrence matrix were employed. A Bayesian classifier was used for automated classification. The images (image number n = 256) were selected from the HRCT images obtained from 17 healthy subjects (n = 67), 26 patients with bronchiolitis obliterans (n = 70), 28 patients with mild centrilobular emphysema (n = 65), and 21 patients with panlobular emphysema or severe centrilobular emphysema (n = 63). An five-fold cross-validation method was used to assess the performance of the system. Class-specific sensitivities were analyzed and the overall accuracy of the system was assessed with kappa statistics. The sensitivity of the system for each class was as follows: normal lung 84.9%, bronchiolitis obliterans 83.8%, mild centrilobular emphysema 77.0%, and panlobular emphysema or severe centrilobular emphysema 95.8%. The overall performance for differentiating each disease and the normal lung was satisfactory with a kappa value of 0.779. An automated classification system for the differentiation between obstructive lung diseases based on the textural analysis of HRCT images was developed. The proposed system discriminates well between the various obstructive lung diseases and the normal lung

Modulated surface textures for enhanced scattering in thin-film silicon solar cells

NARCIS (Netherlands)

Isabella, O.; Battaglia, C.; Ballif, C.; Zeman, M.

2012-01-01

Nano-scale randomly textured front transparent oxides are superposed on micro-scale etched glass substrates to form modulated surface textures. The resulting enhanced light scattering is implemented in single and double junction thin-film silicon solar cells.

Effects of surface treatments on the translucency, opalescence, and surface texture of dental monolithic zirconia ceramics.

Science.gov (United States)

Kim, Hee-Kyung; Kim, Sung-Hun; Lee, Jai-Bong; Ha, Seung-Ryong

2016-06-01

Surface polishing or glazing may increase the appearance of depth of monolithic zirconia restorations. The purpose of this in vitro study was to investigate the effects of surface treatments on the translucency, opalescence, and surface texture of dental monolithic zirconia ceramics. Forty-five monolithic zirconia specimens (16.3×16.4×2.0 mm) were divided into groups I to V, according to the number of colorings each received. Each group was then divided into 3 subgroups (n=3) according to the surface treatment: N=no treatment; P=polished; and G=glazed. CIElab color coordinates were obtained relative to D65 on a reflection spectrophotometer. The translucency parameter (TP) and opalescence parameter (OP) were calculated. One specimen per subgroups I and V was selected for evaluation of surface roughness (Ra) and was examined with scanning electron microscopy (SEM). Data were analyzed with 2-way ANOVA and pairwise comparisons (α=.05). Statistical powers were verified to evaluate results (α=.05). The interaction effects of surface treatments combined with the number of colorings were significant for TP, OP, and Ra (P.05), whereas glazing significantly decreased OP and Ra in most groups. SEM images demonstrated that surface treatments affected the surface texture of monolithic zirconia ceramics. Surface treatments combined with coloring strongly affect the surface texture of dental monolithic zirconia ceramics. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Picosecond laser micro/nano surface texturing of nickel for superhydrophobicity

Science.gov (United States)

Wang, X. C.; Wang, B.; Xie, H.; Zheng, H. Y.; Lam, Y. C.

2018-03-01

A single step direct picosecond laser texturing process was demonstrated to be able to obtain a superhydrophobic surface on a nickel substrate, a key material for mold fabrication in the manufacture of various devices, including polymeric microfluidic devices. A two-scale hierarchical surface structure of regular 2D array micro-bumps with nano-ripples was produced on a nickel surface. The laser textured surface initially showed superhydrophilicity with almost complete wetting of the structured surface just after laser treatment, then quickly changed to nearly superhydrophobic with a water contact angle (WCA) of 140° in less than 1 d, and finally became superhydrophobic with a WCA of more than 150° and a contact angle hysteresis (CAH) of less than 5°. The mechanism involved in the process is discussed in terms of surface morphology and surface chemistry. The ultra-fast laser induced NiO catalytic effect was thought to play a key role in modifying the surface chemistry so as to lower the surface energy. The developed process has the potential to improve the performance of nickel mold in the fabrication of microfluidic devices.

Textural Analysis of Fatique Crack Surfaces: Image Pre-processing

Directory of Open Access Journals (Sweden)

H. Lauschmann

2000-01-01

Full Text Available For the fatique crack history reconstitution, new methods of quantitative microfractography are beeing developed based on the image processing and textural analysis. SEM magnifications between micro- and macrofractography are used. Two image pre-processing operatins were suggested and proved to prepare the crack surface images for analytical treatment: 1. Normalization is used to transform the image to a stationary form. Compared to the generally used equalization, it conserves the shape of brightness distribution and saves the character of the texture. 2. Binarization is used to transform the grayscale image to a system of thick fibres. An objective criterion for the threshold brightness value was found as that resulting into the maximum number of objects. Both methods were succesfully applied together with the following textural analysis.

Shape and Texture Based Classification of Fish Species

DEFF Research Database (Denmark)

Larsen, Rasmus; Ólafsdóttir, Hildur; Ersbøll, Bjarne Kjær

2009-01-01

In this paper we conduct a case study of ¯sh species classi- fication based on shape and texture. We consider three fish species: cod, haddock, and whiting. We derive shape and texture features from an appearance model of a set of training data. The fish in the training images were manual outlined......, and a few features including the eye and backbone contour were also annotated. From these annotations an optimal MDL curve correspondence and a subsequent image registration were derived. We have analyzed a series of shape and texture and combined shape and texture modes of variation for their ability...

Effect of Groove Surface Texture on Tribological Characteristics and Energy Consumption under High Temperature Friction.

Science.gov (United States)

Wu, Wei; Chen, Guiming; Fan, Boxuan; Liu, Jianyou

2016-01-01

Energy consumption and tribological properties could be improved by proper design of surface texture in friction. However, some literature focused on investigating their performance under high temperature. In the study, different groove surface textures were fabricated on steels by a laser machine, and their tribological behaviors were experimentally studied with the employment of the friction and wear tester under distinct high temperature and other working conditions. The friction coefficient was recorded, and wear performance were characterized by double light interference microscope, scanning electron microscope (SEM) and x-ray energy dispersive spectrometry (EDS). Then, the performances of energy consumptions were carefully estimated. Results showed that friction coefficient, wear, and energy consumption could almost all be reduced by most textures under high temperature conditions, but to a different extent which depends on the experimental conditions and texture parameters. The main improvement mechanisms were analyzed, such as the hardness change, wear debris storage, thermal stress release and friction induced temperature reduction by the textures. Finally, a scattergram of the relatively reduced ratio of the energy consumption was drawn for different surface textures under four distinctive experimental conditions to illustrate the comprehensive energy consumption improving ability of textures, which was of benefit for the application of texture design.

Automotive System for Remote Surface Classification.

Science.gov (United States)

Bystrov, Aleksandr; Hoare, Edward; Tran, Thuy-Yung; Clarke, Nigel; Gashinova, Marina; Cherniakov, Mikhail

2017-04-01

In this paper we shall discuss a novel approach to road surface recognition, based on the analysis of backscattered microwave and ultrasonic signals. The novelty of our method is sonar and polarimetric radar data fusion, extraction of features for separate swathes of illuminated surface (segmentation), and using of multi-stage artificial neural network for surface classification. The developed system consists of 24 GHz radar and 40 kHz ultrasonic sensor. The features are extracted from backscattered signals and then the procedures of principal component analysis and supervised classification are applied to feature data. The special attention is paid to multi-stage artificial neural network which allows an overall increase in classification accuracy. The proposed technique was tested for recognition of a large number of real surfaces in different weather conditions with the average accuracy of correct classification of 95%. The obtained results thereby demonstrate that the use of proposed system architecture and statistical methods allow for reliable discrimination of various road surfaces in real conditions.

Surface inspection of flat products by means of texture analysis: on-line implementation using neural networks

Science.gov (United States)

Fernandez, Carlos; Platero, Carlos; Campoy, Pascual; Aracil, Rafael

1994-11-01

This paper describes some texture-based techniques that can be applied to quality assessment of flat products continuously produced (metal strips, wooden surfaces, cork, textile products, ...). Since the most difficult task is that of inspecting for product appearance, human-like inspection ability is required. A common feature to all these products is the presence of non- deterministic texture on their surfaces. Two main subjects are discussed: statistical techniques for both surface finishing determination and surface defect analysis as well as real-time implementation for on-line inspection in high-speed applications. For surface finishing determination a Gray Level Difference technique is presented to perform over low resolution images, that is, no-zoomed images. Defect analysis is performed by means of statistical texture analysis over defective portions of the surface. On-line implementation is accomplished by means of neural networks. When a defect arises, textural analysis is applied which result in a data-vector, acting as input of a neural net, previously trained in a supervised way. This approach tries to reach on-line performance in automated visual inspection applications when texture is presented in flat product surfaces.

Breast tissue classification in digital breast tomosynthesis images using texture features: a feasibility study

Science.gov (United States)

Kontos, Despina; Berger, Rachelle; Bakic, Predrag R.; Maidment, Andrew D. A.

2009-02-01

Mammographic breast density is a known breast cancer risk factor. Studies have shown the potential to automate breast density estimation by using computerized texture-based segmentation of the dense tissue in mammograms. Digital breast tomosynthesis (DBT) is a tomographic x-ray breast imaging modality that could allow volumetric breast density estimation. We evaluated the feasibility of distinguishing between dense and fatty breast regions in DBT using computer-extracted texture features. Our long-term hypothesis is that DBT texture analysis can be used to develop 3D dense tissue segmentation algorithms for estimating volumetric breast density. DBT images from 40 women were analyzed. The dense tissue area was delineated within each central source projection (CSP) image using a thresholding technique (Cumulus, Univ. Toronto). Two (2.5cm)2 ROIs were manually selected: one within the dense tissue region and another within the fatty region. Corresponding (2.5cm)3 ROIs were placed within the reconstructed DBT images. Texture features, previously used for mammographic dense tissue segmentation, were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance. Different texture features appeared to perform best in the 3D reconstructed DBT compared to the 2D CSP images. Fractal dimension was superior in DBT (AUC=0.90), while contrast was best in CSP images (AUC=0.92). We attribute these differences to the effects of tissue superimposition in CSP and the volumetric visualization of the breast tissue in DBT. Our results suggest that novel approaches, different than those conventionally used in projection mammography, need to be investigated in order to develop DBT dense tissue segmentation algorithms for estimating volumetric breast density.

UV laser-ablated surface textures as potential regulator of cellular response.

Science.gov (United States)

Chandra, Prafulla; Lai, Karen; Sung, Hak-Joon; Murthy, N Sanjeeva; Kohn, Joachim

2010-06-01

Textured surfaces obtained by UV laser ablation of poly(ethylene terephthalate) films were used to study the effect of shape and spacing of surface features on cellular response. Two distinct patterns, cones and ripples with spacing from 2 to 25 μm, were produced. Surface features with different shapes and spacings were produced by varying pulse repetition rate, laser fluence, and exposure time. The effects of the surface texture parameters, i.e., shape and spacing, on cell attachment, proliferation, and morphology of neonatal human dermal fibroblasts and mouse fibroblasts were studied. Cell attachment was the highest in the regions with cones at ∼4 μm spacing. As feature spacing increased, cell spreading decreased, and the fibroblasts became more circular, indicating a stress-mediated cell shrinkage. This study shows that UV laser ablation is a useful alternative to lithographic techniques to produce surface patterns for controlling cell attachment and growth on biomaterial surfaces.

Spin texture of the surface state of three-dimensional Dirac material Ca3PbO

Science.gov (United States)

Kariyado, Toshikaze

2015-04-01

The bulk and surface electronic structures of a candidate three-dimensional Dirac material Ca3PbO and its family are discussed especially focusing on the spin texture on the surface states. We first explain the basic features of the bulk band structure of Ca3PbO, such as emergence of Dirac fermions near the Fermi energy, and compare it with the other known three-dimensional Dirac semimetals. Then, the surface bands and spin-texture on them are investigated in detail. It is shown that the surface bands exhibit strong momentum-spin locking, which may be useful in some application for spin manipulation, induced by a combination of the inversion symmetry breaking at the surface and the strong spin-orbit coupling of Pb atoms. The surface band structure and the spin-textures are sensitive to the surface types.

Spin texture of the surface state of three-dimensional Dirac material Ca3PbO

International Nuclear Information System (INIS)

Kariyado, Toshikaze

2015-01-01

The bulk and surface electronic structures of a candidate three-dimensional Dirac material Ca 3 PbO and its family are discussed especially focusing on the spin texture on the surface states. We first explain the basic features of the bulk band structure of Ca 3 PbO, such as emergence of Dirac fermions near the Fermi energy, and compare it with the other known three-dimensional Dirac semimetals. Then, the surface bands and spin-texture on them are investigated in detail. It is shown that the surface bands exhibit strong momentum-spin locking, which may be useful in some application for spin manipulation, induced by a combination of the inversion symmetry breaking at the surface and the strong spin-orbit coupling of Pb atoms. The surface band structure and the spin-textures are sensitive to the surface types. (paper)

Influence of citric acid on the surface texture of glass ionomer restorative materials.

Science.gov (United States)

Reddy, Dappili Swami Ranga; Kumar, Ramachandran Anil; Venkatesan, Sokkalingam Mothilal; Narayan, Gopal Shankar; Duraivel, Dasarathan; Indra, Rajamani

2014-09-01

This study determined the effectiveness of G-coat plus surface protective agent over petroleum jelly on the surface texture of conventional Glass ionomer restorative materials. Three chemically cured conventional glass ionomer restorative materials type II, type IX and ketac molar were evaluated in this study. Sixty specimens were made for each restorative material. They were divided into two groups of thirty specimens each. Of the sixty specimens, thirty were coated with G-coat plus (a nano-filler coating) and the rest with petroleum jelly. Thirty samples of both protective coating agents were randomly divided into six groups of five specimens and conditioned in citric acid solutions of differing pH (pH 2, 3, 4, 5, 6 & 7). Each specimen was kept in citric acid for three hours a day, and the rest of time stored in salivary substitute. This procedure was repeated for 8 days. After conditioning, the surface roughness (Ra, μm) of each specimen was measured using a surface profilometer (Taylor & Habson, UK). Data was analyzed using one-way analysis of variance (ANOVA) and Tukey's HSD test at a significance level of 0.05. The surface textures of all the tested glass ionomer restorative materials protected with G-coat plus were not significantly affected by acids at low pH. The surface textures of all the tested glass ionomer restorative materials protected with petroleum jelly coating were significantly affected by acids at low pH. The effects of pH on the surface texture of glass ionomer restoratives are material dependent. Among all the materials tested the surface texture of Type II GIC (Group I) revealed marked deterioration when conditioned in solutions of low pH and was statistically significant. Hence, a protective coating either with G-coat plus or with light polymerized low viscosity unfilled resin adhesives is mandatory for all the glass ionomer restorations to increase the wear resistance of the restorative materials.

The effect of texture on the shaft surface on the sealing performance of radial lip seals

Science.gov (United States)

Guo, Fei; Jia, XiaoHong; Gao, Zhi; Wang, YuMing

2014-07-01

On the basis of elastohydrodynamic model, the present study numerically analyzes the effect of various microdimple texture shapes, namely, circular, square, oriented isosceles triangular, on the pumping rate and the friction torque of radial lip seals, and determines the microdimple texture shape that can produce positive pumping rate. The area ratio, depth and shape dimension of a single texture are the most important geometric parameters which influence the tribological performance. According to the selected texture shape, parameter analysis is conducted to determine the optimal combination for the above three parameters. Simultaneously, the simulated performances of radial lip seal with texture on the shaft surface are compared with those of the conventional lip seal without any texture on the shaft surface.

Tribological analysis of the ventral scale structure in a Python regius in relation to laser textured surfaces

International Nuclear Information System (INIS)

Abdel-Aal, H A; El Mansori, M

2013-01-01

Laser texturing is one of the leading technologies applied to modify surface topography. To date, however, a standardized procedure to generate deterministic textures is virtually non-existent. In nature, especially in squamata, there are many examples of deterministic structured textures that allow species to control friction and condition their tribological response for efficient function. In this work, we draw a comparison between industrial surfaces and reptilian surfaces. We chose the Python regius species as a bio-analogue with a deterministic surface. We first study the structural make up of the ventral scales of the snake (both construction and metrology). We further compare the metrological features of the ventral scales to experimentally recommended performance indicators of industrial surfaces extracted from open literature. The results indicate the feasibility of engineering a laser textured surface based on the reptilian ornamentation constructs. It is shown that the metrological features, key to efficient function of a rubbing deterministic surface, are already optimized in the reptile. We further show that optimization in reptilian surfaces is based on synchronizing surface form, textures and aspects to condition the frictional response. Mimicking reptilian surfaces, we argue, may form a design methodology potentially capable of generating advanced deterministic surface constructs capable of efficient tribological function. (paper)

Effect of texture randomization on the slip and interfacial robustness in turbulent flows over superhydrophobic surfaces

Science.gov (United States)

Seo, Jongmin; Mani, Ali

2018-04-01

Superhydrophobic surfaces demonstrate promising potential for skin friction reduction in naval and hydrodynamic applications. Recent developments of superhydrophobic surfaces aiming for scalable applications use random distribution of roughness, such as spray coating and etched process. However, most previous analyses of the interaction between flows and superhydrophobic surfaces studied periodic geometries that are economically feasible only in laboratory-scale experiments. In order to assess the drag reduction effectiveness as well as interfacial robustness of superhydrophobic surfaces with randomly distributed textures, we conduct direct numerical simulations of turbulent flows over randomly patterned interfaces considering a range of texture widths w+≈4 -26 , and solid fractions ϕs=11 %-25 % . Slip and no-slip boundary conditions are implemented in a pattern, modeling the presence of gas-liquid interfaces and solid elements. Our results indicate that slip of randomly distributed textures under turbulent flows is about 30 % less than those of surfaces with aligned features of the same size. In the small texture size limit w+≈4 , the slip length of the randomly distributed textures in turbulent flows is well described by a previously introduced Stokes flow solution of randomly distributed shear-free holes. By comparing DNS results for patterned slip and no-slip boundary against the corresponding homogenized slip length boundary conditions, we show that turbulent flows over randomly distributed posts can be represented by an isotropic slip length in streamwise and spanwise direction. The average pressure fluctuation on a gas pocket is similar to that of the aligned features with the same texture size and gas fraction, but the maximum interface deformation at the leading edge of the roughness element is about twice as large when the textures are randomly distributed. The presented analyses provide insights on implications of texture randomness on drag

Nanoscale silver-assisted wet etching of crystalline silicon for anti-reflection surface textures.

Science.gov (United States)

Li, Rui; Wang, Shuling; Chuwongin, Santhad; Zhou, Weidong

2013-01-01

We report here an electro-less metal-assisted chemical etching (MacEtch) process as light management surface-texturing technique for single crystalline Si photovoltaics. Random Silver nanostructures were formed on top of the Si surface based on the thin film evaporation and annealing process. Significant reflection reduction was obtained from the fabricated Si sample, with approximately 2% reflection over a wide spectra range (300 to 1050 nm). The work demonstrates the potential of MacEtch process for anti-reflection surface texture fabrication of large area, high efficiency, and low cost thin film solar cell.

Investigations on femtosecond laser modified micro-textured surface with anti-friction property on bearing steel GCr15

Science.gov (United States)

Yang, Lijun; Ding, Ye; Cheng, Bai; He, Jiangtao; Wang, Genwang; Wang, Yang

2018-03-01

This work puts forward femtosecond laser modification of micro-textured surface on bearing steel GCr15 in order to reduce frictional wear and enhance load capacity during its application. Multi pulses femtosecond laser ablation experiments are established for the confirmation of laser spot radius as well as single pulse threshold fluence and pulse incubation coefficient of bulk material. Analytical models are set up in combination with hydrodynamics lubrication theory. Corresponding simulations are carried out on to explore influences of surface and cross sectional morphology of textures on hydrodynamics lubrication effect based on Navier-Stokes (N-S) equation. Technological experiments focus on the impacts of femtosecond laser machining variables, like scanning times, scanning velocity, pulse frequency and scanning gap on morphology of grooves as well as realization of optimized textures proposed by simulations, mechanisms of which are analyzed from multiple perspectives. Results of unidirectional rotating friction tests suggest that spherical texture with depth-to-width ratio of 0.2 can significantly improve tribological properties at low loading and velocity condition comparing with un-textured and other textured surfaces, which also verifies the accuracy of simulations and feasibility of femtosecond laser in modification of micro-textured surface.

Surface passivation of nano-textured fluorescent SiC by atomic layer deposited TiO2

DEFF Research Database (Denmark)

Lu, Weifang; Ou, Yiyu; Jokubavicius, Valdas

2016-01-01

Nano-textured surfaces have played a key role in optoelectronic materials to enhance the light extraction efficiency. In this work, morphology and optical properties of nano-textured SiC covered with atomic layer deposited (ALD) TiO2 were investigated. In order to obtain a high quality surface fo...

Surface Textural Analysis of Quartz Grains from Modern Point Bar Deposits in Lower Reaches of the Yellow River

Science.gov (United States)

Cheng, Yong; Liu, Cong; Lu, Ping; Zhang, Yu; Nie, Qi; Wen, Yiming

2018-01-01

The surfaces of quartz grains contain characteristic textures formed during the process of transport, due to their stable physical and chemical properties. The surface textures include the information about source area, transporting force, sedimentary environment and evolution history of sediment. Surface textures of quartz grains from modern point bar deposits in the lower reaches of the Yellow River are observed and studied by scanning electron microscopy (SEM). Results indicate that there are 22 kinds of surface textures. The overall surface morphology of quartz grains shows short transporting time and distance and weak abrasive action of the river water. The combined surface textures caused by mechanical action indicate that quartz grains are transporting in a high-energy hydrodynamic condition and suffer a strong mechanical impact and abrasion. The common solution pits prove that the chemical property of transportation medium is very active and quartz grains receive an obvious chemical action. The combination of these surface textures can be an identification mark of fluvial environment, and that is: quartz grains are main subangular outline, whose roundness is higher with the farther motion distance; Surface fluctuation degree of quartz grains is relatively high, and gives priority to high and medium relief; V-shaped percussion marks are very abundant caused by mechanical action; The conchoidal of different sizes and steps are common-developed with paragenesis relationship; Solution pits are common-developed as well. The study makes up for the blank of surface textures analysis of quartz grains from modern fluvial deposits in China. It provides new ideas and evidence for studies of the sedimentary process and environmental significance, although the deep meanings of these micro textures remain to be further researched.

Broadband absorption enhancement in amorphous Si solar cells using metal gratings and surface texturing

Science.gov (United States)

Magdi, Sara; Swillam, Mohamed A.

2017-02-01

The efficiencies of thin film amorphous silicon (a-Si) solar cells are restricted by the small thickness required for efficient carrier collection. This thickness limitations result in poor light absorption. In this work, broadband absorption enhancement is theoretically achieved in a-Si solar cells by using nanostructured back electrode along with surface texturing. The back electrode is formed of Au nanogratings and the surface texturing consists of Si nanocones. The results were then compared to random texturing surfaces. Three dimensional finite difference time domain (FDTD) simulations are used to design and optimize the structure. The Au nanogratings achieved absorption enhancement in the long wavelengths due to sunlight coupling to surface plasmon polaritons (SPP) modes. High absorption enhancement was achieved at short wavelengths due to the decreased reflection and enhanced scattering inside the a-Si absorbing layer. Optimizations have been performed to obtain the optimal geometrical parameters for both the nanogratings and the periodic texturing. In addition, an enhancement factor (i.e. absorbed power in nanostructured device/absorbed power in reference device) was calculated to evaluate the enhancement obtained due to the incorporation of each nanostructure.

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

Science.gov (United States)

Rodriguez Gutierrez, D; Awwad, A; Meijer, L; Manita, M; Jaspan, T; Dineen, R A; Grundy, R G; Auer, D P

2014-05-01

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology. © 2014 by American Journal of Neuroradiology.

Surface fractal dimensions and textural properties of mesoporous alkaline-earth hydroxyapatites

International Nuclear Information System (INIS)

Vilchis-Granados, J.; Granados-Correa, F.; Barrera-Díaz, C.E.

2013-01-01

This work examines the surface fractal dimensions (D f ) and textural properties of three different alkaline-earth hydroxyapatites. Calcium, strontium and barium hydroxyapatite compounds were successfully synthesized via chemical precipitation method and characterized using X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectrometry, Fourier transform infrared spectroscopy, and N 2 -physisorption measurements. Surface fractal dimensions were determined using single N 2 -adsorption/desorption isotherms method to quantify the irregular surface of as-prepared compounds. The obtained materials were also characterized through their surface hydroxyl group content, determined by the mass titration method. It was found that the D f values for the three materials covered the range of 0.77 ± 0.04–2.33 ± 0.11; these results indicated that the materials tend to have smooth surfaces, except the irregular surface of barium hydroxyapatite. Moreover, regarding the synthesized calcium hydroxyapatite exhibited better textural properties compared with the synthesized strontium and barium hydroxyapatites for adsorbent purposes. However, barium hydroxyapatite shows irregular surface, indicating a high population of active sites across the surface, in comparison with the others studied hydroxyapatites. Finally, the results showed a linear correlation between the surface hydroxyl group content at the external surface of materials and their surface fractal dimensions.

Ultra short pulse laser generated surface textures for anti-ice applications in aviation

NARCIS (Netherlands)

Römer, G.W.; Del Cerro, D.A.; Sipkema, R.C.J.; Groenendijk, M.N.W.; Huis in 't Veld, A.J.

2009-01-01

By laser ablation with ultra short laser pulses in the pico- and femto-second range, well controlled dual scaled micro- and nano-scaled surface textures can be obtained. The micro-scale of the texture is mainly determined by the dimensions of the laser spot, whereas the superimposed nano-structure

Superhydrophylic textures fabricated by femtosecond laser pulses on sub-micro- and nano-crystalline titanium surfaces

International Nuclear Information System (INIS)

Kolobov, Yury R; Smolyakova, Marina Yu; Kolobova, Anastasia Yu; Ionin, Andrey A; Kudryashov, Sergey I; Makarov, Sergey V; Saltuganov, Pavel N; Zayarny, Dmitry A; Ligachev, Alexander E

2014-01-01

Sub-micron quasi-regular surface textures were fabricated on surfaces of pure titanium (VT1-0) with micro- and ultrafine-grained bulk structures by multiple femtosecond laser pulses in the scanning mode and characterized by scanning electron and atomic force microscopy. Their wetting characteristics acquired for the initial non-textured and as-textured samples, as well as upon ultrasonic and plasma cleaning, demonstrate corresponding drastic changes of the wetting angles from 87° to ≤ 10°, with much more pronounced contamination, cleaning and wetting effects for the ultrafine-grained titanium. (letter)

A New Rig for Testing Textured Surfaces in Pure Sliding Conditions

DEFF Research Database (Denmark)

Godi, Alessandro; Grønbæk, J.; Mohaghegh, Kamran

2013-01-01

machineries are necessary: a press to provide the normal pressure and a tensile machine to perform the axial movements. The test is calibrated so that the correspondence between the normal pressure and the container advancement is found. Preliminary tests are carried out involving a multifunctional and a fine......Throughout the years, it has become more and more important to find new methods for reducing friction and wear occurrence in machine elements. A possible solution is found in texturing the surfaces under tribological contact, as demonstrated by the development and spread of plateau-honed surface...... for cylinder liners. To prove the efficacy of a particular textured surface, it is paramount to perform experimental tests under controlled laboratory conditions. In this paper, a new test rig simulating pure sliding conditions is presented, dubbed axial sliding test. It presents four major components: a rod...

Ion-beam texturing of uniaxially textured Ni films

International Nuclear Information System (INIS)

Park, S.J.; Norton, D.P.; Selvamanickam, Venkat

2005-01-01

The formation of biaxial texture in uniaxially textured Ni thin films via Ar-ion irradiation is reported. The ion-beam irradiation was not simultaneous with deposition. Instead, the ion beam irradiates the uniaxially textured film surface with no impinging deposition flux, which differs from conventional ion-beam-assisted deposition. The uniaxial texture is established via a nonion beam process, with the in-plane texture imposed on the uniaxial film via ion beam bombardment. Within this sequential ion beam texturing method, grain alignment is driven by selective etching and grain overgrowth

The study of road surface micro-texture's effects for the pavement's decontamination by high pressure water washing

International Nuclear Information System (INIS)

Kobayashi, Masatoshi; Shimizu, Tadaaki; Hirayama, Takahiro

2014-01-01

In the result of “decontamination technical demonstration project” by Ministry of the Environment, it has became clear that the effect variation is larger in high pressure water washing method, compared with others in road surface decontamination technology. In this study, we have hypothesized the fact at the difference of micro-texture of the road surface, by carrying out high pressure water washing method in different kinds of road surfaces and verified the relation between washing efficiency and micro-texture road surface. Positive correlation has admitted between the washing number of times and radiation reduction rate and the trend of primary regression equation (i.e. radiation reduction rate per washing time) is indicating that decreasing tendency of radiation carried by the increasing of micro-texture of the road surface. Here, we proposed the method to estimated essential washing number of times to achieve the targeted radiation reduction rate from the relation of that trend and micro-texture of the road surface. (author)

Emergent Momentum-Space Skyrmion Texture on the Surface of Topological Insulators

Science.gov (United States)

Mohanta, Narayan; Kampf, Arno P.; Kopp, Thilo

The quantum anomalous Hall effect has been theoretically predicted and experimentally verified in magnetic topological insulators. In addition, the surface states of these materials exhibit a hedgehog-like ``spin'' texture in momentum space. Here, we apply the previously formulated low-energy model for Bi2Se3, a parent compound for magnetic topological insulators, to a slab geometry in which an exchange field acts only within one of the surface layers. In this sample set up, the hedgehog transforms into a skyrmion texture beyond a critical exchange field. This critical field marks a transition between two topologically distinct phases. The topological phase transition takes place without energy gap closing at the Fermi level and leaves the transverse Hall conductance unchanged and quantized to e2 / 2 h . The momentum-space skyrmion texture persists in a finite field range. It may find its realization in hybrid heterostructures with an interface between a three-dimensional topological insulator and a ferromagnetic insulator. The work was supported by the Deutsche Forschungsgemeinschaft through TRR 80.

Evaporation dynamics of completely wetting drops on geometrically textured surfaces

Science.gov (United States)

Mekhitarian, Loucine; Sobac, Benjamin; Dehaeck, Sam; Haut, Benoît; Colinet, Pierre

2017-10-01

This study deals with the evaporation dynamics of completely wetting and highly volatile drops deposited on geometrically textured but chemically homogeneous surfaces. The texturation consists in a cylindrical pillars array with a square pitch. The triple line dynamics and the drop shape are characterized by an interferometric method. A parametric study is realized by varying the radius and the height of the pillars (at fixed interpillar distance), allowing to distinguish three types of dynamics: i) an evaporation-dominated regime with a receding triple line; ii) a spreading-dominated regime with an initially advancing triple line; iii) a cross-over region with strong pinning effects. The overall picture is in qualitative agreement with a mathematical model showing that the selected regime mostly depends on the value of a dimensionless parameter comparing the time scales for evaporation and spreading into the substrate texture.

Fabrication of friction-reducing texture surface by selective laser melting of ink-printed (SLM-IP) copper (Cu) nanoparticles(NPs)

Science.gov (United States)

Wang, Xinjian; Liu, Junyan; Wang, Yang; Fu, Yanan

2017-02-01

This paper reports a process of selective laser melting of ink-printed (SLM-IP) copper (Cu) nanoparticles(NPs) for the fabrication of full dense Cu friction-reducing texture on the metallic surface in ambient condition. This technique synthesizes pure Cu by chemical reduction route using an organic solvent during laser melting in the atmosphere environment, and provides a flexible additive manufacture approach to form complex friction-reduction texture on the metallic surface. Microtextures of ring and disc arrays have been fabricated on the stainless steel surface by SLM-IP Cu NPs. The friction coefficient has been measured under the lubricating condition of the oil. Disc texture surface (DTS) has a relatively low friction coefficient compared with ring texture surface (RTS), Cu film surface (Cu-FS) and the untreated substrate. The study suggests a further research on SLM-IP approach for complex microstructure or texture manufacturing, possibly realizing its advantage of flexibility.

Dynamic Leidenfrost temperature on micro-textured surfaces: Acoustic wave absorption into thin vapor layer

Science.gov (United States)

Jerng, Dong Wook; Kim, Dong Eok

2018-01-01

The dynamic Leidenfrost phenomenon is governed by three types of pressure potentials induced via vapor hydrodynamics, liquid dynamic pressure, and the water hammer effect resulting from the generation of acoustic waves at the liquid-vapor interface. The prediction of the Leidenfrost temperature for a dynamic droplet needs quantitative evaluation and definition for each of the pressure fields. In particular, the textures on a heated surface can significantly affect the vapor hydrodynamics and the water hammer pressure. We present a quantitative model for evaluating the water hammer pressure on micro-textured surfaces taking into account the absorption of acoustic waves into the thin vapor layer. The model demonstrates that the strength of the acoustic flow into the liquid droplet, which directly contributes to the water hammer pressure, depends on the magnitude of the acoustic resistance (impedance) in the droplet and the vapor region. In consequence, the micro-textures of the surface and the increased spacing between them reduce the water hammer coefficient ( kh ) defined as the ratio of the acoustic flow into the droplet to total generated flow. Aided by numerical calculations that solve the laminar Navier-Stokes equation for the vapor flow, we also predict the dynamic Leidenfrost temperature on a micro-textured surface with reliable accuracy consistent with the experimental data.

Surface Texturing-Plasma Nitriding Duplex Treatment for Improving Tribological Performance of AISI 316 Stainless Steel

Directory of Open Access Journals (Sweden)

Naiming Lin

2016-10-01

Full Text Available Surface texturing-plasma nitriding duplex treatment was conducted on AISI 316 stainless steel to improve its tribological performance. Tribological behaviors of ground 316 substrates, plasma-nitrided 316 (PN-316, surface-textured 316 (ST-316, and duplex-treated 316 (DT-316 in air and under grease lubrication were investigated using a pin-on-disc rotary tribometer against counterparts of high carbon chromium bearing steel GCr15 and silicon nitride Si3N4 balls. The variations in friction coefficient, mass loss, and worn trace morphology of the tested samples were systemically investigated and analyzed. The results showed that a textured surface was formed on 316 after electrochemical processing in a 15 wt % NaCl solution. Grooves and dimples were found on the textured surface. As plasma nitriding was conducted on a 316 substrate and ST-316, continuous and uniform nitriding layers were successfully fabricated on the surfaces of the 316 substrate and ST-316. Both of the obtained nitriding layers presented thickness values of more than 30 μm. The nitriding layers were composed of iron nitrides and chromium nitride. The 316 substrate and ST-316 received improved surface hardness after plasma nitriding. When the tribological tests were carried out under dry sliding and grease lubrication conditions, the tested samples showed different tribological behaviors. As expected, the DT-316 samples revealed the most promising tribological properties, reflected by the lowest mass loss and worn morphologies. The DT-316 received the slightest damage, and its excellent tribological performance was attributed to the following aspects: firstly, the nitriding layer had high surface hardness; secondly, the surface texture was able to capture wear debris, store up grease, and then provide continuous lubrication.

TESTING OF LAND COVER CLASSIFICATION FROM MULTISPECTRAL AIRBORNE LASER SCANNING DATA

Directory of Open Access Journals (Sweden)

K. Bakuła

2016-06-01

Full Text Available Multispectral Airborne Laser Scanning provides a new opportunity for airborne data collection. It provides high-density topographic surveying and is also a useful tool for land cover mapping. Use of a minimum of three intensity images from a multiwavelength laser scanner and 3D information included in the digital surface model has the potential for land cover/use classification and a discussion about the application of this type of data in land cover/use mapping has recently begun. In the test study, three laser reflectance intensity images (orthogonalized point cloud acquired in green, near-infrared and short-wave infrared bands, together with a digital surface model, were used in land cover/use classification where six classes were distinguished: water, sand and gravel, concrete and asphalt, low vegetation, trees and buildings. In the tested methods, different approaches for classification were applied: spectral (based only on laser reflectance intensity images, spectral with elevation data as additional input data, and spectro-textural, using morphological granulometry as a method of texture analysis of both types of data: spectral images and the digital surface model. The method of generating the intensity raster was also tested in the experiment. Reference data were created based on visual interpretation of ALS data and traditional optical aerial and satellite images. The results have shown that multispectral ALS data are unlike typical multispectral optical images, and they have a major potential for land cover/use classification. An overall accuracy of classification over 90% was achieved. The fusion of multi-wavelength laser intensity images and elevation data, with the additional use of textural information derived from granulometric analysis of images, helped to improve the accuracy of classification significantly. The method of interpolation for the intensity raster was not very helpful, and using intensity rasters with both first and

Hardwood species classification with DWT based hybrid texture ...

Indian Academy of Sciences (India)

to decompose the image up to 7 levels using Daubechies (db3) wavelet as decom ... binary pattern (DWTFOSLBPu2) texture features at the 4th level of image decomposi ...... In addition, inclusion of further levels of image decomposition gives rise to ..... Texture analysis of SAR sea ice imagery using gray level co-occurrence.

All Organic Polymers Based Morphing Skin with Controllable Surface Texture

KAUST Repository

Favero Bolson, Natanael

2018-05-01

Smart skins are integrating an increasing number of functionalities in order to improve the interaction between the systems they equip and their ambient environment. Here we have developed an electromechanical soft actuator with controlled surface texture due to applied thermal gradient via electrical voltage. The device was fabricated and integrated with optimized process parameters for a prepared heater element [doped PEDOT: PSS (poly-(3, 4 ethylenedioxythiophene): poly (styrene sulfonic acid))], a soft actuator (Ecoflex 00-50/ethanol) and overall packaging case [PDMS (polydimethylsiloxane)]. To study a potential application of the proposed smart skin, we analyze the fluid drag reduction in a texture controlled water flow unit. As a result, we obtained a reduction of approximately 14% in the skin drag friction coefficient during the actuation. We conclude that the proposed soft actuator device is a preferred option for a texture-controlled skin that reduces the skin drag friction coefficient.

Anti-reflection textured structures by wet etching and island lithography for surface-enhanced Raman spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Chao, Bo-Kai [Department of Materials Science and Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Cheng, Hsin-Hung [Department of Marine Engineering, Taipei College of Maritime Technology, Taipei 11174, Taiwan (China); Nien, Li-Wei; Chen, Miin-Jang [Department of Materials Science and Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Nagao, Tadaaki [Center for Materials Nanoarchitectonics, National Institute for Materials Science, Tsukuba, Ibaraki 305-0044 (Japan); Li, Jia-Han [Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Hsueh, Chun-Hway, E-mail: hsuehc@ntu.edu.tw [Department of Materials Science and Engineering, National Taiwan University, Taipei 10617, Taiwan (China)

2015-12-01

Graphical abstract: - Highlights: • We fabricated textured SERS substrate with a high surface area and low reflectance. • Large surface area of substrate contains more gold nanodroplets to absorb analytes. • Low reflectance of textured SERS substrate enabled multiple reflections of incident laser light. • We obtained strong SERS enhancement from nanopillar-on-pyramid SERS substrate. - Abstract: A high surface area and low reflection textured surface-enhanced Raman scattering (SERS) substrate with plasmonic gold nanodroplets fabricated by wet etching and island lithography was reported in the present study. Specifically, four textured substrates, planar, pyramid, nanopillar, and nanopillar-on-pyramid, were fabricated. The fabricated structures were simulated using the finite-difference time-domain method and the results agreed with the reflection and dark-field scattering measurements. Although the SERS signals varied in different measured regions because of the random nanostructure, the SERS substrates with nanopillar-on-pyramid structure always have the stronger enhancement factor than the SERS substrates with only pyramids or nanopillars. Based on the atomic force microscope and reflection measurements, the nanopillar-on-pyramid structure provided a large surface area and multiple reflections for SERS enhancement, which was about 3 orders of magnitude larger than that of the planar substrate. Our results can be applied to fabricate the inexpensive, large surface area, and high SERS enhancement substrates.

A signature dissimilarity measure for trabecular bone texture in knee radiographs

International Nuclear Information System (INIS)

Woloszynski, T.; Podsiadlo, P.; Stachowiak, G. W.; Kurzynski, M.

2010-01-01

Purpose: The purpose of this study is to develop a dissimilarity measure for the classification of trabecular bone (TB) texture in knee radiographs. Problems associated with the traditional extraction and selection of texture features and with the invariance to imaging conditions such as image size, anisotropy, noise, blur, exposure, magnification, and projection angle were addressed. Methods: In the method developed, called a signature dissimilarity measure (SDM), a sum of earth mover's distances calculated for roughness and orientation signatures is used to quantify dissimilarities between textures. Scale-space theory was used to ensure scale and rotation invariance. The effects of image size, anisotropy, noise, and blur on the SDM developed were studied using computer generated fractal texture images. The invariance of the measure to image exposure, magnification, and projection angle was studied using x-ray images of human tibia head. For the studies, Mann-Whitney tests with significance level of 0.01 were used. A comparison study between the performances of a SDM based classification system and other two systems in the classification of Brodatz textures and the detection of knee osteoarthritis (OA) were conducted. The other systems are based on weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM) and local binary patterns (LBP). Results: Results obtained indicate that the SDM developed is invariant to image exposure (2.5-30 mA s), magnification (x1.00-x1.35), noise associated with film graininess and quantum mottle ( 64x64 pixels). However, the measure is sensitive to changes in projection angle (>5 deg.), image anisotropy (>30 deg.), and blur generated by a regular film screen. For the classification of Brodatz textures, the SDM based system produced comparable results to the LBP system. For the detection of knee OA, the SDM based system achieved 78.8% classification accuracy and outperformed the WND

Stretchable surfaces with programmable 3D texture morphing for synthetic camouflaging skins

Science.gov (United States)

Pikul, J. H.; Li, S.; Bai, H.; Hanlon, R. T.; Cohen, I.; Shepherd, R. F.

2017-10-01

Technologies that use stretchable materials are increasingly important, yet we are unable to control how they stretch with much more sophistication than inflating balloons. Nature, however, demonstrates remarkable control of stretchable surfaces; for example, cephalopods can project hierarchical structures from their skin in milliseconds for a wide range of textural camouflage. Inspired by cephalopod muscular morphology, we developed synthetic tissue groupings that allowed programmable transformation of two-dimensional (2D) stretchable surfaces into target 3D shapes. The synthetic tissue groupings consisted of elastomeric membranes embedded with inextensible textile mesh that inflated to within 10% of their target shapes by using a simple fabrication method and modeling approach. These stretchable surfaces transform from flat sheets to 3D textures that imitate natural stone and plant shapes and camouflage into their background environments.

Tactile surface classification for limbed robots using a pressure sensitive robot skin

International Nuclear Information System (INIS)

Shill, Jacob J; Collins Jr, Emmanuel G; Coyle, Eric; Clark, Jonathan

2015-01-01

This paper describes an approach to terrain identification based on pressure images generated through direct surface contact using a robot skin constructed around a high-resolution pressure sensing array. Terrain signatures for classification are formulated from the magnitude frequency responses of the pressure images. The initial experimental results for statically obtained images show that the approach yields classification accuracies >98%. The methodology is extended to accommodate the dynamic pressure images anticipated when a robot is walking or running. Experiments with a one-legged hopping robot yield similar identification accuracies ≈99%. In addition, the accuracies are independent with respect to changing robot dynamics (i.e., when using different leg gaits). The paper further shows that the high-resolution capabilities of the sensor enables similarly textured surfaces to be distinguished. A correcting filter is developed to accommodate for failures or faults that inevitably occur within the sensing array with continued use. Experimental results show using the correcting filter can extend the effective operational lifespan of a high-resolution sensing array over 6x in the presence of sensor damage. The results presented suggest this methodology can be extended to autonomous field robots, providing a robot with crucial information about the environment that can be used to aid stable and efficient mobility over rough and varying terrains. (paper)

Comparison of models of automatic classification of textural patterns of mineral presents in Colombian coals

International Nuclear Information System (INIS)

Lopez Carvajal, Jaime; Branch Bedoya, John Willian

2005-01-01

The automatic classification of objects is a very interesting approach under several problem domains. This paper outlines some results obtained under different classification models to categorize textural patterns of minerals using real digital images. The data set used was characterized by a small size and noise presence. The implemented models were the Bayesian classifier, Neural Network (2-5-1), support vector machine, decision tree and 3-nearest neighbors. The results after applying crossed validation show that the Bayesian model (84%) proved better predictive capacity than the others, mainly due to its noise robustness behavior. The neuronal network (68%) and the SVM (67%) gave promising results, because they could be improved increasing the data amount used, while the decision tree (55%) and K-NN (54%) did not seem to be adequate for this problem, because of their sensibility to noise

Depth image enhancement using perceptual texture priors

Science.gov (United States)

Bang, Duhyeon; Shim, Hyunjung

2015-03-01

A depth camera is widely used in various applications because it provides a depth image of the scene in real time. However, due to the limited power consumption, the depth camera presents severe noises, incapable of providing the high quality 3D data. Although the smoothness prior is often employed to subside the depth noise, it discards the geometric details so to degrade the distance resolution and hinder achieving the realism in 3D contents. In this paper, we propose a perceptual-based depth image enhancement technique that automatically recovers the depth details of various textures, using a statistical framework inspired by human mechanism of perceiving surface details by texture priors. We construct the database composed of the high quality normals. Based on the recent studies in human visual perception (HVP), we select the pattern density as a primary feature to classify textures. Upon the classification results, we match and substitute the noisy input normals with high quality normals in the database. As a result, our method provides the high quality depth image preserving the surface details. We expect that our work is effective to enhance the details of depth image from 3D sensors and to provide a high-fidelity virtual reality experience.

Breast tissue classification in digital tomosynthesis images based on global gradient minimization and texture features

Science.gov (United States)

Qin, Xulei; Lu, Guolan; Sechopoulos, Ioannis; Fei, Baowei

2014-03-01

Digital breast tomosynthesis (DBT) is a pseudo-three-dimensional x-ray imaging modality proposed to decrease the effect of tissue superposition present in mammography, potentially resulting in an increase in clinical performance for the detection and diagnosis of breast cancer. Tissue classification in DBT images can be useful in risk assessment, computer-aided detection and radiation dosimetry, among other aspects. However, classifying breast tissue in DBT is a challenging problem because DBT images include complicated structures, image noise, and out-of-plane artifacts due to limited angular tomographic sampling. In this project, we propose an automatic method to classify fatty and glandular tissue in DBT images. First, the DBT images are pre-processed to enhance the tissue structures and to decrease image noise and artifacts. Second, a global smooth filter based on L0 gradient minimization is applied to eliminate detailed structures and enhance large-scale ones. Third, the similar structure regions are extracted and labeled by fuzzy C-means (FCM) classification. At the same time, the texture features are also calculated. Finally, each region is classified into different tissue types based on both intensity and texture features. The proposed method is validated using five patient DBT images using manual segmentation as the gold standard. The Dice scores and the confusion matrix are utilized to evaluate the classified results. The evaluation results demonstrated the feasibility of the proposed method for classifying breast glandular and fat tissue on DBT images.

COMPUTER GRAPHICS MEETS IMAGE FUSION: THE POWER OF TEXTURE BAKING TO SIMULTANEOUSLY VISUALISE 3D SURFACE FEATURES AND COLOUR

Directory of Open Access Journals (Sweden)

G. J. Verhoeven

2017-08-01

Full Text Available Since a few years, structure-from-motion and multi-view stereo pipelines have become omnipresent in the cultural heritage domain. The fact that such Image-Based Modelling (IBM approaches are capable of providing a photo-realistic texture along the threedimensional (3D digital surface geometry is often considered a unique selling point, certainly for those cases that aim for a visually pleasing result. However, this texture can very often also obscure the underlying geometrical details of the surface, making it very hard to assess the morphological features of the digitised artefact or scene. Instead of constantly switching between the textured and untextured version of the 3D surface model, this paper presents a new method to generate a morphology-enhanced colour texture for the 3D polymesh. The presented approach tries to overcome this switching between objects visualisations by fusing the original colour texture data with a specific depiction of the surface normals. Whether applied to the original 3D surface model or a lowresolution derivative, this newly generated texture does not solely convey the colours in a proper way but also enhances the smalland large-scale spatial and morphological features that are hard or impossible to perceive in the original textured model. In addition, the technique is very useful for low-end 3D viewers, since no additional memory and computing capacity are needed to convey relief details properly. Apart from simple visualisation purposes, the textured 3D models are now also better suited for on-surface interpretative mapping and the generation of line drawings.

Computer Graphics Meets Image Fusion: the Power of Texture Baking to Simultaneously Visualise 3d Surface Features and Colour

Science.gov (United States)

Verhoeven, G. J.

2017-08-01

Since a few years, structure-from-motion and multi-view stereo pipelines have become omnipresent in the cultural heritage domain. The fact that such Image-Based Modelling (IBM) approaches are capable of providing a photo-realistic texture along the threedimensional (3D) digital surface geometry is often considered a unique selling point, certainly for those cases that aim for a visually pleasing result. However, this texture can very often also obscure the underlying geometrical details of the surface, making it very hard to assess the morphological features of the digitised artefact or scene. Instead of constantly switching between the textured and untextured version of the 3D surface model, this paper presents a new method to generate a morphology-enhanced colour texture for the 3D polymesh. The presented approach tries to overcome this switching between objects visualisations by fusing the original colour texture data with a specific depiction of the surface normals. Whether applied to the original 3D surface model or a lowresolution derivative, this newly generated texture does not solely convey the colours in a proper way but also enhances the smalland large-scale spatial and morphological features that are hard or impossible to perceive in the original textured model. In addition, the technique is very useful for low-end 3D viewers, since no additional memory and computing capacity are needed to convey relief details properly. Apart from simple visualisation purposes, the textured 3D models are now also better suited for on-surface interpretative mapping and the generation of line drawings.

Effect of surface shear on cube texture formation in heavy cold-rolled Cu-45 at%Ni alloy substrates

DEFF Research Database (Denmark)

Tian, Hui; Suo, Hongli; Liang, Yaru

2015-01-01

Two types of Cu-45 at%Ni alloy thin tapes with and without surface shear were obtained by different heavy cold rolling processes. The deformation and recrystallization textures of the two tapes were thoroughly investigated by electron back scattering diffraction technique. The results showed...... that a shear texture mainly covered the surface of the heavy deformed tapes because of the fraction between the surface of rolling mills and the thin tapes when the rolling force strongly reduced at high strain, which significantly reduced the fraction of rolling texture on the surface of the Cu-45at %Ni alloy...

Touching Textured Surfaces: Cells in Somatosensory Cortex Respond Both to Finger Movement and to Surface Features

Science.gov (United States)

Darian-Smith, Ian; Sugitani, Michio; Heywood, John; Karita, Keishiro; Goodwin, Antony

1982-11-01

Single neurons in Brodmann's areas 3b and 1 of the macaque postcentral gyrus discharge when the monkey rubs the contralateral finger pads across a textured surface. Both the finger movement and the spatial pattern of the surface determine this discharge in each cell. The spatial features of the surface are represented unambiguously only in the responses of populations of these neurons, and not in the responses of the constituent cells.

Classification of Carotid Plaque Echogenicity by Combining Texture Features and Morphologic Characteristics.

Science.gov (United States)

Huang, Xiaowei; Zhang, Yanling; Qian, Ming; Meng, Long; Xiao, Yang; Niu, Lili; Zheng, Rongqin; Zheng, Hairong

2016-10-01

Anechoic carotid plaques on sonography have been used to predict future cardiovascular or cerebrovascular events. The purpose of this study was to investigate whether carotid plaque echogenicity could be assessed objectively by combining texture features extracted by MaZda software (Institute of Electronics, Technical University of Lodz, Lodz, Poland) and morphologic characteristics, which may provide a promising method for early prediction of acute cardiovascular disease. A total of 268 plaque images were collected from 136 volunteers and classified into 85 hyperechoic, 83 intermediate, and 100 anechoic plaques. About 300 texture features were extracted from histogram, absolute gradient, run-length matrix, gray-level co-occurrence matrix, autoregressive model, and wavelet transform algorithms by MaZda. The morphologic characteristics, including degree of stenosis, maximum plaque intima-media thickness, and maximum plaque length, were measured by B-mode sonography. Statistically significant features were selected by analysis of covariance. The most discriminative features were obtained from statistically significant features by linear discriminant analysis. The K-nearest neighbor classifier was used to classify plaque echogenicity based on statistically significant and most discriminative features. A total of 30 statistically significant features were selected among the plaques, and 2 most discriminative features were obtained from the statistically significant features. The classification accuracy rates for 3 types of plaques based on statistically significant and most discriminative features were 72.03% (κ= 0.571; P MaZda and morphologic characteristics.

Production of stable superhydrophilic surfaces on 316L steel by simultaneous laser texturing and SiO2 deposition

Science.gov (United States)

Rajab, Fatema H.; Liu, Zhu; Li, Lin

2018-01-01

Superhydrophilic surfaces with liquid contact angles of less than 5 ° have attracted much interest in practical applications including self-cleaning, cell manipulation, adhesion enhancement, anti-fogging, fluid flow control and evaporative cooling. Standard laser metal texturing method often result in unstable wetting characteristics, i.e. changing from super hydrophilic to hydrophobic in a few days or weeks. In this paper, a simple one step method is reported for fabricating a stable superhydrophilic metallic surface that lasted for at least 6 months. Here, 316L stainless steel substrates were textured using a nanosecond laser with in-situ SiO2 deposition. Morphology and chemistry of laser-textured surfaces were characterised using SEM, XRD, XPS and an optical 3D profiler. Static wettability analysis was carried out over a period of 6 months after the laser treatment. The effect of surface roughness on wettability was also studied. Results showed that the wettability of the textured surfaces could be controlled by changing the scanning speed of laser beam and number of passes. The main reason for the realisation of the stable superhydrophilic surface is the combination of the melted glass particles mainly Si and O with that of stainless steel in the micro-textured patterns. This study presents a useful method

Predicting the effect of surface texture on the qualitative form of prehension.

Directory of Open Access Journals (Sweden)

Ian John Flatters

Full Text Available Reach-to-grasp movements change quantitatively in a lawful (i.e. predictable manner with changes in object properties. We explored whether altering object texture would produce qualitative changes in the form of the precontact movement patterns. Twelve participants reached to lift objects from a tabletop. Nine objects were produced, each with one of three grip surface textures (high-friction, medium-friction and low-friction and one of three widths (50 mm, 70 mm and 90 mm. Each object was placed at three distances (100 mm, 300 mm and 500 mm, representing a total of 27 trial conditions. We observed two distinct movement patterns across all trials--participants either: (i brought their arm to a stop, secured the object and lifted it from the tabletop; or (ii grasped the object 'on-the-fly', so it was secured in the hand while the arm was moving. A majority of grasps were on-the-fly when the texture was high-friction and none when the object was low-friction, with medium-friction producing an intermediate proportion. Previous research has shown that the probability of on-the-fly behaviour is a function of grasp surface accuracy constraints. A finger friction rig was used to calculate the coefficients of friction for the objects and these calculations showed that the area available for a stable grasp (the 'functional grasp surface size' increased with surface friction coefficient. Thus, knowledge of functional grasp surface size is required to predict the probability of observing a given qualitative form of grasping in human prehensile behaviour.

UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis

Directory of Open Access Journals (Sweden)

Quanlong Feng

2015-01-01

Full Text Available Unmanned aerial vehicle (UAV remote sensing has great potential for vegetation mapping in complex urban landscapes due to the ultra-high resolution imagery acquired at low altitudes. Because of payload capacity restrictions, off-the-shelf digital cameras are widely used on medium and small sized UAVs. The limitation of low spectral resolution in digital cameras for vegetation mapping can be reduced by incorporating texture features and robust classifiers. Random Forest has been widely used in satellite remote sensing applications, but its usage in UAV image classification has not been well documented. The objectives of this paper were to propose a hybrid method using Random Forest and texture analysis to accurately differentiate land covers of urban vegetated areas, and analyze how classification accuracy changes with texture window size. Six least correlated second-order texture measures were calculated at nine different window sizes and added to original Red-Green-Blue (RGB images as ancillary data. A Random Forest classifier consisting of 200 decision trees was used for classification in the spectral-textural feature space. Results indicated the following: (1 Random Forest outperformed traditional Maximum Likelihood classifier and showed similar performance to object-based image analysis in urban vegetation classification; (2 the inclusion of texture features improved classification accuracy significantly; (3 classification accuracy followed an inverted U relationship with texture window size. The results demonstrate that UAV provides an efficient and ideal platform for urban vegetation mapping. The hybrid method proposed in this paper shows good performance in differentiating urban vegetation mapping. The drawbacks of off-the-shelf digital cameras can be reduced by adopting Random Forest and texture analysis at the same time.

Development of measurement standards for verifying functional performance of surface texture measuring instruments

Energy Technology Data Exchange (ETDEWEB)

Fujii, A [Life and Industrial Product Development Department Olympus Corporation, 2951 Ishikawa-machi, Hachiouji-shi, Tokyo (Japan); Suzuki, H [Industrial Marketing and Planning Department Olympus Corporation, Shinjyuku Monolith, 3-1 Nishi-Shinjyuku 2-chome, Tokyo (Japan); Yanagi, K, E-mail: a_fujii@ot.olympus.co.jp [Department of Mechanical Engineering, Nagaoka University of Technology, 1603-1 Kamitomioka-machi, Nagaoka-shi, Niigata (Japan)

2011-08-19

A new measurement standard is proposed for verifying overall functional performance of surface texture measuring instruments. Its surface is composed of sinusoidal surface waveforms of chirp signals along horizontal cross sections of the material measure. One of the notable features is that the amplitude of each cycle in the chirp signal form is geometrically modulated so that the maximum slope is kept constant. The maximum slope of the chirp-like signal is gradually decreased according to movement in the lateral direction. We fabricated the measurement standard by FIB processing, and it was calibrated by AFM. We tried to evaluate the functional performance of Laser Scanning Microscope by this standard in terms of amplitude response with varying slope angles. As a result, it was concluded that the proposed standard can easily evaluate the performance of surface texture measuring instruments.

Optical and electrical properties of porous silicon layer formed on the textured surface by electrochemical etching

Science.gov (United States)

Weiying, Ou; Lei, Zhao; Hongwei, Diao; Jun, Zhang; Wenjing, Wang

2011-05-01

Porous silicon (PS) layers were formed on textured crystalline silicon by electrochemical etching in HF-based electrolyte. Optical and electrical properties of the TMAH textured surfaces with PS formation are studied. Moreover, the influences of the initial structures and the anodizing time on the optical and electrical properties of the surfaces after PS formation are investigated. The results show that the TMAH textured surfaces with PS formation present a dramatic decrease in reflectance. The longer the anodizing time is, the lower the reflectance. Moreover, an initial surface with bigger pyramids achieved lower reflectance in a short wavelength range. A minimum reflectance of 3.86% at 460 nm is achieved for a short anodizing time of 2 min. Furthermore, the reflectance spectrum of the sample, which was etched in 3 vol.% TMAH for 25 min and then anodized for 20 min, is extremely flat and lies between 3.67% and 6.15% in the wavelength range from 400 to 1040 nm. In addition, for a short anodizing time, a slight increase in the effective carrier lifetime is observed. Our results indicate that PS layers formed on a TMAH textured surface for a short anodization treatment can be used as both broadband antireflection coatings and passivation layers for the application in solar cells.

Optical and electrical properties of porous silicon layer formed on the textured surface by electrochemical etching

Energy Technology Data Exchange (ETDEWEB)

Ou Weiying; Zhao Lei; Diao Hongwei; Zhang Jun; Wang Wenjing, E-mail: wjwangwj@126.com [Key Laboratory of Solar Thermal Energy and Photovoltaic System, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190 (China)

2011-05-15

Porous silicon (PS) layers were formed on textured crystalline silicon by electrochemical etching in HF-based electrolyte. Optical and electrical properties of the TMAH textured surfaces with PS formation are studied. Moreover, the influences of the initial structures and the anodizing time on the optical and electrical properties of the surfaces after PS formation are investigated. The results show that the TMAH textured surfaces with PS formation present a dramatic decrease in reflectance. The longer the anodizing time is, the lower the reflectance. Moreover, an initial surface with bigger pyramids achieved lower reflectance in a short wavelength range. A minimum reflectance of 3.86% at 460 nm is achieved for a short anodizing time of 2 min. Furthermore, the reflectance spectrum of the sample, which was etched in 3 vol.% TMAH for 25 min and then anodized for 20 min, is extremely flat and lies between 3.67% and 6.15% in the wavelength range from 400 to 1040 nm. In addition, for a short anodizing time, a slight increase in the effective carrier lifetime is observed. Our results indicate that PS layers formed on a TMAH textured surface for a short anodization treatment can be used as both broadband antireflection coatings and passivation layers for the application in solar cells. (semiconductor technology)

A signature dissimilarity measure for trabecular bone texture in knee radiographs

Energy Technology Data Exchange (ETDEWEB)

Woloszynski, T.; Podsiadlo, P.; Stachowiak, G. W.; Kurzynski, M. [Tribology Laboratory, School of Mechanical Engineering, University of Western Australia, Crawley, Western Australia 6009 (Australia); Chair of Computer Systems and Networks, Faculty of Electronics, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw (Poland)

2010-05-15

Purpose: The purpose of this study is to develop a dissimilarity measure for the classification of trabecular bone (TB) texture in knee radiographs. Problems associated with the traditional extraction and selection of texture features and with the invariance to imaging conditions such as image size, anisotropy, noise, blur, exposure, magnification, and projection angle were addressed. Methods: In the method developed, called a signature dissimilarity measure (SDM), a sum of earth mover's distances calculated for roughness and orientation signatures is used to quantify dissimilarities between textures. Scale-space theory was used to ensure scale and rotation invariance. The effects of image size, anisotropy, noise, and blur on the SDM developed were studied using computer generated fractal texture images. The invariance of the measure to image exposure, magnification, and projection angle was studied using x-ray images of human tibia head. For the studies, Mann-Whitney tests with significance level of 0.01 were used. A comparison study between the performances of a SDM based classification system and other two systems in the classification of Brodatz textures and the detection of knee osteoarthritis (OA) were conducted. The other systems are based on weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM) and local binary patterns (LBP). Results: Results obtained indicate that the SDM developed is invariant to image exposure (2.5-30 mA s), magnification (x1.00-x1.35), noise associated with film graininess and quantum mottle (<25%), blur generated by a sharp film screen, and image size (>64x64 pixels). However, the measure is sensitive to changes in projection angle (>5 deg.), image anisotropy (>30 deg.), and blur generated by a regular film screen. For the classification of Brodatz textures, the SDM based system produced comparable results to the LBP system. For the detection of knee OA, the SDM based system

Effect of machining parameters on surface textures in EDM of Fe-Mn-Al alloy

International Nuclear Information System (INIS)

Guu, Y.H.; Hou, Max Ti-Kuang

2007-01-01

In this work, the surface characteristics caused by EDM were analyzed by means of the atomic force microscopy (AFM) technique. An empirical model of Fe-Mn-Al alloy was proposed based on the experimental data. A qualitative energy dispersive spectroscopic analyzer was used to measure the chemical composition of the specimen. Surface hardness was determined with a microhardness tester. Experimental results indicate that the EDM process causes a ridged surface and induces machining damage in the surface layer, and increases the surface roughness. The depth of micro-cracks, micro-voids and machined damage increase with an increase in the amount of pulsed current and pulse-on duration. The effect of the magnitude of the pulse-on duration on the surface texture of the specimen is more significant than the pulsed current. Furthermore, the AFM method reveals the 3D surface textures of the EDM specimen with a nanometer scale

Influence of Femtosecond Laser Parameters and Environment on Surface Texture Characteristics of Metals and Non-Metals - State of the Art

Science.gov (United States)

Bharatish, A.; Soundarapandian, S.

2018-04-01

Enhancing the surface functionality by ultrashort pulsed laser texturing has received the considerable attention from researchers in the past few decades. Femtosecond lasers are widely adopted since it provides high repeatability and reproducibility by minimizing the heat affected zone (HAZ) and other collateral damages to a great extent. The present paper reports some recent studies being made worldwide on femtosecond laser surface texturing of metals, ceramics, polymers, semiconductors, thinfilms and advanced nanocomposites. It presents the state of the art knowledge in femtosecond laser surface texturing and the potential of this technology to improve properties in terms of biological, tribological and wetting performance. Since the texture quality and functionality are enhanced by the proper selection of appropriate laser parameters and ambient conditions for individual application, reporting the influence of laser parameters on surface texture characteristics assume utmost importance.

HOS cell adhesion on Ti6Al4V surfaces texturized by laser engraving

Science.gov (United States)

Sandoval Amador, A.; Carreño Garcia, H.; Escobar Rivero, P.; Peña Ballesteros, D. Y.; Estupiñán Duran, H. A.

2016-02-01

The cell adhesion of the implant is determinate by the chemical composition, topography, wettability, surface energy and biocompatibility of the biomaterial. In this work the interaction between human osteosarcoma HOS cells and textured Ti6Al4V surfaces were evaluated. Ti6Al4V surfaces were textured using a CO2 laser in order to obtain circular spots on the surfaces. Test surfaces were uncoated (C1) used as a control surface, and surfaces with points obtained by laser engraving, with 1mm spacing (C2) and 0.5mm (C3). The HOS cells were cultured in RPMI-1640 medium with 10% fetal bovine serum and 1% antibiotics. No cells toxicity after one month incubation time occurred. The increased cell adhesion and cell spreading was observed after 1, 3 and 5 days without significant differences between the sample surfaces (C2 and C3) and control (uncoated) at the end of the experiment.

HOS cell adhesion on Ti6Al4V surfaces texturized by laser engraving

International Nuclear Information System (INIS)

Sandoval Amador, A; Carreño Garcia, H; Escobar Rivero, P; Peña Ballesteros, D Y; Estupiñán Duran, H A

2016-01-01

The cell adhesion of the implant is determinate by the chemical composition, topography, wettability, surface energy and biocompatibility of the biomaterial. In this work the interaction between human osteosarcoma HOS cells and textured Ti 6 Al 4 V surfaces were evaluated. Ti 6 Al 4 V surfaces were textured using a CO 2 laser in order to obtain circular spots on the surfaces. Test surfaces were uncoated (C1) used as a control surface, and surfaces with points obtained by laser engraving, with 1mm spacing (C2) and 0.5mm (C3). The HOS cells were cultured in RPMI-1640 medium with 10% fetal bovine serum and 1% antibiotics. No cells toxicity after one month incubation time occurred. The increased cell adhesion and cell spreading was observed after 1, 3 and 5 days without significant differences between the sample surfaces (C2 and C3) and control (uncoated) at the end of the experiment. (paper)

Tribological Behavior of Oil-Lubricated Laser Textured Steel Surfaces in Conformal Flat and Non-Conformal Contacts

Energy Technology Data Exchange (ETDEWEB)

Kovalchenko, A. M. [Inst. for Problems of Materials Science, Dept. 7, 3 Krzhizhanovsky Street, Kyiv 03142, UA (Corresponding author), e-mail: andrii.kovalchenko@gatech.edu; Erdemir, A. [Argonne National Lab., Energy Systems Division, 9700 South Cass Avenue, Argonne, IL 60439 US; Ajayi, O. O. [Argonne National Lab., Energy Systems Division, 9700 South Cass Avenue, Argonne, IL 60439 US; Etsion, I. [Technion-Israel Inst. of Technology, Dept. of Mechanical Engineering, Haifa 32000, IL

2017-01-30

Changing the surface texture of sliding surfaces is an effective way to manipulate friction and wear of lubricated surfaces. Having realized its potential, we have done very extensive studies on the effects of laser surface texturing (LST, which involves the creation of an array of microdimples on a surface) on friction and wear behavior of oil-lubricated steel surfaces in the early 2000s. In this paper, we reviewed some of our research accomplishments and assessed future directions of the laser texturing field in many diverse industrial applications. Our studies specifically addressed the impact of laser texturing on friction and wear of both the flat conformal and initial non-conformal point contact configurations using a pin-on-disk test rig under fully-flooded synthetic oil lubricants with different viscosities. Electrical resistance measurement between pin and LST disks was also used to determine the operating lubrication regimes in relation to friction. In conformal contact, we confirmed that LST could significantly expand the operating conditions for hydrodynamic lubrication to significantly much higher loads and slower speeds. In particular, with LST and higher viscosity oils, the low-friction full hydrodynamic regime was shifted to the far left in the Stribeck diagram. Overall, the beneficial effects of laser surface texturing were more pronounced at higher speeds and loads and with higher viscosity oil. LST was also observed to reduce the magnitude of friction coefficients in the boundary regime. For the non-conformal contact configuration, we determined that LST would produce more abrasive wear on the rubbing counterface compared to the untreated surfaces due to a reduction in lubricant fluid film thickness, as well as the highly uneven and rough nature of the textured surfaces. However, this higher initial wear rate has led to faster generation of a conformal contact, and thus transition from the high-friction boundary to lower friction mixed

Application of texture analysis method for classification of benign and malignant thyroid nodules in ultrasound images.

Science.gov (United States)

Abbasian Ardakani, Ali; Gharbali, Akbar; Mohammadi, Afshin

2015-01-01

The aim of this study was to evaluate computer aided diagnosis (CAD) system with texture analysis (TA) to improve radiologists' accuracy in identification of thyroid nodules as malignant or benign. A total of 70 cases (26 benign and 44 malignant) were analyzed in this study. We extracted up to 270 statistical texture features as a descriptor for each selected region of interests (ROIs) in three normalization schemes (default, 3s and 1%-99%). Then features by the lowest probability of classification error and average correlation coefficients (POE+ACC), and Fisher coefficient (Fisher) eliminated to 10 best and most effective features. These features were analyzed under standard and nonstandard states. For TA of the thyroid nodules, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA) were applied. First Nearest-Neighbour (1-NN) classifier was performed for the features resulting from PCA and LDA. NDA features were classified by artificial neural network (A-NN). Receiver operating characteristic (ROC) curve analysis was used for examining the performance of TA methods. The best results were driven in 1-99% normalization with features extracted by POE+ACC algorithm and analyzed by NDA with the area under the ROC curve ( Az) of 0.9722 which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Our results indicate that TA is a reliable method, can provide useful information help radiologist in detection and classification of benign and malignant thyroid nodules.

A neural network detection model of spilled oil based on the texture analysis of SAR image

Science.gov (United States)

An, Jubai; Zhu, Lisong

2006-01-01

A Radial Basis Function Neural Network (RBFNN) Model is investigated for the detection of spilled oil based on the texture analysis of SAR imagery. In this paper, to take the advantage of the abundant texture information of SAR imagery, the texture features are extracted by both wavelet transform and the Gray Level Co-occurrence matrix. The RBFNN Model is fed with a vector of these texture features. The RBFNN Model is trained and tested by the sample data set of the feature vectors. Finally, a SAR image is classified by this model. The classification results of a spilled oil SAR image show that the classification accuracy for oil spill is 86.2 by the RBFNN Model using both wavelet texture and gray texture, while the classification accuracy for oil spill is 78.0 by same RBFNN Model using only wavelet texture as the input of this RBFNN model. The model using both wavelet transform and the Gray Level Co-occurrence matrix is more effective than that only using wavelet texture. Furthermore, it keeps the complicated proximity and has a good performance of classification.

SAR Image Classification Based on Its Texture Features

Institute of Scientific and Technical Information of China (English)

LI Pingxiang; FANG Shenghui

2003-01-01

SAR images not only have the characteristics of all-ay, all-eather, but also provide object information which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The authors conducted the experiments of texture statistics analysis on SAR image features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpretation.

Nanocrystalline nickel films with lotus leaf texture for superhydrophobic and low friction surfaces

Science.gov (United States)

Shafiei, Mehdi; Alpas, Ahmet T.

2009-11-01

Nanostructured Ni films with high hardness, high hydrophobicity and low coefficient of friction (COF) were fabricated. The surface texture of lotus leaf was replicated using a cellulose acetate film, on which a nanocrystalline (NC) Ni coating with a grain size of 30 ± 4 nm was electrodeposited to obtain a self-sustaining film with a hardness of 4.42 GPa. The surface texture of the NC Ni obtained in this way featured a high density (4 × 10 3 mm -2) of conical protuberances with an average height of 10.0 ± 2.0 μm and a tip radius of 2.5 ± 0.5 μm. This structure increased the water repellency and reduced the COF, compared to smooth NC Ni surfaces. The application of a short-duration (120 s) electrodeposition process that deposited "Ni crowns" with a larger radius of 6.0 ± 0.5 μm on the protuberances, followed by a perfluoropolyether (PFPE) solution treatment succeeded in producing a surface texture consisting of nanotextured protuberances that resulted in a very high water contact angle of 156°, comparable to that of the superhydrophobic lotus leaf. Additionally, the microscale protuberances eliminated the initial high COF peaks observed when smooth NC Ni films were tested, and the PFPE treatment resulted in a 60% reduction in the steady-state COFs.

Wetting and other physical characteristics of polycarbonate surface textured using laser ablation

Energy Technology Data Exchange (ETDEWEB)

Yilbas, B.S., E-mail: bsyilbas@kfupm.edu.sa [ME Department, King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia); Khaled, M. [CHEM Department, King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia); Abu-Dheir, N.; Al-Aqeeli, N.; Said, S.A.M. [ME Department, King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia); Ahmed, A.O.M. [CHEM Department, King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia); Varanasi, K.K.; Toumi, Y.K. [Mechanical Engineering, Massachusetts Institute of Technology, Boston (United States)

2014-11-30

Highlights: • Laser causes micro/nano size pores and shallow fine-size cavities. • Crystallinity at surface is 18% after laser treatment increasing hydrophobicity. • Surface hydrophobicity improves after laser treatment. • Microhardness increases twofold after laser treatment process. • Residual stress is compressive and scratch hardness is 110 ± 11 MPa. • Optical transmittance reduces by 15% after laser treatment. - Abstract: Surface texturing of polycarbonate glass is carried out for improved hydrophobicity via controlled laser ablation at the surface. Optical and physical characteristics of the laser treated layer are examined using analytical tools including optical, atomic force, and scanning electron microscopes, Fourier transform infrared spectroscopy, and X-ray diffraction. Contact angle measurements are carried out to assess the hydrophobicity of the laser treated surface. Residual stress in the laser ablated layer is determined using the curvature method, and microhardnes and scratch resistance are analyzed using a micro-tribometer. Findings reveal that textured surfaces compose of micro/nano pores with fine cavities and increase the contact angle to hydrophobicity such a way that contact angles in the range of 120° are resulted. Crystallization of the laser treated surface reduces the optical transmittance by 15%, contributes to residual stress formation, and enhances the microhardness by twice the value of untreated polycarbonate surface. In addition, laser treatment improves surface scratch resistance by 40%.

Some Numerical Characteristics of Image Texture

Directory of Open Access Journals (Sweden)

O. Samarina

2012-05-01

Full Text Available Texture classification is one of the basic images processing tasks. In this paper we present some numerical characteristics to the images analysis and processing. It can be used at the solving of images classification problems, their recognition, problems of remote sounding, biomedical images analysis, geological researches.

Description of textures by a structural analysis.

Science.gov (United States)

Tomita, F; Shirai, Y; Tsuji, S

1982-02-01

A structural analysis system for describing natural textures is introduced. The analyzer automatically extracts the texture elements in an input image, measures their properties, classifies them into some distinctive classes (one ``ground'' class and some ``figure'' classes), and computes the distributions of the gray level, the shape, and the placement of the texture elements in each class. These descriptions are used for classification of texture images. An analysis-by-synthesis method for evaluating texture analyzers is also presented. We propose a synthesizer which generates a texture image based on the descriptions. By comparing the reconstructed image with the original one, we can see what information is preserved and what is lost in the descriptions.

Femtosecond laser surface texturing of titanium as a method to reduce the adhesion of Staphylococcus aureus and biofilm formation

Energy Technology Data Exchange (ETDEWEB)

Cunha, Alexandre [Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Bordeaux University, Institute of Chemistry & Biology of Membranes & Nanoobjects (CBMN UMR 5248, CNRS), European Institute of Chemistry and Biology, 2 Rue Robert Escarpit, 33607 Pessac (France); Elie, Anne-Marie [Bordeaux University, CBMN UMR 5248, CNRS, Bordeaux Science Agro, 1 Rue du G. de Gaulle, 33170 Gradignan (France); Plawinski, Laurent [Bordeaux University, Institute of Chemistry & Biology of Membranes & Nanoobjects (CBMN UMR 5248, CNRS), European Institute of Chemistry and Biology, 2 Rue Robert Escarpit, 33607 Pessac (France); Serro, Ana Paula [Instituto Superior Técnico, Universidade de Lisboa, CQE-Centro de Química Estrutural, Av. Rovisco Pais 1, 1049-001 Lisbon (Portugal); Botelho do Rego, Ana Maria [Instituto Superior Técnico, Universidade de Lisboa, CQFM-Centro de Química-Física Molecular and Institute of Nanoscience and Nanotechnology - IN, Av. Rovisco Pais 1, 1049-001 Lisbon (Portugal); Almeida, Amélia [Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Urdaci, Maria C. [Bordeaux University, CBMN UMR 5248, CNRS, Bordeaux Science Agro, 1 Rue du G. de Gaulle, 33170 Gradignan (France); Durrieu, Marie-Christine [Bordeaux University, Institute of Chemistry & Biology of Membranes & Nanoobjects (CBMN UMR 5248, CNRS), European Institute of Chemistry and Biology, 2 Rue Robert Escarpit, 33607 Pessac (France); Vilar, Rui, E-mail: rui.vilar@tecnico.ulisboa.pt [Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)

2016-01-01

Graphical abstract: - Highlights: • The short-term adhesion of Staphylococcus aureus onto femtosecond laser textured surfaces of titanium was investigated. • The laser textured surfaces consist of laser-induced periodic surface structures (LIPSS) and nanopillars. • The laser treatment enhances the hydrophilicity and the surface free energy of the material. • The laser treatment reduces significantly the adhesion of S. aureus and biofilm formation. • Femtosecond laser surface texturing of titanium is a simple and promising method for endowing dental and orthopedic implants with antibacterial properties. - Abstract: The aim of the present work was to investigate the possibility of using femtosecond laser surface texturing as a method to reduce the colonization of Grade 2 Titanium alloy surfaces by Staphylococcus aureus and the subsequent formation of biofilm. The laser treatments were carried out with a Yb:KYW chirped-pulse-regenerative amplification laser system with a central wavelength of 1030 nm and a pulse duration of 500 fs. Two types of surface textures, consisting of laser-induced periodic surface structures (LIPSS) and nanopillars, were produced. The topography, chemical composition and phase constitution of these surfaces were investigated by atomic force microscopy, scanning electron microscopy, X-ray photoelectron spectroscopy, micro-Raman spectroscopy, and X-ray diffraction. Surface wettability was assessed by the sessile drop method using water and diiodomethane as testing liquids. The response of S. aureus put into contact with the laser treated surfaces in controlled conditions was investigated by epifluorescence microscopy and scanning electron microscopy 48 h after cell seeding. The results achieved show that the laser treatment reduces significantly the bacterial adhesion to the surface as well as biofilm formation as compared to a reference polished surfaces and suggest that femtosecond laser texturing is a simple and promising method

The effect of texture unit shape on silicon surface on the absorption properties

Energy Technology Data Exchange (ETDEWEB)

Hua, Xiao-She; Zhang, Yi-Jie; Wang, Hao-Wei [Institute of Ecological and Environmental Materials, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)

2010-02-15

Improving the utilization ratio of sunlight is a key factor for the development of solar cell. In this work, different structures including triangular pyramid, rectangular pyramid, hexangular pyramid and cone structure are established to investigate the influences of many factors, like geometrical shape, density and the top angle of the texture unit on silicon front surface to sunlight absorption. Ray-tracing technology is used for simulation. The simulation results indicate that the triangular pyramid texture on silicon front surface performs the best, and its total absorption rate is more than 90% for the light with wavelength between 640 and 1080 nm when the top angle of pyramid is less than 100 . (author)

Non-Uniform Laser Surface Texturing of an Un-Tapered Square Pad for Tribological Applications

Directory of Open Access Journals (Sweden)

Antonio Ancona

2017-10-01

Full Text Available Femtosecond laser surface micro-texturing has emerged as a promising technology to enhance the tribological properties of different kinds of electromechanical devices. In this research paper, we have exploited the intrinsic flexibility and micrometric accuracy of femtosecond laser ablation to realize complex micro-structural modifications on the surface of a laboratory prototype of a steel thrust bearing (un-tapered pad. The Bruggeman Texture Hydrodynamics theory (BTH is employed for the design of the anisotropic and non-uniform texture maximizing the thrust load of the pad prototype. The preliminary experimental results, reported in this work, show that the non-uniform micro-texture largely affects the friction characteristics of the contact. In particular, in agreement with the BTH predictions, the tribo-system shows friction properties that are strongly sensitive to the direction of the sliding speed, as a consequence of the micro-fluid dynamics which are designed to occur only in a specific sliding direction. We suggest that the joint action of virtual prototyping (BTH lubrication theory and ultrafast laser micro-prototyping can lead to unconventional and impressive results in terms of enhanced or tailored contact mechanics properties of the generic lubricated tribopair.

Advanced measurement and analysis of surface textures produced by micro-machining processes

International Nuclear Information System (INIS)

Bordatchev, Evgueni V; Hafiz, Abdullah M K

2014-01-01

Surface texture of a part or a product has significant effects on its functionality, physical-mechanical properties and visual appearance. In particular for miniature products, the implication of surface quality becomes critical owing to the presence of geometrical features with micro/nano-scale dimensions. Qualitative and quantitative assessments of surface texture are carried out predominantly by profile parameters, which are often insufficient to address the contribution of constituent spatial components with varied amplitudes and wavelengths. In this context, this article presents a novel approach for advanced measurement and analysis of profile average roughness (R a ) and its spatial distribution at different wavelength intervals. The applicability of the proposed approach was verified for three different surface topographies prepared by grinding, laser micro-polishing and micro-milling processes. From the measurement and analysis results, R a (λ) spatial distribution was found to be an effective measure of revealing the contributions of various spatial components within specific wavelength intervals towards formation of the entire surface profile. In addition, the approach was extended to the measurement and analysis of areal average roughness S a (λ) spatial distribution within different wavelength intervals. Besides, the proposed method was demonstrated to be a useful technique in developing a functional correlation between a manufacturing process and its corresponding surface profile. (paper)

An international comparison of surface texture parameters quantification on polymer artefacts using optical instruments

DEFF Research Database (Denmark)

Tosello, Guido; Haitjema, H.; Leach, R.K.

2016-01-01

An international comparison of optical instruments measuring polymer surfaces with arithmetic mean height values in the sub-micrometre range has been carried out. The comparison involved sixteen optical surface texture instruments (focus variation instruments, confocal microscopes and coherent...

Cold Gas-Sprayed Deposition of Metallic Coatings onto Ceramic Substrates Using Laser Surface Texturing Pre-treatment

Science.gov (United States)

Kromer, R.; Danlos, Y.; Costil, S.

2018-04-01

Cold spraying enables a variety of metals dense coatings onto metal surfaces. Supersonic gas jet accelerates particles which undergo with the substrate plastic deformation. Different bonding mechanisms can be created depending on the materials. The particle-substrate contact time, contact temperature and contact area upon impact are the parameters influencing physicochemical and mechanical bonds. The resultant bonding arose from plastic deformation of the particle and substrate and temperature increasing at the interface. The objective was to create specific topography to enable metallic particle adhesion onto ceramic substrates. Ceramic did not demonstrate deformation during the impact which minimized the intimate bonds. Laser surface texturing was hence used as prior surface treatment to create specific topography and to enable mechanical anchoring. Particle compressive states were necessary to build up coating. The coating deposition efficiency and adhesion strength were evaluated. Textured surface is required to obtain strong adhesion of metallic coatings onto ceramic substrates. Consequently, cold spray coating parameters depend on the target material and a methodology was established with particle parameters (diameters, velocities, temperatures) and particle/substrate properties to adapt the surface topography. Laser surface texturing is a promising tool to increase the cold spraying applications.

Electromechanical performance of an ionic polymer–metal composite actuator with hierarchical surface texture

International Nuclear Information System (INIS)

He, Qingsong; Yu, Min; Zhang, Xiaoqing; Dai, Zhendong

2013-01-01

Two stainless steel templates were fabricated using electric-spark machining, and a hierarchical surface texture of ionic polymer was produced using both polishing and replication methods, which produced microscale and nanoscale groove-shaped microstructures at the surface of the polymer. The surface morphology of the Nafion membrane and metal electrode were observed using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). SEM and EDS line-scan analysis indicated that the interfacial surface area was considerably increased and an excellent metal electrode was obtained with the production of a hierarchical surface texture. The displacement, blocking force, and electric current were measured using home-built apparatus. The results revealed that the combined polishing and replication method significantly improved the electromechanical performance of the ionic polymer–metal composite (IPMC). Compared with sandblasted Nafion-based IPMC, the blocking force, displacement, and electric current of the replicated Nafion-based IPMC were 4.39, 2.35, and 1.87 times higher, respectively. The IPMC fabricated in this work exhibited a competitive blocking force compared with recently reported actuators. (paper)

Idiopathic interstitial pneumonias and emphysema: detection and classification using a texture-discriminative approach

Science.gov (United States)

Fetita, C.; Chang-Chien, K. C.; Brillet, P. Y.; Pr"teux, F.; Chang, R. F.

2012-03-01

Our study aims at developing a computer-aided diagnosis (CAD) system for fully automatic detection and classification of pathological lung parenchyma patterns in idiopathic interstitial pneumonias (IIP) and emphysema using multi-detector computed tomography (MDCT). The proposed CAD system is based on three-dimensional (3-D) mathematical morphology, texture and fuzzy logic analysis, and can be divided into four stages: (1) a multi-resolution decomposition scheme based on a 3-D morphological filter was exploited to discriminate the lung region patterns at different analysis scales. (2) An additional spatial lung partitioning based on the lung tissue texture was introduced to reinforce the spatial separation between patterns extracted at the same resolution level in the decomposition pyramid. Then, (3) a hierarchic tree structure was exploited to describe the relationship between patterns at different resolution levels, and for each pattern, six fuzzy membership functions were established for assigning a probability of association with a normal tissue or a pathological target. Finally, (4) a decision step exploiting the fuzzy-logic assignments selects the target class of each lung pattern among the following categories: normal (N), emphysema (EM), fibrosis/honeycombing (FHC), and ground glass (GDG). According to a preliminary evaluation on an extended database, the proposed method can overcome the drawbacks of a previously developed approach and achieve higher sensitivity and specificity.

Use of digital image analysis combined with fractal theory to determine particle morphology and surface texture of quartz sands

Directory of Open Access Journals (Sweden)

Georgia S. Araujo

2017-12-01

Full Text Available The particle morphology and surface texture play a major role in influencing mechanical and hydraulic behaviors of sandy soils. This paper presents the use of digital image analysis combined with fractal theory as a tool to quantify the particle morphology and surface texture of two types of quartz sands widely used in the region of Vitória, Espírito Santo, southeast of Brazil. The two investigated sands are sampled from different locations. The purpose of this paper is to present a simple, straightforward, reliable and reproducible methodology that can identify representative sandy soil texture parameters. The test results of the soil samples of the two sands separated by sieving into six size fractions are presented and discussed. The main advantages of the adopted methodology are its simplicity, reliability of the results, and relatively low cost. The results show that sands from the coastal spit (BS have a greater degree of roundness and a smoother surface texture than river sands (RS. The values obtained in the test are statistically analyzed, and again it is confirmed that the BS sand has a slightly greater degree of sphericity than that of the RS sand. Moreover, the RS sand with rough surface texture has larger specific surface area values than the similar BS sand, which agree with the obtained roughness fractal dimensions. The consistent experimental results demonstrate that image analysis combined with fractal theory is an accurate and efficient method to quantify the differences in particle morphology and surface texture of quartz sands.

Classification of JERS-1 Image Mosaic of Central Africa Using A Supervised Multiscale Classifier of Texture Features

Science.gov (United States)

Saatchi, Sassan; DeGrandi, Franco; Simard, Marc; Podest, Erika

1999-01-01

In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.

Cloud and surface textural features in polar regions

Science.gov (United States)

Welch, Ronald M.; Kuo, Kwo-Sen; Sengupta, Sailes K.

1990-01-01

The study examines the textural signatures of clouds, ice-covered mountains, solid and broken sea ice and floes, and open water. The textural features are computed from sum and difference histogram and gray-level difference vector statistics defined at various pixel displacement distances derived from Landsat multispectral scanner data. Polar cloudiness, snow-covered mountainous regions, solid sea ice, glaciers, and open water have distinguishable texture features. This suggests that textural measures can be successfully applied to the detection of clouds over snow-covered mountains, an ability of considerable importance for the modeling of snow-melt runoff. However, broken stratocumulus cloud decks and thin cirrus over broken sea ice remain difficult to distinguish texturally. It is concluded that even with high spatial resolution imagery, it may not be possible to distinguish broken stratocumulus and thin clouds from sea ice in the marginal ice zone using the visible channel textural features alone.

Study on cavitation effect of mechanical seals with laser-textured porous surface

Science.gov (United States)

Liu, T.; Chen, H. l.; Liu, Y. H.; Wang, Q.; Liu, Z. B.; Hou, D. H.

2012-11-01

Study on the mechanisms underlying generation of hydrodynamic pressure effect associated with laser-textured porous surface on mechanical seal, is the key to seal and lubricant properties. The theory model of mechanical seals with laser-textured porous surface (LES-MS) based on cavitation model was established. The LST-MS was calculated and analyzed by using Fluent software with full cavitation model and non-cavitation model and film thickness was predicted by the dynamic mesh technique. The results indicate that the effect of hydrodynamic pressure and cavitation are the important reasons to generate liquid film opening force on LST-MS; Cavitation effect can enhance hydrodynamic pressure effect of LST-MS; The thickness of liquid film could be well predicted with the method of dynamic mesh technique on Fluent and it becomes larger as the increasing of shaft speed and the decreasing of pressure.

Study on cavitation effect of mechanical seals with laser-textured porous surface

International Nuclear Information System (INIS)

Liu, T; Chen, H l; Liu, Y H; Wang, Q; Liu, Z B; Hou, D H

2012-01-01

Study on the mechanisms underlying generation of hydrodynamic pressure effect associated with laser-textured porous surface on mechanical seal, is the key to seal and lubricant properties. The theory model of mechanical seals with laser-textured porous surface (LES-MS) based on cavitation model was established. The LST-MS was calculated and analyzed by using Fluent software with full cavitation model and non-cavitation model and film thickness was predicted by the dynamic mesh technique. The results indicate that the effect of hydrodynamic pressure and cavitation are the important reasons to generate liquid film opening force on LST-MS; Cavitation effect can enhance hydrodynamic pressure effect of LST-MS; The thickness of liquid film could be well predicted with the method of dynamic mesh technique on Fluent and it becomes larger as the increasing of shaft speed and the decreasing of pressure.

Effects of Two-stage Heat Treatment on Delayed Coke and Study of Their Surface Texture Characteristics

Science.gov (United States)

Im, Ui-Su; Kim, Jiyoung; Lee, Seon Ho; Lee, Byung-Rok; Peck, Dong-Hyun; Jung, Doo-Hwan

2017-12-01

In the present study, surface texture features and chemical properties of two types of cokes, made from coal tar by either 1-stage heat treatment or 2-stage heat treatment, were researched. The relationship between surface texture characteristics and the chemical properties was identified through molecular weight distribution, insolubility of coal tar, weight loss with temperature increase, coking yield, and polarized light microscope analysis. Rapidly cleared anisotropy texture in cokes was observed in accordance with the coking temperature rise. Quinoline insolubility and toluene insolubility of coal tar increased with a corresponding increases in coking temperature. In particular, the cokes produced by the 2-stage heat treatment (2S-C) showed surface structure of needle cokes at a temperature approximately 50°C lower than the 1-stage heat treatment (1S-C). Additionally, the coking yield of 2S-C increased by approximately 14% in comparison with 1S-C.

Nd:YOV4 laser surface texturing on DLC coating: Effect on morphology, adhesion, and dry wear behavior

Science.gov (United States)

Surfaro, Maria; Giorleo, Luca; Montesano, Lorenzo; Allegri, Gabriele; Ceretti, Elisabetta; La Vecchia, Giovina Marina

2018-05-01

The surface of structural components is usually subjected to higher stresses, greater wear or fatigue damage, and more direct environmental exposure than the inner parts. For this reason, the interest to improve superficial properties of items is constantly increasing in different fields as automotive, electronic, biomedical, etc. Different approaches can be used to achieve this goal: case hardening by means of superficial heat treatments like carburizing or nitriding, deposition of thin or thick coatings, roughness modification, etc. Between the available technologies to modify components surface, Laser Surface Texturing (LST) has already been recognized in the last decade as a process, which improves the tribological properties of various parts. Based on these considerations the aim of the present research work was to realize a controlled laser texture on a Diamond-like Carbon (DLC) thin coating (about 3 µm thick) without damaging both the coating itself and the substrate. In particular, the effect of laser process parameters as marking speed and loop cycle were investigated in terms of texture features modifications. Both qualitative and quantitative analyses of the texture were executed by using a scanning electron microscope and a laser probe system to select the proper laser parameters. Moreover, the effect of the selected texture on the DLC nanohardness, adhesion and wear behavior was pointed out.

Comparison of features response in texture-based iris segmentation

CSIR Research Space (South Africa)

Bachoo, A

2009-03-01

Full Text Available the Fisher linear discriminant and the iris region of interest is extracted. Four texture description methods are compared for segmenting iris texture using a region based pattern classification approach: Grey Level Co-occurrence Matrix (GLCM), Discrete...

Simulating the Effect of Modulated Tool-Path Chip Breaking On Surface Texture and Chip Length

Energy Technology Data Exchange (ETDEWEB)

Smith, K.S.; McFarland, J.T.; Tursky, D. A.; Assaid, T. S.; Barkman, W. E.; Babelay, Jr., E. F.

2010-04-30

One method for creating broken chips in turning processes involves oscillating the cutting tool in the feed direction utilizing the CNC machine axes. The University of North Carolina at Charlotte and the Y-12 National Security Complex have developed and are refining a method to reliably control surface finish and chip length based on a particular machine's dynamic performance. Using computer simulations it is possible to combine the motion of the machine axes with the geometry of the cutting tool to predict the surface characteristics and map the surface texture for a wide range of oscillation parameters. These data allow the selection of oscillation parameters to simultaneously ensure broken chips and acceptable surface characteristics. This paper describes the machine dynamic testing and characterization activities as well as the computational method used for evaluating and predicting chip length and surface texture.

Soil texture classification algorithm using RGB characteristics of soil images

Science.gov (United States)

Soil texture has an important influence on agriculture, affecting crop selection, movement of nutrients and water, soil electrical conductivity, and crop growth. Soil texture has traditionally been determined in the laboratory using pipette and hydrometer methods that require a considerable amount o...

Numerical modelling of microdroplet self-propelled jumping on micro-textured surface

Science.gov (United States)

Attarzadeh, S. M. Reza; Dolatabadi, Ali; Chun Kim, Kyung

2015-11-01

Understanding various stages of single and multiple droplet impact on a super-hydrophobic surface is of interest for many industrial applications such as aerospace industry. In this study, the phenomenon of coalescence induced droplets self-propelled jumping on a micro-textured super-hydrophobic surface is numerically simulated using Volume of Fluid (VOF) method. This model mimics the scenario of coalescing cloud-sized particles over the surface structure of an aircraft. The VOF coupled with a dynamic contact angle model is used to simulate the coalescence of two equal size droplets, that are initially placed very closed to each other with their interface overlapping with each other's which triggers the incipience of their coalescence. The textured surface is modeled as a series of equally spaced squared pillars, with 111° as the intrinsic contact angle all over the solid contact area. It is shown that the radial velocity of coalescing liquid bridge is reverted to upward direction due to the counter action of the surface to the basal area of droplet in contact. The presence of air beneath the droplet inside micro grooves which aimed at repelling water droplet is also captured in this model. The simulated results are found in good agreement with experimental observations. The authors gratefully acknowledge the financial support from Natural Sciences and Engineering Research Council of Canada (NSERC), Consortium de Recherche et d'innovation en Aerospatiale au Quebec (CRIAQ), Bombardier Aerospace, Pratt Whitney Canada.

Memory color of natural familiar objects: effects of surface texture and 3-D shape.

Science.gov (United States)

Vurro, Milena; Ling, Yazhu; Hurlbert, Anya C

2013-06-28

Natural objects typically possess characteristic contours, chromatic surface textures, and three-dimensional shapes. These diagnostic features aid object recognition, as does memory color, the color most associated in memory with a particular object. Here we aim to determine whether polychromatic surface texture, 3-D shape, and contour diagnosticity improve memory color for familiar objects, separately and in combination. We use solid three-dimensional familiar objects rendered with their natural texture, which participants adjust in real time to match their memory color for the object. We analyze mean, accuracy, and precision of the memory color settings relative to the natural color of the objects under the same conditions. We find that in all conditions, memory colors deviate slightly but significantly in the same direction from the natural color. Surface polychromaticity, shape diagnosticity, and three dimensionality each improve memory color accuracy, relative to uniformly colored, generic, or two-dimensional shapes, respectively. Shape diagnosticity improves the precision of memory color also, and there is a trend for polychromaticity to do so as well. Differently from other studies, we find that the object contour alone also improves memory color. Thus, enhancing the naturalness of the stimulus, in terms of either surface or shape properties, enhances the accuracy and precision of memory color. The results support the hypothesis that memory color representations are polychromatic and are synergistically linked with diagnostic shape representations.

Texture analysis using Gabor wavelets

Science.gov (United States)

Naghdy, Golshah A.; Wang, Jian; Ogunbona, Philip O.

1996-04-01

Receptive field profiles of simple cells in the visual cortex have been shown to resemble even- symmetric or odd-symmetric Gabor filters. Computational models employed in the analysis of textures have been motivated by two-dimensional Gabor functions arranged in a multi-channel architecture. More recently wavelets have emerged as a powerful tool for non-stationary signal analysis capable of encoding scale-space information efficiently. A multi-resolution implementation in the form of a dyadic decomposition of the signal of interest has been popularized by many researchers. In this paper, Gabor wavelet configured in a 'rosette' fashion is used as a multi-channel filter-bank feature extractor for texture classification. The 'rosette' spans 360 degrees of orientation and covers frequencies from dc. In the proposed algorithm, the texture images are decomposed by the Gabor wavelet configuration and the feature vectors corresponding to the mean of the outputs of the multi-channel filters extracted. A minimum distance classifier is used in the classification procedure. As a comparison the Gabor filter has been used to classify the same texture images from the Brodatz album and the results indicate the superior discriminatory characteristics of the Gabor wavelet. With the test images used it can be concluded that the Gabor wavelet model is a better approximation of the cortical cell receptive field profiles.

Bilinear magnetoelectric resistance as a probe of three-dimensional spin texture in topological surface states

Science.gov (United States)

He, Pan; Zhang, Steven S.-L.; Zhu, Dapeng; Liu, Yang; Wang, Yi; Yu, Jiawei; Vignale, Giovanni; Yang, Hyunsoo

2018-05-01

Surface states of three-dimensional topological insulators exhibit the phenomenon of spin-momentum locking, whereby the orientation of an electron spin is determined by its momentum. Probing the spin texture of these states is of critical importance for the realization of topological insulator devices, but the main technique currently available is spin- and angle-resolved photoemission spectroscopy. Here we reveal a close link between the spin texture and a new kind of magnetoresistance, which depends on the relative orientation of the current with respect to the magnetic field as well as the crystallographic axes, and scales linearly with both the applied electric and magnetic fields. This bilinear magnetoelectric resistance can be used to map the spin texture of topological surface states by simple transport measurements. For a prototypical Bi2Se3 single layer, we can map both the in-plane and out-of-plane components of the spin texture (the latter arising from hexagonal warping). Theoretical calculations suggest that the bilinear magnetoelectric resistance originates from conversion of a non-equilibrium spin current into a charge current under application of the external magnetic field.

Design and characterization of textured surfaces for applications in the food industry

Science.gov (United States)

Lazzini, G.; Romoli, L.; Blunt, L.; Gemini, L.

2017-12-01

The aim of this work is to design, manufacture and characterize surface morphologies on AISI 316L stainless steel produced by a custom designed laser-texturing strategy. Surface textures were characterized at a micrometric dimension in terms of areal parameters compliant with ISO 25178, and correlations between these parameters and processing parameters (e.g. laser energy dose supplied to the material, repetition rate of the laser pulses and scanning velocity) were investigated. Preliminary efforts were devoted to the research of special requirements for surface morphology that, according to the commonly accepted research on the influence of surface roughness on cellular adhesion on surfaces, should discourage the formation of biofilms. The topographical characterization of the surfaces was performed with a coherence scanning interferometer. This approach showed that increasing doses of energy to the surfaces increased the global level of roughness as well as the surface complexity. Moreover, the behavior of the parameters S pk, S vk also indicates that, due to the ablation process, an increase in the energy dose causes an average increase in the height of the highest peaks and in the depth of the deepest dales. The study of the density of peaks S pd showed that none of the surfaces analyzed here seem to perfectly match the conditions dictated by the theories on cellular adhesion to confer anti-biofouling properties. However, this result seems to be mainly due to the limits of the resolving power of coherence scanning interferometry, which does not allow the resolution of sub-micrometric features which could be crucial in the prevention of cellular attachment.

Differences in the surface texture of aggregate particles determined by 3D model derived from optic microscope measurements

Directory of Open Access Journals (Sweden)

Jozef Komačka

2015-12-01

Full Text Available The surface texture of aggregate particles was investigated based on the 3D model of surface generated from the measurements by optic microscope. New software MicroSYS was developed to determine the wrapping plane of 3D model of aggregate using the function called “Thin plate spline“. New parameter for evaluation of surface texture of aggregate particle was proposed as the volumetric difference between two planes (wrapping plane and aggregate surface. Applicability of this parameters was tested on two aggregate fractions (4/8 and 8/11 coming form 11 quarries in Slovakia. The tested aggregates differed from petrography point of view and ranged from soft to hard. The difference among the quarries and also between fractions of aggregate was found out. The better surface texture was observed for the finner fraction of aggregate. Simultaneously, the better results were determined in the case of aggregate produced from the ingeous intrusive or extrusive rocks comparing to the sedimentary carbonate rocks aggregate.

Image segmentation and particles classification using texture analysis method

Directory of Open Access Journals (Sweden)

Mayar Aly Atteya

Full Text Available Introduction: Ingredients of oily fish include a large amount of polyunsaturated fatty acids, which are important elements in various metabolic processes of humans, and have also been used to prevent diseases. However, in an attempt to reduce cost, recent developments are starting a replace the ingredients of fish oil with products of microalgae, that also produce polyunsaturated fatty acids. To do so, it is important to closely monitor morphological changes in algae cells and monitor their age in order to achieve the best results. This paper aims to describe an advanced vision-based system to automatically detect, classify, and track the organic cells using a recently developed SOPAT-System (Smart On-line Particle Analysis Technology, a photo-optical image acquisition device combined with innovative image analysis software. Methods The proposed method includes image de-noising, binarization and Enhancement, as well as object recognition, localization and classification based on the analysis of particles’ size and texture. Results The methods allowed for correctly computing cell’s size for each particle separately. By computing an area histogram for the input images (1h, 18h, and 42h, the variation could be observed showing a clear increase in cell. Conclusion The proposed method allows for algae particles to be correctly identified with accuracies up to 99% and classified correctly with accuracies up to 100%.

Laser surface texturing of polymers for biomedical applications

Science.gov (United States)

Riveiro, Antonio; Maçon, Anthony L. B.; del Val, Jesus; Comesaña, Rafael; Pou, Juan

2018-02-01

Polymers are materials widely used in biomedical science because of their biocompatibility, and good mechanical properties (which, in some cases, are similar to those of human tissues); however, these materials are, in general, chemically and biologically inert. Surface characteristics, such as topography (at the macro-, micro, and nanoscale), surface chemistry, surface energy, charge or wettability are interrelated properties, and they cooperatively influence the biological performance of materials when used for biomedical applications. They regulate the biological response at the implant/tissue interface (e.g., influencing the cell adhesion, cell orientation, cell motility, etc.). Several surface processing techniques have been explored to modulate these properties for biomedical applications. Despite their potentials, these methods have limitations that prevent their applicability. In this regard, laser-based methods, in particular laser surface texturing (LST), can be an interesting alternative. Different works have showed the potentiality of this technique to control the surface properties of biomedical polymers and enhance their biological performance; however, more research is needed to obtain the desired biological response. This work provides a general overview of the basics and applications of LST for the surface modification of polymers currently used in the clinical practice (e.g. PEEK, UHMWPE, PP, etc.). The modification of roughness, wettability, and their impact on the biological response is addressed to offer new insights on the surface modification of biomedical polymers.

Synthesis of nano-textured biocompatible scaffolds from chicken eggshells

International Nuclear Information System (INIS)

Asghar, Waseem; Ilyas, Azhar; Sankaran, Jeyantt; Wan Yuan; Iqbal, Samir M; Kim, Young-Tae

2012-01-01

Cell adhesion, morphology and growth are influenced by surface topography at nano and micrometer scales. Nano-textured surfaces are prepared using photolithography, plasma etching and long polymer chemical etching which are cost prohibitive and require specialized equipment. This article demonstrates a simple approach to synthesize nano-textured scaffolds from chicken eggshells. Varieties of pattern are made on the eggshells like micro-needle forests and nanopores, giving very uniform nano-textures to the surfaces. The surfaces are characterized for chemical composition and crystal phase. The novel patterns are transferred to PDMS surfaces and the nano-textured PDMS surfaces are used to study the effect of texturing on human fibroblast cell growth and attachment. The effects of surface topographies, along with laminin coating on cell cultures, are also studied. We find an exciting phenomenon that the initial seeding density of the fibroblast cells affects the influence of the nano-texturing on cell growth. These nano-textured surfaces give 16 times more fibroblast growth when compared to flat PDMS surfaces. The novel nano-textured patterns also double the laminin adsorption on PDMS. (paper)

Arc-textured metal surfaces for high thermal emittance space radiators

International Nuclear Information System (INIS)

Banks, B.A.; Rutledge, S.K.; Mirtich, M.J.; Behrend, T.; Hotes, D.; Kussmaul, M.; Barry, J.; Stidham, C.; Stueber, T.; DiFilippo, F.

1994-01-01

Carbon arc electrical discharges struck across the surfaces of metals such as Nb-1% Zr, alter the morphology to produce a high thermal emittance surface. Metal from the surface and carbon from the arc electrode vaporize during arcing, and then condense on the metal surface to produce a microscopically rough surface having a high thermal emittance. Quantitative spectral reflectance measurements from 0.33 to 15 μm were made on metal surfaces which were carbon arc treated in an inert gas environment. The resulting spectral reflectance data were then used to calculate thermal emittance as a function of temperature for various methods of arc treatment. The results of arc treatment on various metals are presented for both ac and dc arcs. Surface characterization data, including thermal emittance as a function of temperature, scanning electron microscopy, and atomic oxygen durability, are also presented. Ac arc texturing was found to increase the thermal emittance at 800 K from 0.05. to 0.70

Texture-based segmentation with Gabor filters, wavelet and pyramid decompositions for extracting individual surface features from areal surface topography maps

International Nuclear Information System (INIS)

Senin, Nicola; Leach, Richard K; Pini, Stefano; Blunt, Liam A

2015-01-01

Areal topography segmentation plays a fundamental role in those surface metrology applications concerned with the characterisation of individual topography features. Typical scenarios include the dimensional inspection and verification of micro-structured surface features, and the identification and characterisation of localised defects and other random singularities. While morphological segmentation into hills or dales is the only partitioning operation currently endorsed by the ISO specification standards on surface texture metrology, many other approaches are possible, in particular adapted from the literature on digital image segmentation. In this work an original segmentation approach is introduced and discussed, where topography partitioning is driven by information collected through the application of texture characterisation transforms popular in digital image processing. Gabor filters, wavelets and pyramid decompositions are investigated and applied to a selected set of test cases. The behaviour, performance and limitations of the proposed approach are discussed from the viewpoint of the identification and extraction of individual surface topography features. (paper)

Texture and wettability of metallic lotus leaves

Science.gov (United States)

Frankiewicz, C.; Attinger, D.

2016-02-01

Superhydrophobic surfaces with the self-cleaning behavior of lotus leaves are sought for drag reduction and phase change heat transfer applications. These superrepellent surfaces have traditionally been fabricated by random or deterministic texturing of a hydrophobic material. Recently, superrepellent surfaces have also been made from hydrophilic materials, by deterministic texturing using photolithography, without low-surface energy coating. Here, we show that hydrophilic materials can also be made superrepellent to water by chemical texturing, a stochastic rather than deterministic process. These metallic surfaces are the first analog of lotus leaves, in terms of wettability, texture and repellency. A mechanistic model is also proposed to describe the influence of multiple tiers of roughness on wettability and repellency. This demonstrated ability to make hydrophilic materials superrepellent without deterministic structuring or additional coatings opens the way to large scale and robust manufacturing of superrepellent surfaces.Superhydrophobic surfaces with the self-cleaning behavior of lotus leaves are sought for drag reduction and phase change heat transfer applications. These superrepellent surfaces have traditionally been fabricated by random or deterministic texturing of a hydrophobic material. Recently, superrepellent surfaces have also been made from hydrophilic materials, by deterministic texturing using photolithography, without low-surface energy coating. Here, we show that hydrophilic materials can also be made superrepellent to water by chemical texturing, a stochastic rather than deterministic process. These metallic surfaces are the first analog of lotus leaves, in terms of wettability, texture and repellency. A mechanistic model is also proposed to describe the influence of multiple tiers of roughness on wettability and repellency. This demonstrated ability to make hydrophilic materials superrepellent without deterministic structuring or additional

Edge detection and texture classification by cuttlefish.

Science.gov (United States)

Zylinski, Sarah; Osorio, Daniel; Shohet, Adam J

2009-12-14

Cephalopod mollusks including octopus and cuttlefish are adept at adaptive camouflage, varying their appearance to suit the surroundings. This behavior allows unique access into the vision of a non-human species because one can ask how these animals use spatial information to control their coloration pattern. There is particular interest in factors that affect the relative levels of expression of the Mottle and the Disruptive body patterns. Broadly speaking, the Mottle is displayed on continuous patterned surfaces whereas the Disruptive is used on discrete objects such as pebbles. Recent evidence from common cuttlefish, Sepia officinalis, suggests that multiple cues are relevant, including spatial scale, contrast, and depth. We analyze the body pattern responses of juvenile cuttlefish to a range of checkerboard stimuli. Our results suggest that the choice of camouflage pattern is consistent with a simple model of how cuttlefish classify visual textures, according to whether they are Uniform or patterned, and whether the pattern includes visual edges. In particular, cuttlefish appear to detect edges by sensing the relative spatial phases of two spatial frequency components (e.g., fundamental and the third harmonic Fourier component in a square wave). We discuss the relevance of these findings to vision and camouflage in aquatic environments.

Fast Characterization of Moving Samples with Nano-Textured Surfaces

DEFF Research Database (Denmark)

Madsen, Morten Hannibal; Hansen, Poul-Erik; Zalkovskij, Maksim

2015-01-01

Characterization of structures using conventional optical microscopy is restricted by the diffraction limit. Techniques like atomic force and scanning electron microscopy can investigate smaller structures but are very time consuming. We show that using scatterometry, a technique based on optical...... diffraction, integrated into a commercial light microscope we can characterize nano-textured surfaces in a few milliseconds. The adapted microscope has two detectors, a CCD camera used to easily find an area of interest and a spectrometer for the measurements. We demonstrate that the microscope has...

Modeling of liquid–gas meniscus for textured surfaces: effects of curvature and local slip length

International Nuclear Information System (INIS)

Gaddam, Anvesh; Garg, Mayank; Agrawal, Amit; Joshi, Suhas S

2015-01-01

Surface texturing at the micro/nanolevel allows air to be trapped in sufficiently small cavities, thereby reducing the flow resistance over the surface in the laminar regime. The nature of the liquid–gas meniscus plays an important role in defining the boundary condition and it depends on the flow conditions and geometrical properties of textures. In the present work, we employ the unsteady volume of fluid model to investigate the behavior of the liquid–gas meniscus for ridges arranged normal to the flow direction to substantiate the frictional resistance of flow in a microchannel. It is found that the assumption of ‘zero shear stress’ at the liquid–gas interface grossly overpredicts the effective slip length with meniscus curvature and local partial slip length playing the dominant role. Numerical simulations performed in the laminar regime (20  <  Re  <  120) over single layered ridges normal to the flow direction revealed the effect of texture geometry on the reduction in pressure drop. In single layered structures, lotus-like geometries exhibited a greater reduction in drag (more than 30%) when compared to all other texture geometries. It is recognized that the flow experiences expansion and contraction cycles as it flows over the transverse ridges increasing the frictional resistance. Our findings will help to modify the boundary condition at the liquid–gas meniscus for accurate modeling in the laminar regime and to optimize the texture geometry to improve drag reduction. (paper)

Iris Image Classification Based on Hierarchical Visual Codebook.

Science.gov (United States)

Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

2014-06-01

Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection.

Altering textural properties of fermented milk by using surface-engineered Lactococcus lactis.

Science.gov (United States)

Tarazanova, Mariya; Huppertz, Thom; Kok, Jan; Bachmann, Herwig

2018-05-09

Lactic acid bacteria are widely used for the fermentation of dairy products. While bacterial acidification rates, proteolytic activity and the production of exopolysaccharides are known to influence textural properties of fermented milk products, little is known about the role of the microbial surface on microbe-matrix interactions in dairy products. To investigate how alterations of the bacterial cell surface affect fermented milk properties, 25 isogenic Lactococcus lactis strains that differed with respect to surface charge, hydrophobicity, cell chaining, cell-clumping, attachment to milk proteins, pili expression and EPS production were used to produce fermented milk. We show that overexpression of pili increases surface hydrophobicity of various strains from 3-19% to 94-99%. A profound effect of different cell surface properties was an altered spatial distribution of the cells in the fermented product. Aggregated cells tightly fill the cavities of the protein matrix, while chaining cells seem to be localized randomly. A positive correlation was found between pili overexpression and viscosity and gel hardness of fermented milk. Gel hardness also positively correlated with clumping of cells in the fermented milk. Viscosity of fermented milk was also higher when it was produced with cells with a chaining phenotype or with cells that overexpress exopolysaccharides. Our results show that alteration of cell surface morphology affects textural parameters of fermented milk and cell localization in the product. This is indicative of a cell surface-dependent potential of bacterial cells as structure elements in fermented foods. © 2018 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Sliding behavior of oil droplets on nanosphere stacking layers with different surface textures

International Nuclear Information System (INIS)

Hsieh, Chien-Te; Wu, Fang-Lin; Chen, Wei-Yu

2010-01-01

Two facile coating techniques, gravitational sediment and spin coating, were applied for the creation of silica sphere stacking layers with different textures onto glass substrates that display various sliding abilities toward liquid drops with different surface tensions, ranged from 25.6 to 72.3 mN/m. The resulting silica surface exhibits oil repellency, long-period durability > 30 days, and oil sliding capability. The two-tier texture offers a better roll-off ability toward liquid drops with a wide range of γ L , ranged from 30.2 to 72.3 mN/m, i.e., when the sliding angle (SA) ad ) appears to describe the sliding behavior within the W ad region: 2.20-3.03 mN/m. The smaller W ad , the easier drop sliding (i.e., the smaller SA value) takes place on the surfaces. The W ad value ∼3.03 mN/m shows a critical kinetic barrier for drop sliding on the silica surfaces from stationary to movement states. This work proposes a mathematical model to simulate the sliding behavior of oil drops on a nanosphere stacking layer, confirming the anti-oil contamination capability.

Assessing Asphalt and Concrete Pavement Surface Texture in the Field

OpenAIRE

Saad I. Sarsam; Huda N. Al Shareef

2016-01-01

The incorporation of safety characteristics into the traditional pavement structural design or in the functional evaluation of pavement condition has not been established yet. The design has focused on the structural capacity of the roadway so that the pavement can withstand specific level of repetitive loading over the design life. On the other hand, the surface texture condition was neither included in the AASHTO design procedure nor in the present serviceability index measurements. The ...

New Statistics for Texture Classification Based on Gabor Filters

Directory of Open Access Journals (Sweden)

J. Pavlovicova

2007-09-01

Full Text Available The paper introduces a new method of texture segmentation efficiency evaluation. One of the well known texture segmentation methods is based on Gabor filters because of their orientation and spatial frequency character. Several statistics are used to extract more information from results obtained by Gabor filtering. Big amount of input parameters causes a wide set of results which need to be evaluated. The evaluation method is based on the normal distributions Gaussian curves intersection assessment and provides a new point of view to the segmentation method selection.

Effects of textural and surface characteristics of microporous activated carbons on the methane adsorption capacity at high pressures

International Nuclear Information System (INIS)

Bastos-Neto, M.; Canabrava, D.V.; Torres, A.E.B.; Rodriguez-Castellon, E.; Jimenez-Lopez, A.; Azevedo, D.C.S.; Cavalcante, C.L.

2007-01-01

The objective of this study is to relate textural and surface characteristics of selected microporous activated carbons to their methane storage capacity. In this work, a magnetic suspension balance (Rubotherm, Germany) was used to measure methane adsorption isotherms of several activated carbon samples. Textural characteristics were assessed by nitrogen adsorption on a regular surface area analyzer (Autosorb-MP, by Quantachrome, USA). N 2 adsorption was analysed by conventional models (BET, DR, HK) and by Monte Carlo molecular simulations. Elemental and surface analyses were performed by X-ray photoelectronic spectroscopy (XPS) for the selected samples. A comparative analysis was then carried out with the purpose of defining some correlation among the variables under study. For the system under study, pore size distribution and micropore volume seem to be a determining factor as long as the solid surface is perfectly hydrophobic. It was concluded that the textural parameters per se do not unequivocally determine natural gas storage capacities. Surface chemistry and methane adsorption equilibria must be taken into account in the decision-making process of choosing an adsorbent for gas storage

Textural pattern classification for oral squamous cell carcinoma.

Science.gov (United States)

Rahman, T Y; Mahanta, L B; Chakraborty, C; DAS, A K; Sarma, J D

2018-01-01

Despite being an area of cancer with highest worldwide incidence, oral cancer yet remains to be widely researched. Studies on computer-aided analysis of pathological slides of oral cancer contribute a lot to the diagnosis and treatment of the disease. Some researches in this direction have been carried out on oral submucous fibrosis. In this work an approach for analysing abnormality based on textural features present in squamous cell carcinoma histological slides have been considered. Histogram and grey-level co-occurrence matrix approaches for extraction of textural features from biopsy images with normal and malignant cells are used here. Further, we have used linear support vector machine classifier for automated diagnosis of the oral cancer, which gives 100% accuracy. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

Development of a surface topography instrument for automotive textured steel plate

Science.gov (United States)

Wang, Zhen; Wang, Shenghuai; Chen, Yurong; Xie, Tiebang

2010-08-01

The surface topography of automotive steel plate is decisive to its stamping, painting and image clarity performances. For measuring this kind of surface topography, an instrument has been developed based on the principle of vertical scanning white light microscopy interference principle. The microscopy interference system of this instrument is designed based on the structure of Linnik interference microscopy. The 1D worktable of Z direction is designed and introduced in details. The work principle of this instrument is analyzed. In measuring process, the interference microscopy is derived as a whole and the measured surface is scanned in vertical direction. The measurement accuracy and validity is verified by templates. Surface topography of textured steel plate is also measured by this instrument.

Orbital selective spin-texture in a topological insulator

Energy Technology Data Exchange (ETDEWEB)

Singh, Bahadur, E-mail: bahadursingh24@gmail.com; Prasad, R. [Department of Physics, Indian Institute of Technology Kanpur, Kanpur 208016 (India)

2015-05-15

Three-dimensional topological insulators support a metallic non-trivial surface state with unique spin texture, where spin and momentum are locked perpendicular to each other. In this work, we investigate the orbital selective spin-texture associated with the topological surface states in Sb2Te{sub 3}, using the first principles calculations. Sb2Te{sub 3} is a strong topological insulator with a p-p type bulk band inversion at the Γ-point and supports a single topological metallic surface state with upper (lower) Dirac-cone has left (right) handed spin-texture. Here, we show that the topological surface state has an additional locking between the spin and orbitals, leading to an orbital selective spin-texture. The out-of-plane orbitals (p{sub z} orbitals) have an isotropic orbital texture for both the Dirac cones with an associated left and right handed spin-texture for the upper and lower Dirac cones, respectively. In contrast, the in-planar orbital texture (p{sub x} and p{sub y} projections) is tangential for the upper Dirac-cone and is radial for the lower Dirac-cone surface state. The dominant in-planar orbital texture in both the Dirac cones lead to a right handed orbital-selective spin-texture.

Performance of two-lobe hole-entry hybrid journal bearing system under the combined influence of textured surface and couple stress lubricant

Science.gov (United States)

Khatri, Chandra B.; Sharma, Satish C.

2018-02-01

Textured surface in journal bearings is becoming an important area of investigation during the last few years. Surface textures have the shapes of micro-dimple with a small diameter and depth having order of magnitude of bearing clearance. This paper presents the influence of couple stress lubricant on the circular and non-circular hole-entry hybrid journal bearing system and reports the comparative study between the textured and non-textured circular/non-circular hybrid journal bearing system. The governing Reynolds equation has been modified for the couple stress lubricant flow in the clearance of bearing and journal. The FEM technique has been applied to solve the modified Reynolds equation together with restrictor flow equation. The numerically simulated results indicate that the influence of couple stress lubricant is significantly more in textured journal bearing than that of non-textured journal bearing. Further, it has been observed that the textured two-lobe (δ = 1.1) hybrid journal bearing lubricated with couple stress lubricant provides larger values of fluid film stiffness coefficients and stability threshold speed against other bearings studied in the present paper.

Robust surface roughness indices and morphological interpretation

Science.gov (United States)

Trevisani, Sebastiano; Rocca, Michele

2016-04-01

Geostatistical-based image/surface texture indices based on variogram (Atkison and Lewis, 2000; Herzfeld and Higginson, 1996; Trevisani et al., 2012) and on its robust variant MAD (median absolute differences, Trevisani and Rocca, 2015) offer powerful tools for the analysis and interpretation of surface morphology (potentially not limited to solid earth). In particular, the proposed robust index (Trevisani and Rocca, 2015) with its implementation based on local kernels permits the derivation of a wide set of robust and customizable geomorphometric indices capable to outline specific aspects of surface texture. The stability of MAD in presence of signal noise and abrupt changes in spatial variability is well suited for the analysis of high-resolution digital terrain models. Moreover, the implementation of MAD by means of a pixel-centered perspective based on local kernels, with some analogies to the local binary pattern approach (Lucieer and Stein, 2005; Ojala et al., 2002), permits to create custom roughness indices capable to outline different aspects of surface roughness (Grohmann et al., 2011; Smith, 2015). In the proposed poster, some potentialities of the new indices in the context of geomorphometry and landscape analysis will be presented. At same time, challenges and future developments related to the proposed indices will be outlined. Atkinson, P.M., Lewis, P., 2000. Geostatistical classification for remote sensing: an introduction. Computers & Geosciences 26, 361-371. Grohmann, C.H., Smith, M.J., Riccomini, C., 2011. Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland. IEEE Transactions on Geoscience and Remote Sensing 49, 1220-1213. Herzfeld, U.C., Higginson, C.A., 1996. Automated geostatistical seafloor classification - Principles, parameters, feature vectors, and discrimination criteria. Computers and Geosciences, 22 (1), pp. 35-52. Lucieer, A., Stein, A., 2005. Texture-based landform segmentation of LiDAR imagery

TEXTURAL FRACTOGRAPHY

Directory of Open Access Journals (Sweden)

Hynek Lauschmann

2011-05-01

Full Text Available The reconstitution of the history of a fatigue process is based on the knowledge of any correspondences between the morphology of the crack surface and the velocity of the crack growth (crack growth rate - CGR. The textural fractography is oriented to mezoscopic SEM magnifications (30 to 500x. Images contain complicated textures without distinct borders. The aim is to find any characteristics of this texture, which correlate with CGR. Pre-processing of images is necessary to obtain a homogeneous texture. Three methods of textural analysis have been developed and realized as computational programs: the method based on the spectral structure of the image, the method based on a Gibbs random field (GRF model, and the method based on the idealization of light objects into a fibre process. In order to extract and analyze the fibre process, special methods - tracing fibres and a database-oriented analysis of a fibre process - have been developed.

Frictional Performance Assessment of Cemented Carbide Surfaces Textured by Laser

Science.gov (United States)

Fang, S.; Llanes, L.; Klein, S.; Gachot, C.; Rosenkranz, A.; Bähre, D.; Mücklich, F.

2017-10-01

Cemented carbides are advanced engineering materials often used in industry for manufacturing cutting tools or supporting parts in tribological system. In order to improve service life, special attention has been paid to change surface conditions by means of different methods, since surface modification can be beneficial to reduce the friction between the contact surfaces as well as to avoid unintended damage. Laser surface texturing is one of the newly developed surface modification methods. It has been successfully introduced to fabricate some basic patterns on cemented carbide surfaces. In this work, Direct Laser Interference Patterning Technique (DLIP) is implemented to produce special line-like patterns on a cobalt (Co) and nickel (Ni) based cemented tungsten carbide grade. It is proven that the laser-produced patterns have high geometrical precision and quality stability. Furthermore, tribology testing using a nano-tribometer unit shows that friction is reduced by the line-like patterns, as compared to the polished one, under both lubricated and dry testing regimes, and the reduction is more pronounced in the latter case.

Microstructure and Texture in Surface Deformation Layer of Al-Zn-Mg-Cu Alloy Processed by Milling

Directory of Open Access Journals (Sweden)

CHEN Yanxia

2017-12-01

Full Text Available The microstructural and crystallographic features of the surface deformation layer in Al-Zn-Mg-Cu alloy induced by milling were investigated by means of transmission electron microscopy (TEM and precession electron diffraction (PED assisted nanoscale orientation mapping. The result shows that the surface deformation layer is composed by the top surface of equiaxed nanograins/ultrafine grains and the subsurface of lamellar nanograins/ultrafine grains surrounded by coarse grain boundary precipitates (GBPs. The recrystallized nanograins/ultrafine grains in the deformation layer show direct evidence that dynamic recrystallization plays an important role in grain refining process. The GBPs and grain interior precipitates (GIPs show a great difference in size and density with the matrix due to the thermally and mechanically induced precipitate redistribution. The crystallographic texture of the surface deformation layer is proved to be a mixture of approximate copper{112}, rotated cube{001} and F {111}. The severe shear deformation of the surface induced by milling is responsible for the texture evolution.

Fusion of geometric and texture features for finger knuckle surface recognition

Directory of Open Access Journals (Sweden)

K. Usha

2016-03-01

Full Text Available Hand-based biometrics plays a significant role in establishing security for real-time environments involving human interaction and is found to be more successful in terms of high speed and accuracy. This paper investigates on an integrated approach for personal authentication using Finger Back Knuckle Surface (FBKS based on two methodologies viz., Angular Geometric Analysis based Feature Extraction Method (AGFEM and Contourlet Transform based Feature Extraction Method (CTFEM. Based on these methods, this personal authentication system simultaneously extracts shape oriented feature information and textural pattern information of FBKS for authenticating an individual. Furthermore, the proposed geometric and textural analysis methods extract feature information from both proximal phalanx and distal phalanx knuckle regions (FBKS, while the existing works of the literature concentrate only on the features of proximal phalanx knuckle region. The finger joint region found nearer to the tip of the finger is called distal phalanx region of FBKS, which is a unique feature and has greater potentiality toward identification. Extensive experiments conducted using newly created database with 5400 FBKS images and the obtained results infer that the integration of shape oriented features with texture feature information yields excellent accuracy rate of 99.12% with lowest equal error rate of 1.04%.

Bio-inspired design of ice-retardant devices based on benthic marine invertebrates: the effect of surface texture

Directory of Open Access Journals (Sweden)

Homayun Mehrabani

2014-09-01

Full Text Available Growth of ice on surfaces poses a challenge for both organisms and for devices that come into contact with liquids below the freezing point. Resistance of some organisms to ice formation and growth, either in subtidal environments (e.g., Antarctic anchor ice, or in environments with moisture and cold air (e.g., plants, intertidal begs examination of how this is accomplished. Several factors may be important in promoting or mitigating ice formation. As a start, here we examine the effect of surface texture alone. We tested four candidate surfaces, inspired by hard-shelled marine invertebrates and constructed using a three-dimensional printing process. We examined sub-polar marine organisms to develop sample textures and screened them for ice formation and accretion in submerged conditions using previous methods for comparison to data for Antarctic organisms. The sub-polar organisms tested were all found to form ice readily. We also screened artificial 3-D printed samples using the same previous methods, and developed a new test to examine ice formation from surface droplets as might be encountered in environments with moist, cold air. Despite limitations inherent to our techniques, it appears surface texture plays only a small role in delaying the onset of ice formation: a stripe feature (corresponding to patterning found on valves of blue mussels, Mytilus edulis, or on the spines of the Antarctic sea urchin Sterechinus neumayeri slowed ice formation an average of 25% compared to a grid feature (corresponding to patterning found on sub-polar butterclams, Saxidomas nuttalli. The geometric dimensions of the features have only a small (∼6% effect on ice formation. Surface texture affects ice formation, but does not explain by itself the large variation in ice formation and species-specific ice resistance observed in other work. This suggests future examination of other factors, such as material elastic properties and surface coatings, and their

A plateau–valley separation method for textured surfaces with a deterministic pattern

DEFF Research Database (Denmark)

Godi, Alessandro; Kühle, Anders; De Chiffre, Leonardo

2014-01-01

The effective characterization of textured surfaces presenting a deterministic pattern of lubricant reservoirs is an issue with which many researchers are nowadays struggling. Existing standards are not suitable for the characterization of such surfaces, providing at times values without physical...... meaning. A new method based on the separation between the plateau and valley regions is hereby presented allowing independent functional analyses of the detected features. The determination of a proper threshold between plateaus and valleys is the first step of a procedure resulting in an efficient...

Optimization of surface morphology and scattering properties of TCO/AIT textured glass front electrode for thin film solar cells

Energy Technology Data Exchange (ETDEWEB)

Addonizio, M.L., E-mail: marialuisa.addonizio@enea.it; Fusco, L.; Antonaia, A.; Cominale, F.; Usatii, I.

2015-12-01

Graphical abstract: - Highlights: • Aluminium induced texture (AIT) method has been used for obtaining highly textured glass substrates. • The effect of wet etch step on morphological and optical properties has been analyzed. • The morphology features have been optimized in order to obtain the best scattering properties. • Different ZnO surface textures, depending on the underlying glass substrate structures, are obtained. • The effect of different glass texture on optical confinement has been tested in a-Si:H devices. - Abstract: Aluminium induced texture (AIT) method has been used for obtaining highly textured glass substrate suitable for silicon based thin film solar cell technology. Wet etch step parameters of AIT process have been varied and effect of different etchants and different etching times on morphological and optical properties has been analyzed. The resulting morphology features (shape, size distribution, inclination angle) have been optimized in order to obtain the best scattering properties. ZnO:Ga (GZO) films have been deposited by sputtering technique on AIT-processed glass. Two different ZnO surface morphologies have been obtained, strongly depending on the underlying glass substrate morphology induced by different etching times. Very rough and porous texture (σ{sub rms} ∼ 150 nm) was obtained on glass etched 2 min showing cauliflower-like structure, whereas a softer texture (σ{sub rms} ∼ 78 nm) was obtained on glass etched 7 min giving wider and smoother U-shaped craters. The effect of different glass textures on optical confinement has been tested in amorphous silicon based p-i-n devices. Devices fabricated on GZO/high textured glass showed a quantum efficiency enhancement due to both an effective light trapping phenomenon and an effective anti-reflective optical behaviour. Short etching time produce smaller cavities (<1 μm) with deep U-shape characterized by high roughness, high inclination angle and low autocorrelation

Multi-Scale Texturing of Metallic Surfaces for High Performance Military Systems

Science.gov (United States)

2015-08-17

AISI 440C stainless steel balls of 3 mm radius and 690 HV hardness. The sliding time (20 min), amplitude (10.5 mm), frequency (1.5 Hz) and normal...texture form (e. g., micro-scale topography) on surface integrity measures and tribological wear performance were quantified. The ensuing results are... Tribological Applications, Submitted for publication (08 2015) TOTAL: 2 Books Number of Manuscripts: Patents Submitted Patents Awarded Awards Graduate Students

Influence of citric acid on the surface texture of glass ionomer restorative materials

OpenAIRE

Reddy, Dappili Swami Ranga; Kumar, Ramachandran Anil; Venkatesan, Sokkalingam Mothilal; Narayan, Gopal Shankar; Duraivel, Dasarathan; Indra, Rajamani

2014-01-01

Aim: This study determined the effectiveness of G-coat plus surface protective agent over petroleum jelly on the surface texture of conventional Glass ionomer restorative materials. Materials and Methods: Three chemically cured conventional glass ionomer restorative materials type II, type IX and ketac molar were evaluated in this study. Sixty specimens were made for each restorative material. They were divided into two groups of thirty specimens each. Of the sixty specimens, thirty were...

3-D Solid Texture Classification Using Locally-Oriented Wavelet Transforms

OpenAIRE

Dicente Cid Yashin; Müller Henning; Platon Alexandra; Poletti Pierre-Alexandre; Depeursinge Adrien

2017-01-01

Many image acquisition techniques used in biomedical imaging material analysis and structural geology are capable of acquiring 3D solid images. Computational analysis of these images is complex but necessary since it is difficult for humans to visualize and quantify their detailed 3D content. One of the most common methods to analyze 3D data is to characterize the volumetric texture patterns. Texture analysis generally consists of encoding the local organization of image scales and directions...

Light scattering effect of ITO:Zr/AZO films deposited on periodic textured glass surface morphologies for silicon thin film solar cells

Energy Technology Data Exchange (ETDEWEB)

Hussain, Shahzada Qamar [Sungkyunkwan University, Department of Energy Science, Suwon (Korea, Republic of); COMSATS Institute of Information Technology, Department of Physics, Lahore (Pakistan); Kwon, Gi Duk; Kim, Sunbo; Balaji, Nagarajan; Shin, Chonghoon; Kim, Sangho; Khan, Shahbaz; Pribat, Didier [Sungkyunkwan University, Department of Energy Science, Suwon (Korea, Republic of); Ahn, Shihyun; Le, Anh Huy Tuan; Park, Hyeongsik; Raja, Jayapal; Lee, Youn-Jung [Sungkyunkwan University, College of Information and Communication Engineering, Suwon (Korea, Republic of); Razaq, Aamir [COMSATS Institute of Information Technology, Department of Physics, Lahore (Pakistan); Velumani, S. [Sungkyunkwan University, College of Information and Communication Engineering, Suwon (Korea, Republic of); Department of Electrical Engineering (SEES), Mexico City (Mexico); Yi, Junsin [Sungkyunkwan University, Department of Energy Science, Suwon (Korea, Republic of); Sungkyunkwan University, College of Information and Communication Engineering, Suwon (Korea, Republic of)

2015-09-15

Various SF{sub 6}/Ar plasma-textured periodic glass surface morphologies for high transmittance, haze ratio and low sheet resistance of ITO:Zr films are reported. The SF{sub 6}/Ar plasma-textured glass surface morphologies were changed from low aspect ratio to high aspect ratio with the increase in RF power from 500 to 600 W. The micro- and nano-size features of textured glass surface morphologies enhanced the haze ratio in visible as well as NIR wavelength region. Micro-size textured features also influenced the sheet resistance and electrical characteristics of ITO:Zr films due to step coverage. The ITO:Zr/AZO bilayer was used as front TCO electrode for p-i-n amorphous silicon thin film solar cells with current density-voltage characteristics as: V{sub oc} = 875 mV, FF = 70.90 %, J{sub sc} = 11.31 mA/cm{sup 2}, η = 7.02 %. (orig.)

High-resolution imaging of cellular processes across textured surfaces using an indexed-matched elastomer.

Science.gov (United States)

Ravasio, Andrea; Vaishnavi, Sree; Ladoux, Benoit; Viasnoff, Virgile

2015-03-01

Understanding and controlling how cells interact with the microenvironment has emerged as a prominent field in bioengineering, stem cell research and in the development of the next generation of in vitro assays as well as organs on a chip. Changing the local rheology or the nanotextured surface of substrates has proved an efficient approach to improve cell lineage differentiation, to control cell migration properties and to understand environmental sensing processes. However, introducing substrate surface textures often alters the ability to image cells with high precision, compromising our understanding of molecular mechanisms at stake in environmental sensing. In this paper, we demonstrate how nano/microstructured surfaces can be molded from an elastomeric material with a refractive index matched to the cell culture medium. Once made biocompatible, contrast imaging (differential interference contrast, phase contrast) and high-resolution fluorescence imaging of subcellular structures can be implemented through the textured surface using an inverted microscope. Simultaneous traction force measurements by micropost deflection were also performed, demonstrating the potential of our approach to study cell-environment interactions, sensing processes and cellular force generation with unprecedented resolution. Copyright © 2014 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Wafer Surface Charge Reversal as a Method of Simplifying Nanosphere Lithography for Reactive Ion Etch Texturing of Solar Cells

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Daniel Inns

2007-01-01

Full Text Available A simplified nanosphere lithography process has been developed which allows fast and low-waste maskings of Si surfaces for subsequent reactive ion etching (RIE texturing. Initially, a positive surface charge is applied to a wafer surface by dipping in a solution of aluminum nitrate. Dipping the positive-coated wafer into a solution of negatively charged silica beads (nanospheres results in the spheres becoming electrostatically attracted to the wafer surface. These nanospheres form an etch mask for RIE. After RIE texturing, the reflection of the surface is reduced as effectively as any other nanosphere lithography method, while this batch process used for masking is much faster, making it more industrially relevant.

Land-cover classification in a moist tropical region of Brazil with Landsat TM imagery.

Science.gov (United States)

Li, Guiying; Lu, Dengsheng; Moran, Emilio; Hetrick, Scott

2011-01-01

This research aims to improve land-cover classification accuracy in a moist tropical region in Brazil by examining the use of different remote sensing-derived variables and classification algorithms. Different scenarios based on Landsat Thematic Mapper (TM) spectral data and derived vegetation indices and textural images, and different classification algorithms - maximum likelihood classification (MLC), artificial neural network (ANN), classification tree analysis (CTA), and object-based classification (OBC), were explored. The results indicated that a combination of vegetation indices as extra bands into Landsat TM multispectral bands did not improve the overall classification performance, but the combination of textural images was valuable for improving vegetation classification accuracy. In particular, the combination of both vegetation indices and textural images into TM multispectral bands improved overall classification accuracy by 5.6% and kappa coefficient by 6.25%. Comparison of the different classification algorithms indicated that CTA and ANN have poor classification performance in this research, but OBC improved primary forest and pasture classification accuracies. This research indicates that use of textural images or use of OBC are especially valuable for improving the vegetation classes such as upland and liana forest classes having complex stand structures and having relatively large patch sizes.

Non-negative matrix factorization in texture feature for classification of dementia with MRI data

Science.gov (United States)

Sarwinda, D.; Bustamam, A.; Ardaneswari, G.

2017-07-01

This paper investigates applications of non-negative matrix factorization as feature selection method to select the features from gray level co-occurrence matrix. The proposed approach is used to classify dementia using MRI data. In this study, texture analysis using gray level co-occurrence matrix is done to feature extraction. In the feature extraction process of MRI data, we found seven features from gray level co-occurrence matrix. Non-negative matrix factorization selected three features that influence of all features produced by feature extractions. A Naïve Bayes classifier is adapted to classify dementia, i.e. Alzheimer's disease, Mild Cognitive Impairment (MCI) and normal control. The experimental results show that non-negative factorization as feature selection method able to achieve an accuracy of 96.4% for classification of Alzheimer's and normal control. The proposed method also compared with other features selection methods i.e. Principal Component Analysis (PCA).

Structure and texture of uranium ores in exogenous deposits

International Nuclear Information System (INIS)

Danchev, V.I.

1977-01-01

Structure and texture signs of uranium rock exogenous deposits have been systematized for the first time, taking into account the slaging of the ore-formation process, connected with formation and change of containing sedimentary rocks, starting with the sedimentogenesis stage and early sediment diagenesis and their subsequent transformation in katagenesis and metamorphism processes. The main features of uranium geochemistry in the exogenous process are considered. Suggested is the genetic classification of uranium exogenous deposits in rocks of sedimentary cover, made with respect to conjugation and various ore-forming productivity of the litogenesis stage. Described are the main combinations of various rock texture and structure properties, characteristic of deposits of genetic classes and groups of the above classification. Eight most frequently occuring textures (lamellar, concretion, oolitic, coagulate, crack, mixed and impregnated) and their types are described and illustrated. Materials of soviet and foreign authors have been used to compile the atlas

High Performance of PEDOT:PSS/n-Si Solar Cells Based on Textured Surface with AgNWs Electrodes

Science.gov (United States)

Jiang, Xiangyu; Zhang, Pengbo; Zhang, Juan; Wang, Jilei; Li, Gaofei; Fang, Xiaohong; Yang, Liyou; Chen, Xiaoyuan

2018-02-01

Hybrid heterojunction solar cells (HHSCs) have gained extensive research and attention due to simple device structure and low-cost technological processes. Here, HHSCs are presented based on a highly transparent conductive polymer poly(3,4ethylenedioxythiophene):poly(styrenesulfonate)(PEDOT:PSS) directly spin-coated on an n-type crystalline silicon with microscale surface textures, which are prepared by traditional chemical etching. We have studied interface properties between PEDOT:PSS and textured n-Si by varying coating conditions. Final power conversion efficiency (PCE) could arrive at 8.54% by these simple solution-based fabrication processes. The high conversion efficiency is attributed to the fully conformal contact between PEDOT:PSS film and textured silicon. Furthermore, the reflectance of the PEDOT:PSS layer on textured surface is analyzed by changing film thickness. In order to improve the performance of the device, silver nanowires were employed as electrodes because of its better optical transmittance and electrical conductivity. The highest PCE of 11.07% was achieved which displayed a 29.6% enhancement compared with traditional silver electrodes. These findings imply that the combination of PEDOT:PSS film and silver nanowire transparent electrodes pave a promising way for realizing high-efficiency and low-cost solar cells.

Tribological Behavior of Laser Textured Hot Stamping Dies

Directory of Open Access Journals (Sweden)

Andre Shihomatsu

2016-01-01

Full Text Available Hot stamping of high strength steels has been continuously developed in the automotive industry to improve mechanical properties and surface quality of stamped components. One of the main challenges faced by researchers and technicians is to improve stamping dies lifetime by reducing the wear caused by high pressures and temperatures present during the process. This paper analyzes the laser texturing of hot stamping dies and discusses how different surfaces textures influence the lubrication and wear mechanisms. To this purpose, experimental tests and numerical simulation were carried out to define the die region to be texturized and to characterize the textured surface topography before and after hot stamping tests with a 3D surface profilometer and scanning electron microscopy. Results showed that laser texturing influences the lubrication at the interface die-hot sheet and improves die lifetime. In this work, the best texture presented dimples with the highest diameter, depth, and spacing, with the surface topography and dimples morphology practically preserved after the hot stamping tests.

Automatic inspection of textured surfaces by support vector machines

Science.gov (United States)

Jahanbin, Sina; Bovik, Alan C.; Pérez, Eduardo; Nair, Dinesh

2009-08-01

Automatic inspection of manufactured products with natural looking textures is a challenging task. Products such as tiles, textile, leather, and lumber project image textures that cannot be modeled as periodic or otherwise regular; therefore, a stochastic modeling of local intensity distribution is required. An inspection system to replace human inspectors should be flexible in detecting flaws such as scratches, cracks, and stains occurring in various shapes and sizes that have never been seen before. A computer vision algorithm is proposed in this paper that extracts local statistical features from grey-level texture images decomposed with wavelet frames into subbands of various orientations and scales. The local features extracted are second order statistics derived from grey-level co-occurrence matrices. Subsequently, a support vector machine (SVM) classifier is trained to learn a general description of normal texture from defect-free samples. This algorithm is implemented in LabVIEW and is capable of processing natural texture images in real-time.

Femtosecond laser surface texturing of titanium as a method to reduce the adhesion of Staphylococcus aureus and biofilm formation

Science.gov (United States)

Cunha, Alexandre; Elie, Anne-Marie; Plawinski, Laurent; Serro, Ana Paula; Botelho do Rego, Ana Maria; Almeida, Amélia; Urdaci, Maria C.; Durrieu, Marie-Christine; Vilar, Rui

2016-01-01

The aim of the present work was to investigate the possibility of using femtosecond laser surface texturing as a method to reduce the colonization of Grade 2 Titanium alloy surfaces by Staphylococcus aureus and the subsequent formation of biofilm. The laser treatments were carried out with a Yb:KYW chirped-pulse-regenerative amplification laser system with a central wavelength of 1030 nm and a pulse duration of 500 fs. Two types of surface textures, consisting of laser-induced periodic surface structures (LIPSS) and nanopillars, were produced. The topography, chemical composition and phase constitution of these surfaces were investigated by atomic force microscopy, scanning electron microscopy, X-ray photoelectron spectroscopy, micro-Raman spectroscopy, and X-ray diffraction. Surface wettability was assessed by the sessile drop method using water and diiodomethane as testing liquids. The response of S. aureus put into contact with the laser treated surfaces in controlled conditions was investigated by epifluorescence microscopy and scanning electron microscopy 48 h after cell seeding. The results achieved show that the laser treatment reduces significantly the bacterial adhesion to the surface as well as biofilm formation as compared to a reference polished surfaces and suggest that femtosecond laser texturing is a simple and promising method for endowing dental and orthopedic titanium implants with antibacterial properties, reducing the risk of implant-associated infections without requiring immobilized antibacterial substances, nanoparticles or coatings.

Combining Spectral Data and a DSM from UAS-Images for Improved Classification of Non-Submerged Aquatic Vegetation

Directory of Open Access Journals (Sweden)

Eva Husson

2017-03-01

Full Text Available Monitoring of aquatic vegetation is an important component in the assessment of freshwater ecosystems. Remote sensing with unmanned aircraft systems (UASs can provide sub-decimetre-resolution aerial images and is a useful tool for detailed vegetation mapping. In a previous study, non-submerged aquatic vegetation was successfully mapped using automated classification of spectral and textural features from a true-colour UAS-orthoimage with 5-cm pixels. In the present study, height data from a digital surface model (DSM created from overlapping UAS-images has been incorporated together with the spectral and textural features from the UAS-orthoimage to test if classification accuracy can be improved further. We studied two levels of thematic detail: (a Growth forms including the classes of water, nymphaeid, and helophyte; and (b dominant taxa including seven vegetation classes. We hypothesized that the incorporation of height data together with spectral and textural features would increase classification accuracy as compared to using spectral and textural features alone, at both levels of thematic detail. We tested our hypothesis at five test sites (100 m × 100 m each with varying vegetation complexity and image quality using automated object-based image analysis in combination with Random Forest classification. Overall accuracy at each of the five test sites ranged from 78% to 87% at the growth-form level and from 66% to 85% at the dominant-taxon level. In comparison to using spectral and textural features alone, the inclusion of height data increased the overall accuracy significantly by 4%–21% for growth-forms and 3%–30% for dominant taxa. The biggest improvement gained by adding height data was observed at the test site with the most complex vegetation. Height data derived from UAS-images has a large potential to efficiently increase the accuracy of automated classification of non-submerged aquatic vegetation, indicating good possibilities

Software measurement standards for areal surface texture parameters: part 2—comparison of software

International Nuclear Information System (INIS)

Harris, P M; Smith, I M; Giusca, C; Leach, R K; Wang, C

2012-01-01

A companion paper in this issue describes reference software for the evaluation of areal surface texture parameters, focusing on the definitions of the parameters and giving details of the numerical algorithms employed in the software to implement those definitions. The reference software is used as a benchmark against which software in a measuring instrument can be compared. A data set is used as input to both the software under test and the reference software, and the results delivered by the software under test are compared with those provided by the reference software. This paper presents a comparison of the results returned by the reference software with those reported by proprietary software for surface texture measurement. Differences between the results can be used to identify where algorithms and software for evaluating the parameters differ. They might also be helpful in identifying where parameters are not sufficiently well-defined in standards. (paper)

Texturing in titanium grade 2 surface irradiate with ultrashort pulse laser; Texturizacao em superficies de titanio grau 2 irradiadas com laser com pulsos ultracurtos

Energy Technology Data Exchange (ETDEWEB)

Nogueira, Alessandro Francelino

2015-07-01

The texturing laser micromachining is an important alternative to improve the bonding adhesion between composites and titanium, which are applied to structural components in the aerospace industry. The texturing running on titanium plates is due to the fact that the preferred joining technique for many composite materials is the adhesive bonding. In this work, titanium plates were texturized using laser ultrashort pulses temporal widths of femtoseconds. This process resulted in minimal heat transfer to the material, avoiding deformation of the titanium plate surface as well as the formation of resolidified material in the ablated region. These drawbacks have occurred with the use of nanoseconds pulses. Were performed three types of texturing using laser with femtosecond pulses, with variations in the distances between the machined lines. The analysis of the obtained surfaces found that the wettability increases when there is the increased distance between the texturing lines. Advancing in the analysis by optical profilometry of textured surfaces was observed that there is substantial increase in the volume available for penetration of structural adhesive when the distances between the textured lines are diminished. In tensile tests conducted it was observed that there is an increase in shear strength of the adhesive joint by reducing the distance between the textured lines. (author)

Noncontact Surface Roughness Estimation Using 2D Complex Wavelet Enhanced ResNet for Intelligent Evaluation of Milled Metal Surface Quality

Directory of Open Access Journals (Sweden)

Weifang Sun

2018-03-01

Full Text Available Machined surfaces are rough from a microscopic perspective no matter how finely they are finished. Surface roughness is an important factor to consider during production quality control. Using modern techniques, surface roughness measurements are beneficial for improving machining quality. With optical imaging of machined surfaces as input, a convolutional neural network (CNN can be utilized as an effective way to characterize hierarchical features without prior knowledge. In this paper, a novel method based on CNN is proposed for making intelligent surface roughness identifications. The technical scheme incorporates there elements: texture skew correction, image filtering, and intelligent neural network learning. Firstly, a texture skew correction algorithm, based on an improved Sobel operator and Hough transform, is applied such that surface texture directions can be adjusted. Secondly, two-dimensional (2D dual tree complex wavelet transform (DTCWT is employed to retrieve surface topology information, which is more effective for feature classifications. In addition, residual network (ResNet is utilized to ensure automatic recognition of the filtered texture features. The proposed method has verified its feasibility as well as its effectiveness in actual surface roughness estimation experiments using the material of spheroidal graphite cast iron 500-7 in an agricultural machinery manufacturing company. Testing results demonstrate the proposed method has achieved high-precision surface roughness estimation.

Classification of Textures Using Filter Based Local Feature Extraction

Directory of Open Access Journals (Sweden)

Bocekci Veysel Gokhan

2016-01-01

Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

GLOBAL LAND COVER CLASSIFICATION USING MODIS SURFACE REFLECTANCE PROSUCTS

Directory of Open Access Journals (Sweden)

K. Fukue

2016-06-01

Full Text Available The objective of this study is to develop high accuracy land cover classification algorithm for Global scale by using multi-temporal MODIS land reflectance products. In this study, time-domain co-occurrence matrix was introduced as a classification feature which provides time-series signature of land covers. Further, the non-parametric minimum distance classifier was introduced for timedomain co-occurrence matrix, which performs multi-dimensional pattern matching for time-domain co-occurrence matrices of a classification target pixel and each classification classes. The global land cover classification experiments have been conducted by applying the proposed classification method using 46 multi-temporal(in one year SR(Surface Reflectance and NBAR(Nadir BRDF-Adjusted Reflectance products, respectively. IGBP 17 land cover categories were used in our classification experiments. As the results, SR and NBAR products showed similar classification accuracy of 99%.

Phosphorous gettering in acidic textured multicrystalline solar cells

Energy Technology Data Exchange (ETDEWEB)

Montesdeoca-Santana, A. [Departamento de Fisica Basica, Universidad de La Laguna (ULL), Avenida Astrofisico Francisco Sanchez 2, 38206 La Laguna, S/C de Tenerife (Spain); Fraunhofer Institut fuer Solare Energiesysteme ISE, Laboratory and Servicecenter Gelsenkirchen, Auf der Reihe 2, 45884 Gelsenkirchen (Germany); Jimenez-Rodriguez, E.; Diaz-Herrera, B.; Hernandez-Rodriguez, C. [Departamento de Fisica Basica, Universidad de La Laguna (ULL), Avenida Astrofisico Francisco Sanchez 2, 38206 La Laguna, S/C de Tenerife (Spain); Gonzalez-Diaz, B. [Departamento de Fisica Basica, Universidad de La Laguna (ULL), Avenida Astrofisico Francisco Sanchez 2, 38206 La Laguna, S/C de Tenerife (Spain); Departamento de Energia Fotovoltaica, Instituto Tecnologico y de Energias Renovables. Poligono Industrial de Granadilla s/n, 38600 San Isidro-Granadilla de Abona, S/C de Tenerife (Spain); Rinio, M.; Borchert, D. [Fraunhofer Institut fuer Solare Energiesysteme ISE, Laboratory and Servicecenter Gelsenkirchen, Auf der Reihe 2, 45884 Gelsenkirchen (Germany); Guerrero-Lemus, R. [Departamento de Fisica Basica, Universidad de La Laguna (ULL), Avenida Astrofisico Francisco Sanchez 2, 38206 La Laguna, S/C de Tenerife (Spain); Fundacion de Estudios de Economia Aplicada, Catedra Focus-Abengoa, Jorge Juan 46, 28001 Madrid (Spain)

2011-03-15

The influence of phosphorus gettering is studied in this work applied to an acidic textured multicrystalline silicon substrate. The texturization was achieved with an HF/HNO{sub 3} solution leading to nanostructures on the silicon surface. It has been demonstrated in previous works that this textured surface decreases the reflectance on the solar cell and increases the surface area improving the photon collection and enhancing the short circuit current. The present study investigates the effect on the minority carrier lifetime of the phosphorous diffusion when it is carried out on this textured surface. The lifetime is measured by means microwave photoconductance decay and quasi steady state phototoconductance devices. The diffused textured wafers are used to fabricate solar cells and their electrical parameters are analyzed. (copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Classification Scheme for Diverse Sedimentary and Igneous Rocks Encountered by MSL in Gale Crater

Science.gov (United States)

Schmidt, M. E.; Mangold, N.; Fisk, M.; Forni, O.; McLennan, S.; Ming, D. W.; Sumner, D.; Sautter, V.; Williams, A. J.; Gellert, R.

2015-01-01

The Curiosity Rover landed in a lithologically and geochemically diverse region of Mars. We present a recommended rock classification framework based on terrestrial schemes, and adapted for the imaging and analytical capabilities of MSL as well as for rock types distinctive to Mars (e.g., high Fe sediments). After interpreting rock origin from textures, i.e., sedimentary (clastic, bedded), igneous (porphyritic, glassy), or unknown, the overall classification procedure (Fig 1) involves: (1) the characterization of rock type according to grain size and texture; (2) the assignment of geochemical modifiers according to Figs 3 and 4; and if applicable, in depth study of (3) mineralogy and (4) geologic/stratigraphic context. Sedimentary rock types are assigned by measuring grains in the best available resolution image (Table 1) and classifying according to the coarsest resolvable grains as conglomerate/breccia, (coarse, medium, or fine) sandstone, silt-stone, or mudstone. If grains are not resolvable in MAHLI images, grains in the rock are assumed to be silt sized or smaller than surface dust particles. Rocks with low color contrast contrast between grains (e.g., Dismal Lakes, sol 304) are classified according to minimum size of apparent grains from surface roughness or shadows outlining apparent grains. Igneous rocks are described as intrusive or extrusive depending on crystal size and fabric. Igneous textures may be described as granular, porphyritic, phaneritic, aphyric, or glassy depending on crystal size. Further descriptors may include terms such as vesicular or cumulate textures.

TEXTURAL DESCRIPTORS FOR MULTIPHASIC ORE PARTICLES

Directory of Open Access Journals (Sweden)

Laura Pérez-Barnuevo

2012-11-01

Full Text Available Monitoring of mineral processing circuits by means of particle liberation analysis through quantitative image analysis has become a routine technique within the last decades. Usually, liberation indices are computed as weight proportions, which is not informative enough when complex texture ores are treated by flotation. In these cases, liberation has to be computed as phase surface exposed to reactants, and textural relationships between minerals have to be characterized to determine the possibility of increasing exposure. In this paper, some indices to achieve a complete texture characterization have been developed in terms of 2D phase contact and mineral surfaces exposure. Indices suggested by other authors are also compared. The response of this set of parameters against textural changes has been explored on simple synthetic textures ranging from single to multiple inclusions and single to multiple veins and their ability to discriminate between different textural features is analyzed over real mineral particles with known internal structure.

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

Science.gov (United States)

Cho, Nam-Hoon; Choi, Heung-Kook

2014-01-01

One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM) and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system. PMID:25371701

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

Directory of Open Access Journals (Sweden)

Tae-Yun Kim

2014-01-01

Full Text Available One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system.

Efficient rolling texture predictions and texture-sensitive thermomechanical properties of α-uranium foils

Science.gov (United States)

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.; Knezevic, Marko; Garlea, Elena; Agnew, Sean R.

2017-11-01

Finite element (FE) analysis was used to simulate the strain history of an α-uranium foil during cold straight-rolling, with the sheet modeled as an isotropic elastoplastic continuum. The resulting strain history was then used as input for a viscoplastic self-consistent (VPSC) polycrystal plasticity model to simulate crystallographic texture evolution. Mid-plane textures predicted via the combined FE→VPSC approach show alignment of the (010) poles along the rolling direction (RD), and the (001) poles along the normal direction (ND) with a symmetric splitting along RD. The surface texture is similar to that of the mid-plane, but with a shear-induced asymmetry that favors one of the RD split features of the (001) pole figure. Both the mid-plane and surface textures predicted by the FE→VPSC approach agree with published experimental results for cold straight-rolled α-uranium plates, as well as predictions made by a more computationally intensive full-field crystal plasticity based finite element model. α-uranium foils produced by cold-rolling must typically undergo a recrystallization anneal to restore ductility prior to their final application, resulting in significant texture evolution from the cold-rolled plate deformation texture. Using the texture measured from a foil in the final recrystallized state, coefficients of thermal expansion and the elastic stiffness tensors were calculated using a thermo-elastic self-consistent model, and the anisotropic yield loci and flow curves along the RD, TD, and ND were predicted using the VPSC code.

Differential topology of complex surfaces elliptic surfaces with p g=1 smooth classification

CERN Document Server

Morgan, John W

1993-01-01

This book is about the smooth classification of a certain class of algebraicsurfaces, namely regular elliptic surfaces of geometric genus one, i.e. elliptic surfaces with b1 = 0 and b2+ = 3. The authors give a complete classification of these surfaces up to diffeomorphism. They achieve this result by partially computing one of Donalson's polynomial invariants. The computation is carried out using techniques from algebraic geometry. In these computations both thebasic facts about the Donaldson invariants and the relationship of the moduli space of ASD connections with the moduli space of stable bundles are assumed known. Some familiarity with the basic facts of the theory of moduliof sheaves and bundles on a surface is also assumed. This work gives a good and fairly comprehensive indication of how the methods of algebraic geometry can be used to compute Donaldson invariants.

Measurement uncertainty associated with chromatic confocal profilometry for 3D surface texture characterization of natural human enamel.

Science.gov (United States)

Mullan, F; Bartlett, D; Austin, R S

2017-06-01

To investigate the measurement performance of a chromatic confocal profilometer for quantification of surface texture of natural human enamel in vitro. Contributions to the measurement uncertainty from all potential sources of measurement error using a chromatic confocal profilometer and surface metrology software were quantified using a series of surface metrology calibration artifacts and pre-worn enamel samples. The 3D surface texture analysis protocol was optimized across 0.04mm 2 of natural and unpolished enamel undergoing dietary acid erosion (pH 3.2, titratable acidity 41.3mmolOH/L). Flatness deviations due to the x, y stage mechanical movement were the major contribution to the measurement uncertainty; with maximum Sz flatness errors of 0.49μm. Whereas measurement noise; non-linearity's in x, y, z and enamel sample dimensional instability contributed minimal errors. The measurement errors were propagated into an uncertainty budget following a Type B uncertainty evaluation in order to calculate the Standard Combined Uncertainty (u c ), which was ±0.28μm. Statistically significant increases in the median (IQR) roughness (Sa) of the polished samples occurred after 15 (+0.17 (0.13)μm), 30 (+0.12 (0.09)μm) and 45 (+0.18 (0.15)μm) min of erosion (Pchromatic confocal profilometry was from flatness deviations however by optimizing measurement protocols the profilometer successfully characterized surface texture changes in enamel from erosive wear in vitro. Copyright © 2017 The Academy of Dental Materials. All rights reserved.

Contact splitting and the effect of dimple depth on static friction of textured surfaces.

Science.gov (United States)

Greiner, Christian; Schäfer, Michael; Popp, Uwe; Gumbsch, Peter

2014-06-11

The morphological texturing of surfaces has demonstrated its high potential to maximize adhesion as well as to reduce friction and wear. A key to understanding such phenomena is a principle known as contact splitting. Here, we extend this concept to the static friction behavior of dimpled surfaces. Our results indicate that contact splitting does exist for such structures and that with certain dimple sizes and depths static friction values significantly exceeding those of untextured surfaces can be obtained. These results can be applied to all surfaces where friction forces are to be tuned, from nanoelectromechanical systems up to combustion engines.

The natural weathering of staurolite: crystal-surface textures, relative stability, and the rate-determining step

Science.gov (United States)

Michael A. Velbel; Charles L. Basso; Michael J. Zieg

1996-01-01

Mineral surface-textures on naturally weathered crystals of staurolite [monoclinic, pseudo-orthorhombic; Fe4Al18Si8O46(OH)2] indicate that staurolite weathering is generally interface-limited. Etch pits on naturally weathered staurolites are disk-shaped,...

[A scanning electron microscopy study of the surface of porous-textured breast implants and their capsules. Description of the "velcro" effect of porous-textured breast prostheses].

Science.gov (United States)

Danino, A; Rocher, F; Blanchet-Bardon, C; Revol, M; Servant, J M

2001-02-01

The efficacy of breast prosthesis texturing in the prevention of capsular contracture has been established for about 20 years. This successful procedure has led to the development and marketing of a number of different models. In the present study, four porous-textured breast prostheses have been examined: the Arion monoblock implant, the CUI (McGahn), the Biocell (Mcgahn), and the Sebbin LS21. Scanning electron microscopic (SEM) investigation of the implant surfaces of the different prostheses was carried out on new samples received from the manufacturers. During a prospective study on eight patients, capsule samples corresponding to the four above-mentioned prostheses were taken to determine whether a secondary intervention was necessary for correction of asymmetry or malpositioning. These samples were analyzed by SEM to investigate whether there could be a correlation between prosthesis texturing and the aspect of the corresponding capsules. Significant ultrastructural differences were found between the various prostheses examined: the results showed that only the CUI and Biocell prostheses presented a mirror image of the capsule texturing, with a correspondence between the depressions on the prosthesis and the contacts on the capsule. This finding seems to be linked to the existence of a critical size for the pores that constitute the implant surface. This observation led to the hypothesis of an adhesive "velcro" effect between the prosthesis and its capsule. Although the latter may not be directly linked to the prevention of capsular contracture it can, however, have a major effect on implant stabilization in cases of primary breast reconstruction and in possible secondary adjustments of asymmetry and malpositioning.

Effects of surface roughness, texture and polymer degradation on cathodic delamination of epoxy coated steel samples

International Nuclear Information System (INIS)

Khun, N.W.; Frankel, G.S.

2013-01-01

Highlights: ► Cathodic delamination of epoxy coated steel samples was studied using SKP. ► Delamination of the coating decreased with increased substrate surface roughness. ► Delamination of the coating was faster on the substrate with parallel surface scratches. ► Delamination of the coating exposed to weathering conditions increased with prolonged exposure. - Abstract: The Scanning Kelvin Probe (SKP) technique was used to investigate the effects of surface roughness, texture and polymer degradation on cathodic delamination of epoxy coated steel. The cathodic delamination rate of the epoxy coatings dramatically decreased with increased surface roughness of the underlying steel substrate. The surface texture of the steel substrates also had a significant effect in that samples with parallel abrasion lines exhibiting faster cathodic delamination in the direction of the lines compared to the direction perpendicular to the lines. The cathodic delamination kinetics of epoxy coatings previously exposed to weathering conditions increased with prolonged exposure due to pronounced polymer degradation. SEM observation confirmed that the cyclic exposure to UV radiation and water condensation caused severe deterioration in the polymer structures with surface cracking and erosion. The SKP results clearly showed that the cathodic delamination of the epoxy coatings was significantly influenced by the surface features of the underlying steel substrates and the degradation of the coatings.

Application of CT texture analysis in predicting histopathological characteristics of gastric cancers

International Nuclear Information System (INIS)

Liu, Shunli; Liu, Song; Ji, Changfeng; Zheng, Huanhuan; Pan, Xia; Zhang, Yujuan; He, Jian; Zhou, Zhengyang; Guan, Wenxian; Chen, Ling; Guan, Yue; Li, Weifeng; Ge, Yun

2017-01-01

To explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers. Preoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were retrospectively reviewed. CT texture analysis generated: (1) mean attenuation, (2) standard deviation, (3) max frequency, (4) mode, (5) minimum attenuation, (6) maximum attenuation, (7) the fifth, 10th, 25th, 50th, 75th and 90th percentiles, and (8) entropy. Correlations between CT texture parameters and histopathological features were analysed. Mean attenuation, maximum attenuation, all percentiles and mode derived from portal venous CT images correlated significantly with differentiation degree and Lauren classification of gastric cancers (r, -0.231 ∝-0.324, 0.228 ∝ 0.321, respectively). Standard deviation and entropy derived from arterial CT images also correlated significantly with Lauren classification of gastric cancers (r = -0.265, -0.222, respectively). In arterial phase analysis, standard deviation and entropy were significantly lower in gastric cancers with than those without vascular invasion; however, minimum attenuation was significantly higher in gastric cancers with than those without vascular invasion. CT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers. (orig.)

Application of CT texture analysis in predicting histopathological characteristics of gastric cancers

Energy Technology Data Exchange (ETDEWEB)

Liu, Shunli; Liu, Song; Ji, Changfeng; Zheng, Huanhuan; Pan, Xia; Zhang, Yujuan; He, Jian; Zhou, Zhengyang [The Affiliated Hospital of Nanjing University Medical School, Department of Radiology, Nanjing Drum Tower Hospital, Nanjing, Jiangsu Province (China); Guan, Wenxian [The Affiliated Hospital of Nanjing University Medical School, Department of Gastrointestinal Surgery, Nanjing Drum Tower Hospital, Nanjing (China); Chen, Ling [The Affiliated Hospital of Nanjing University Medical School, Department of Pathology, Nanjing Drum Tower Hospital, Nanjing, Jiangsu Province (China); Guan, Yue; Li, Weifeng; Ge, Yun [Nanjing University, School of Electronic Science and Engineering, Nanjing (China)

2017-12-15

To explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers. Preoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were retrospectively reviewed. CT texture analysis generated: (1) mean attenuation, (2) standard deviation, (3) max frequency, (4) mode, (5) minimum attenuation, (6) maximum attenuation, (7) the fifth, 10th, 25th, 50th, 75th and 90th percentiles, and (8) entropy. Correlations between CT texture parameters and histopathological features were analysed. Mean attenuation, maximum attenuation, all percentiles and mode derived from portal venous CT images correlated significantly with differentiation degree and Lauren classification of gastric cancers (r, -0.231 ∝-0.324, 0.228 ∝ 0.321, respectively). Standard deviation and entropy derived from arterial CT images also correlated significantly with Lauren classification of gastric cancers (r = -0.265, -0.222, respectively). In arterial phase analysis, standard deviation and entropy were significantly lower in gastric cancers with than those without vascular invasion; however, minimum attenuation was significantly higher in gastric cancers with than those without vascular invasion. CT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers. (orig.)

Classification of high resolution satellite images

OpenAIRE

Karlsson, Anders

2003-01-01

In this thesis the Support Vector Machine (SVM)is applied on classification of high resolution satellite images. Sveral different measures for classification, including texture mesasures, 1st order statistics, and simple contextual information were evaluated. Additionnally, the image was segmented, using an enhanced watershed method, in order to improve the classification accuracy.

Surface texture of single-crystal silicon oxidized under a thin V{sub 2}O{sub 5} layer

Energy Technology Data Exchange (ETDEWEB)

Nikitin, S. E., E-mail: nikitin@mail.ioffe.ru; Verbitskiy, V. N.; Nashchekin, A. V.; Trapeznikova, I. N.; Bobyl, A. V.; Terukova, E. E. [Russian Academy of Sciences, Ioffe Physical–Technical Institute (Russian Federation)

2017-01-15

The process of surface texturing of single-crystal silicon oxidized under a V{sub 2}O{sub 5} layer is studied. Intense silicon oxidation at the Si–V{sub 2}O{sub 5} interface begins at a temperature of 903 K which is 200 K below than upon silicon thermal oxidation in an oxygen atmosphere. A silicon dioxide layer 30–50 nm thick with SiO{sub 2} inclusions in silicon depth up to 400 nm is formed at the V{sub 2}O{sub 5}–Si interface. The diffusion coefficient of atomic oxygen through the silicon-dioxide layer at 903 K is determined (D ≥ 2 × 10{sup –15} cm{sup 2} s{sup –1}). A model of low-temperature silicon oxidation, based on atomic oxygen diffusion from V{sub 2}O{sub 5} through the SiO{sub 2} layer to silicon, and SiO{sub x} precipitate formation in silicon is proposed. After removing the V{sub 2}O{sub 5} and silicon-dioxide layers, texture is formed on the silicon surface, which intensely scatters light in the wavelength range of 300–550 nm and is important in the texturing of the front and rear surfaces of solar cells.

Classification d'images RSO polarimétriques à haute résolution spatiale sur site urbain.

OpenAIRE

Soheili Majd , Maryam

2014-01-01

In this research, our aim is to assess the potential of a one single look high spatial resolution polarimetric radar image for the classification of urban areas. For that purpose, we concentrate on classes corresponding to different kinds of roofs, objects and ground surfaces.At first, we propose a uni-variate statistical analysis of polarimetric and texture attributes, that can be used in a classification algorithm. We perform a statistical analysis of descriptors and show that the Fisher di...

Electrochemically grown rough-textured nanowires

International Nuclear Information System (INIS)

Tyagi, Pawan; Postetter, David; Saragnese, Daniel; Papadakis, Stergios J.; Gracias, David H.

2010-01-01

Nanowires with a rough surface texture show unusual electronic, optical, and chemical properties; however, there are only a few existing methods for producing these nanowires. Here, we describe two methods for growing both free standing and lithographically patterned gold (Au) nanowires with a rough surface texture. The first strategy is based on the deposition of nanowires from a silver (Ag)-Au plating solution mixture that precipitates an Ag-Au cyanide complex during electrodeposition at low current densities. This complex disperses in the plating solution, thereby altering the nanowire growth to yield a rough surface texture. These nanowires are mass produced in alumina membranes. The second strategy produces long and rough Au nanowires on lithographically patternable nickel edge templates with corrugations formed by partial etching. These rough nanowires can be easily arrayed and integrated with microscale devices.

Microstructure and mechanical characteristics of laser coating-texturing alloying dimples

International Nuclear Information System (INIS)

Wan Daping; Chen Bingkui; Shao Yimin; Wang Shilong; Hu Dejin

2008-01-01

A novel laser coating-texturing (LCT) technique was proposed to achieve appropriate surface topographies and frictional behaviour. The LCT process was realized by applying laser pulses at very high repetition rate to produce innumerable micro-craters with required shape profile on the surface of the workpiece. Moreover, surface alloying of the dimples was carried out by melting submicron WC-TiC-Co alloy powder on the substrates. Morphology and microstructures of the texturing layers were characterised using optical microscopy (OM), scanning electron microscopy (SEM), and X-ray diffraction (XRD). Mechanical properties of the textured samples were evaluated by abrasive resistance tests and microhardness measurement. Experimental results show that good fusion bonding between the texturing layers and the substrate has been formed, and the texturing layers are mainly composed of dense and hard fine-grained structures. The abrasive wear resistance of the laser coating-textured surface was 10 times higher than that of the substrates. The average surface microhardness values were as high as 830 HV.

Please Don't Move-Evaluating Motion Artifact From Peripheral Quantitative Computed Tomography Scans Using Textural Features.

Science.gov (United States)

Rantalainen, Timo; Chivers, Paola; Beck, Belinda R; Robertson, Sam; Hart, Nicolas H; Nimphius, Sophia; Weeks, Benjamin K; McIntyre, Fleur; Hands, Beth; Siafarikas, Aris

Most imaging methods, including peripheral quantitative computed tomography (pQCT), are susceptible to motion artifacts particularly in fidgety pediatric populations. Methods currently used to address motion artifact include manual screening (visual inspection) and objective assessments of the scans. However, previously reported objective methods either cannot be applied on the reconstructed image or have not been tested for distal bone sites. Therefore, the purpose of the present study was to develop and validate motion artifact classifiers to quantify motion artifact in pQCT scans. Whether textural features could provide adequate motion artifact classification performance in 2 adolescent datasets with pQCT scans from tibial and radial diaphyses and epiphyses was tested. The first dataset was split into training (66% of sample) and validation (33% of sample) datasets. Visual classification was used as the ground truth. Moderate to substantial classification performance (J48 classifier, kappa coefficients from 0.57 to 0.80) was observed in the validation dataset with the novel texture-based classifier. In applying the same classifier to the second cross-sectional dataset, a slight-to-fair (κ = 0.01-0.39) classification performance was observed. Overall, this novel textural analysis-based classifier provided a moderate-to-substantial classification of motion artifact when the classifier was specifically trained for the measurement device and population. Classification based on textural features may be used to prescreen obviously acceptable and unacceptable scans, with a subsequent human-operated visual classification of any remaining scans. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

Basic Hand Gestures Classification Based on Surface Electromyography

Directory of Open Access Journals (Sweden)

Aleksander Palkowski

2016-01-01

Full Text Available This paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average classification rate of 98.12% has been achieved for the proposed method.

Learning features for tissue classification with the classification restricted Boltzmann machine

DEFF Research Database (Denmark)

van Tulder, Gijs; de Bruijne, Marleen

2014-01-01

Performance of automated tissue classification in medical imaging depends on the choice of descriptive features. In this paper, we show how restricted Boltzmann machines (RBMs) can be used to learn features that are especially suited for texture-based tissue classification. We introduce the convo...... outperform conventional RBM-based feature learning, which is unsupervised and uses only a generative learning objective, as well as often-used filter banks. We show that a mixture of generative and discriminative learning can produce filters that give a higher classification accuracy....

Sea ice classification using dual polarization SAR data

International Nuclear Information System (INIS)

Huiying, Liu; Huadong, Guo; Lu, Zhang

2014-01-01

Sea ice is an indicator of climate change and also a threat to the navigation security of ships. Polarimetric SAR images are useful in the sea ice detection and classification. In this paper, backscattering coefficients and texture features derived from dual polarization SAR images are used for sea ice classification. Firstly, the HH image is recalculated based on the angular dependences of sea ice types. Then the effective gray level co-occurrence matrix (GLCM) texture features are selected for the support vector machine (SVM) classification. In the end, because sea ice concentration can provide a better separation of pancake ice from old ice, it is used to improve the SVM result. This method provides a good classification result, compared with the sea ice chart from CIS

Development of natively textured surface hydrogenated Ga-doped ZnO-TCO thin films for solar cells via magnetron sputtering

International Nuclear Information System (INIS)

Wang, Fei; Chen, Xin-liang; Geng, Xin-hua; Zhang, De-kun; Wei, Chang-chun; Huang, Qian; Zhang, Xiao-dan; Zhao, Ying

2012-01-01

Highlights: ► Natively textured surface hydrogenated gallium-doped zinc oxide (HGZO) thin films have been deposited via magnetron sputtering on glass substrates. ► The directly deposited HGZO thin films present rough crater-type surface morphology. ► Typical HGZO thin film exhibits a high electron mobility of 41.3 cm 2 /V s and a relative low sheet resistance of ∼7.0 Ω. ► These HGZO thin films have high optical transmittances in the visible and near infrared region (∼380–1100 nm). ► A gradient H 2 growth method for fabricating HGZO thin films has been proposed in magnetron sputtering process. - Abstract: The main purposes are to obtain high quality transparent conductive oxide (TCO) based on zinc oxide (ZnO) thin films with high optical transparency in the visible and near infrared spectral range, high electrical conductivity and good light-scattering capability to enhance the path of the light inside the Si-based thin film solar cells. Natively textured surface hydrogenated gallium-doped ZnO (HGZO) thin films have been deposited via pulsed direct current (DC) magnetron sputtering on glass substrates at a substrate temperature of 553 K. These natively textured HGZO thin films exhibit high optical transmittance (over 80%) in the visible and near infrared region (λ = 380–1100 nm) and excellent electrical properties. The optimized HGZO thin film with crater-type textured surface obtained at the hydrogen flow rate of ∼2.0 sccm exhibits a high electron mobility of 41.3 cm 2 /V s and a relatively low sheet resistance of ∼7.0 Ω. The influences of hydrogen flow rates on the surface morphology, electrical and optical properties of HGZO thin films were investigated in detail. In addition, we put forward a method of gradient H 2 growth technique for fabricating HGZO thin films so as to obtain rough surface structure with good light-scattering capability and high electrical conductivity. “Crater-like” surface feature size and optical transmittance

AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

Directory of Open Access Journals (Sweden)

P. Kupidura

2016-06-01

Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

Natively textured surface hydrogenated gallium-doped zinc oxide transparent conductive thin films with buffer layers for solar cells

Energy Technology Data Exchange (ETDEWEB)

Chen, Xin-liang, E-mail: cxlruzhou@163.com; Wang, Fei; Geng, Xin-hua; Huang, Qian; Zhao, Ying; Zhang, Xiao-dan

2013-09-02

Natively textured surface hydrogenated gallium-doped zinc oxide (HGZO) thin films have been deposited via magnetron sputtering on glass substrates. These natively textured HGZO thin films exhibit rough pyramid-like textured surface, high optical transmittances in the visible and near infrared region and excellent electrical properties. The experiment results indicate that tungsten-doped indium oxide (In{sub 2}O{sub 3}:W, IWO) buffer layers can effectively improve the surface roughness and enhance the light scattering ability of HGZO thin films. The root-mean-square roughness of HGZO, IWO (10 nm)/HGZO and IWO (30 nm)/HGZO thin films are 28, 44 and 47 nm, respectively. The haze values at the wavelength of 550 nm increase from 7.0% of HGZO thin film without buffer layer to 18.37% of IWO (10 nm)/HGZO thin film. The optimized IWO (10 nm)/HGZO exhibits a high optical transmittance of 82.18% in the visible and near infrared region (λ ∼ 400–1100 nm) and excellent electrical properties with a relatively low sheet resistance of 3.6 Ω/□ and the resistivity of 6.21 × 10{sup −4} Ωcm. - Highlights: • Textured hydrogenated gallium-doped zinc oxide (HGZO) films were developed. • Tungsten-doped indium oxide (IWO) buffer layers were applied for the HGZO films. • Light-scattering ability of the HGZO films can be improved through buffer layers. • Low sheet resistance and high haze were obtained for the IWO(10 nm)/HGZO film. • The IWO/HGZO films are promising transparent conductive layers for solar cells.

Switchable Super-Hydrophilic/Hydrophobic Indium Tin Oxide (ITO) Film Surfaces on Reactive Ion Etching (RIE) Textured Si Wafer.

Science.gov (United States)

Kim, Hwa-Min; Litao, Yao; Kim, Bonghwan

2015-11-01

We have developed a surface texturing process for pyramidal surface features along with an indium tin oxide (ITO) coating process to fabricate super-hydrophilic conductive surfaces. The contact angle of a water droplet was less than 5 degrees, which means that an extremely high wettability is achievable on super-hydrophilic surfaces. We have also fabricated a super-hydrophobic conductive surface using an additional coating of polytetrafluoroethylene (PTFE) on the ITO layer coated on the textured Si surface; the ITO and PTFE films were deposited by using a conventional sputtering method. We found that a super-hydrophilic conductive surface is produced by ITO coated on the pyramidal Si surface (ITO/Si), with contact angles of approximately 0 degrees and a resistivity of 3 x 10(-4) Ω x cm. These values are highly dependent on the substrate temperature during the sputtering process. We also found that the super-hydrophobic conductive surface produced by the additional coating of PTFE on the pyramidal Si surface with an ITO layer (PTFE/ITO/Si) has a contact angle of almost 160 degrees and a resistivity of 3 x 10(-4) Ω x cm, with a reflectance lower than 9%. Therefore, these processes can be used to fabricate multifunctional features of ITO films for switchable super-hydrophilic and super-hydrophobic surfaces.

Gender classification system in uncontrolled environments

Science.gov (United States)

Zeng, Pingping; Zhang, Yu-Jin; Duan, Fei

2011-01-01

Most face analysis systems available today perform mainly on restricted databases of images in terms of size, age, illumination. In addition, it is frequently assumed that all images are frontal and unconcealed. Actually, in a non-guided real-time supervision, the face pictures taken may often be partially covered and with head rotation less or more. In this paper, a special system supposed to be used in real-time surveillance with un-calibrated camera and non-guided photography is described. It mainly consists of five parts: face detection, non-face filtering, best-angle face selection, texture normalization, and gender classification. Emphases are focused on non-face filtering and best-angle face selection parts as well as texture normalization. Best-angle faces are figured out by PCA reconstruction, which equals to an implicit face alignment and results in a huge increase of the accuracy for gender classification. Dynamic skin model and a masked PCA reconstruction algorithm are applied to filter out faces detected in error. In order to fully include facial-texture and shape-outline features, a hybrid feature that is a combination of Gabor wavelet and PHoG (pyramid histogram of gradients) was proposed to equitable inner texture and outer contour. Comparative study on the effects of different non-face filtering and texture masking methods in the context of gender classification by SVM is reported through experiments on a set of UT (a company name) face images, a large number of internet images and CAS (Chinese Academy of Sciences) face database. Some encouraging results are obtained.

Different approaches for the texture classification of a remote sensing image bank

Science.gov (United States)

Durand, Philippe; Brunet, Gerard; Ghorbanzadeh, Dariush; Jaupi, Luan

2018-04-01

In this paper, we summarize and compare two different approaches used by the authors, to classify different natural textures. The first approach, which is simple and inexpensive in computing time, uses a data bank image and an expert system able to classify different textures from a number of rules established by discipline specialists. The second method uses the same database and a neural networks approach.

Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

Czech Academy of Sciences Publication Activity Database

Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

2009-01-01

Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

Automatic Texture Optimization for 3D Urban Reconstruction

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LI Ming

2017-03-01

Full Text Available In order to solve the problem of texture optimization in 3D city reconstruction by using multi-lens oblique images, the paper presents a method of seamless texture model reconstruction. At first, it corrects the radiation information of images by camera response functions and image dark channel. Then, according to the corresponding relevance between terrain triangular mesh surface model to image, implements occlusion detection by sparse triangulation method, and establishes the triangles' texture list of visible. Finally, combines with triangles' topology relationship in 3D triangular mesh surface model and means and variances of image, constructs a graph-cuts-based texture optimization algorithm under the framework of MRF(Markov random filed, to solve the discrete label problem of texture optimization selection and clustering, ensures the consistency of the adjacent triangles in texture mapping, achieves the seamless texture reconstruction of city. The experimental results verify the validity and superiority of our proposed method.

Evaluation of penicylinders used in disinfectant testing: bacterial attachment and surface texture.

Science.gov (United States)

Cole, E C; Rutala, W A; Carson, J L

1987-01-01

Two possible deficiencies in the AOAC use-dilution method for registration of chemical disinfectants by the Environmental Protection Agency are examined: (1) the physical disparities among brands of penicylinders and (2) the variability of bacterial numbers on penicylinders depending upon test strain and penicylinder surface texture. Textural differences of 2 brands of stainless steel penicylinders, one brand of porcelain, and one brand of glass were assessed by scanning electron microscopy. A considerable variation in smoothness of both inner and outer surfaces of stainless steel and porcelain penicylinders was observed. Glass penicylinders were very smooth. Numbers of bacteria attached to a penicylinder were assessed by vortexing the penicylinders 30 s at No. 4 after using the AOAC method of bacterial inoculation and drying 40 min at 37 degrees C. With this methodology, stainless steel carriers retained the 3 AOAC-recommended bacterial test strains differentially: ca 10(7) for Pseudomonas aeruginosa, 5 X 10(6) for Staphylococcus aureus, and 10(6) for Salmonella choleraesuis; glass retained 10(6)-10(7) organisms of all 3 test strains; porcelain retained about that amount of S. aureus but 10(5)-10(6) P. aeruginosa and 10(3)-10(4) S. choleraesuis. These data suggest that disinfectants are not similarly challenged with the AOAC-recommended test bacteria and that an alternative method should be considered to ensure comparable numbers of bacteria on penicylinders.

Computer-aided diagnosis with textural features for breast lesions in sonograms.

Science.gov (United States)

Chen, Dar-Ren; Huang, Yu-Len; Lin, Sheng-Hsiung

2011-04-01

Computer-aided diagnosis (CAD) systems provided second beneficial support reference and enhance the diagnostic accuracy. This paper was aimed to develop and evaluate a CAD with texture analysis in the classification of breast tumors for ultrasound images. The ultrasound (US) dataset evaluated in this study composed of 1020 sonograms of region of interest (ROI) subimages from 255 patients. Two-view sonogram (longitudinal and transverse views) and four different rectangular regions were utilized to analyze each tumor. Six practical textural features from the US images were performed to classify breast tumors as benign or malignant. However, the textural features always perform as a high dimensional vector; high dimensional vector is unfavorable to differentiate breast tumors in practice. The principal component analysis (PCA) was used to reduce the dimension of textural feature vector and then the image retrieval technique was performed to differentiate between benign and malignant tumors. In the experiments, all the cases were sampled with k-fold cross-validation (k=10) to evaluate the performance with receiver operating characteristic (ROC) curve. The area (A(Z)) under the ROC curve for the proposed CAD system with the specific textural features was 0.925±0.019. The classification ability for breast tumor with textural information is satisfactory. This system differentiates benign from malignant breast tumors with a good result and is therefore clinically useful to provide a second opinion. Copyright © 2010 Elsevier Ltd. All rights reserved.

Fast segmentation of industrial quality pavement images using Laws texture energy measures and k -means clustering

Science.gov (United States)

Mathavan, Senthan; Kumar, Akash; Kamal, Khurram; Nieminen, Michael; Shah, Hitesh; Rahman, Mujib

2016-09-01

Thousands of pavement images are collected by road authorities daily for condition monitoring surveys. These images typically have intensity variations and texture nonuniformities that make their segmentation challenging. The automated segmentation of such pavement images is crucial for accurate, thorough, and expedited health monitoring of roads. In the pavement monitoring area, well-known texture descriptors, such as gray-level co-occurrence matrices and local binary patterns, are often used for surface segmentation and identification. These, despite being the established methods for texture discrimination, are inherently slow. This work evaluates Laws texture energy measures as a viable alternative for pavement images for the first time. k-means clustering is used to partition the feature space, limiting the human subjectivity in the process. Data classification, hence image segmentation, is performed by the k-nearest neighbor method. Laws texture energy masks are shown to perform well with resulting accuracy and precision values of more than 80%. The implementations of the algorithm, in both MATLAB® and OpenCV/C++, are extensively compared against the state of the art for execution speed, clearly showing the advantages of the proposed method. Furthermore, the OpenCV-based segmentation shows a 100% increase in processing speed when compared to the fastest algorithm available in literature.

Rapidly 3D Texture Reconstruction Based on Oblique Photography

Directory of Open Access Journals (Sweden)

ZHANG Chunsen

2015-07-01

Full Text Available This paper proposes a city texture fast reconstruction method based on aerial tilt image for reconstruction of three-dimensional city model. Based on the photogrammetry and computer vision theory and using the city building digital surface model obtained by prior treatment, through collinear equation calculation geometric projection of object and image space, to obtain the three-dimensional information and texture information of the structure and through certain the optimal algorithm selecting the optimal texture on the surface of the object, realize automatic extraction of the building side texture and occlusion handling of the dense building texture. The real image texture reconstruction results show that: the method to the 3D city model texture reconstruction has the characteristics of high degree of automation, vivid effect and low cost and provides a means of effective implementation for rapid and widespread real texture rapid reconstruction of city 3D model.

Spin polarized electronic states and spin textures at the surface of oxygen-deficient SrTiO3

Science.gov (United States)

Jeschke, Harald O.; Altmeyer, Michaela; Rozenberg, Marcelo; Gabay, Marc; Valenti, Roser

We investigate the electronic structure and spin texture at the (001) surface of SrTiO3 in the presence of oxygen vacancies by means of ab initio density functional theory (DFT) calculations of slabs. Relativistic non-magnetic DFT calculations exhibit Rashba-like spin winding with a characteristic energy scale ~ 10 meV. However, when surface magnetism on the Ti ions is included, bands become spin-split with an energy difference ~ 100 meV at the Γ point. This energy scale is comparable to the observations in SARPES experiments performed on the two-dimensional electronic states confined near the (001) surface of SrTiO3. We find the spin polarized state to be the ground state of the system, and while magnetism tends to suppress the effects of the relativistic Rashba interaction, signatures of it are still clearly visible in terms of complex spin textures. We gratefully acknowledge financial support from the Deutsche Forschungsgemeinschaft through grants SFB/TR 49 and FOR 1346.

Atomically flat surface of (0 0 1) textured FePt thin films by residual stress control

Energy Technology Data Exchange (ETDEWEB)

Liu, S.H. [Department of Materials Science and Engineering, Feng Chia University, Taichung 407, Taiwan (China); Hsiao, S.N., E-mail: pmami.hsiao@gmail.com [Department of Materials Science and Engineering, Feng Chia University, Taichung 407, Taiwan (China); Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu 300, Taiwan (China); Chou, C.L.; Chen, S.K. [Department of Materials Science and Engineering, Feng Chia University, Taichung 407, Taiwan (China); Lee, H.Y. [National Synchrotron Radiation Research Center, Hsinchu 300, Taiwan (China); Department of Applied Science, National Hsinchu University of Education, Hsinchu 300, Taiwan (China)

2015-11-01

Highlights: • We demonstrate crystallographic structure, (0 0 1) texture, surface roughness, and residual stress in the single-layered FePt thin films annealed at various heating rates (10–110 K/s). • Texture coefficient of (0 0 1)-plane of the samples increases with increasing heating rate from 10 to 40 K/s, which is correlated with perpendicular magnetic anisotropy and in-plane tensile stress. • Dewetting phenomenon due to stress relaxation leads to the broadening of [0 0 1] easy axis and degradation of perpendicular magnetic anisotropy. • A strong dependence of surface roughness on in-plane residual stress was revealed. • When the samples are RTA at 40 K/s, the enhanced perpendicular magnetic anisotropy and atomically surface roughness are achieved. - Abstract: Single-layered Fe{sub 52}Pt{sub 48} films with thickness of 10 nm were sputter-deposited on glass substrates. Rapid thermal annealing with different heating rates (10–110 K/s) was applied to transform as-deposited fcc phase into L1{sub 0} phase and meanwhile to align [0 0 1]-axis of L1{sub 0} crystal along plane normal direction. Based on X-ray diffractometry using synchrotron radiation source, the texture coefficient of (0 0 1)-plane increases with increasing heating rate from 10 to 40 K/s, which is correlated with perpendicular magnetic anisotropy and in-plane tensile stress analyzed by asymmetric sin{sup 2} ψ method. Furthermore, it was revealed by atomic force microscopy that the dewetting process occurred as heating rate was raised up to 80 K/s and higher. The change in the microstructure due to stress relaxation leads to the degradation of (0 0 1) orientation and magnetic properties. Surface roughness is closely related to the in-plane tensile stress. Enhanced perpendicular magnetic anisotropy and atomically flat surface were achieved for the samples annealed at 40 K/s, which may be suitable for further practical applications. This work also suggests a feasible way for surface

Classification of pre-sliced pork and Turkey ham qualities based on image colour and textural features and their relationships with consumer responses.

Science.gov (United States)

Iqbal, Abdullah; Valous, Nektarios A; Mendoza, Fernando; Sun, Da-Wen; Allen, Paul

2010-03-01

Images of three qualities of pre-sliced pork and Turkey hams were evaluated for colour and textural features to characterize and classify them, and to model the ham appearance grading and preference responses of a group of consumers. A total of 26 colour features and 40 textural features were extracted for analysis. Using Mahalanobis distance and feature inter-correlation analyses, two best colour [mean of S (saturation in HSV colour space), std. deviation of b*, which indicates blue to yellow in L*a*b* colour space] and three textural features [entropy of b*, contrast of H (hue of HSV colour space), entropy of R (red of RGB colour space)] for pork, and three colour (mean of R, mean of H, std. deviation of a*, which indicates green to red in L*a*b* colour space) and two textural features [contrast of B, contrast of L* (luminance or lightness in L*a*b* colour space)] for Turkey hams were selected as features with the highest discriminant power. High classification performances were reached for both types of hams (>99.5% for pork and >90.5% for Turkey) using the best selected features or combinations of them. In spite of the poor/fair agreement among ham consumers as determined by Kappa analysis (Kappa-valuetexture appearance and acceptability), a dichotomous logistic regression model using the best image features was able to explain the variability of consumers' responses for all sensorial attributes with accuracies higher than 74.1% for pork hams and 83.3% for Turkey hams. Copyright 2009 Elsevier Ltd. All rights reserved.

Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

Science.gov (United States)

Ma, Xu; Cheng, Yongmei; Hao, Shuai

2016-12-10

Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

[Visual Texture Agnosia in Humans].

Science.gov (United States)

Suzuki, Kyoko

2015-06-01

Visual object recognition requires the processing of both geometric and surface properties. Patients with occipital lesions may have visual agnosia, which is impairment in the recognition and identification of visually presented objects primarily through their geometric features. An analogous condition involving the failure to recognize an object by its texture may exist, which can be called visual texture agnosia. Here we present two cases with visual texture agnosia. Case 1 had left homonymous hemianopia and right upper quadrantanopia, along with achromatopsia, prosopagnosia, and texture agnosia, because of damage to his left ventromedial occipitotemporal cortex and right lateral occipito-temporo-parietal cortex due to multiple cerebral embolisms. Although he showed difficulty matching and naming textures of real materials, he could readily name visually presented objects by their contours. Case 2 had right lower quadrantanopia, along with impairment in stereopsis and recognition of texture in 2D images, because of subcortical hemorrhage in the left occipitotemporal region. He failed to recognize shapes based on texture information, whereas shape recognition based on contours was well preserved. Our findings, along with those of three reported cases with texture agnosia, indicate that there are separate channels for processing texture, color, and geometric features, and that the regions around the left collateral sulcus are crucial for texture processing.

The Synergistic Effect of Leukocyte Platelet-Rich Fibrin and Micrometer/Nanometer Surface Texturing on Bone Healing around Immediately Placed Implants: An Experimental Study in Dogs

Science.gov (United States)

Neiva, Rodrigo F.; Gil, Luiz Fernando; Tovar, Nick; Janal, Malvin N.; Marao, Heloisa Fonseca; Pinto, Nelson; Coelho, Paulo G.

2016-01-01

Aims. This study evaluated the effects of L-PRF presence and implant surface texture on bone healing around immediately placed implants. Methods. The first mandibular molars of 8 beagle dogs were bilaterally extracted, and implants (Blossom™, Intra-Lock International, Boca Raton, FL) were placed in the mesial or distal extraction sockets in an interpolated fashion per animal. Two implant surfaces were distributed per sockets: (1) dual acid-etched (DAE, micrometer scale textured) and (2) micrometer/nanometer scale textured (Ossean™ surface). L-PRF (Intraspin system, Intra-Lock International) was placed in a split-mouth design to fill the macrogap between implant and socket walls on one side of the mandible. The contralateral side received implants without L-PRF. A mixed-model ANOVA (at α = 0.05) evaluated the effect of implant surface, presence of L-PRF, and socket position (mesial or distal), individually or in combination on bone area fraction occupancy (BAFO). Results. BAFO values were significantly higher for the Ossean relative to the DAE surface on the larger mesial socket. The presence of L-PRF resulted in higher BAFO. The Ossean surface and L-PRF presence resulted in significantly higher BAFO. Conclusion. L-PRF and the micro-/nanometer scale textured surface resulted in increased bone formation around immediately placed implants. PMID:28042577

The Synergistic Effect of Leukocyte Platelet-Rich Fibrin and Micrometer/Nanometer Surface Texturing on Bone Healing around Immediately Placed Implants: An Experimental Study in Dogs

Directory of Open Access Journals (Sweden)

Rodrigo F. Neiva

2016-01-01

Full Text Available Aims. This study evaluated the effects of L-PRF presence and implant surface texture on bone healing around immediately placed implants. Methods. The first mandibular molars of 8 beagle dogs were bilaterally extracted, and implants (Blossom™, Intra-Lock International, Boca Raton, FL were placed in the mesial or distal extraction sockets in an interpolated fashion per animal. Two implant surfaces were distributed per sockets: (1 dual acid-etched (DAE, micrometer scale textured and (2 micrometer/nanometer scale textured (Ossean™ surface. L-PRF (Intraspin system, Intra-Lock International was placed in a split-mouth design to fill the macrogap between implant and socket walls on one side of the mandible. The contralateral side received implants without L-PRF. A mixed-model ANOVA (at α=0.05 evaluated the effect of implant surface, presence of L-PRF, and socket position (mesial or distal, individually or in combination on bone area fraction occupancy (BAFO. Results. BAFO values were significantly higher for the Ossean relative to the DAE surface on the larger mesial socket. The presence of L-PRF resulted in higher BAFO. The Ossean surface and L-PRF presence resulted in significantly higher BAFO. Conclusion. L-PRF and the micro-/nanometer scale textured surface resulted in increased bone formation around immediately placed implants.

Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition

Directory of Open Access Journals (Sweden)

Kun-Ching Wang

2015-01-01

Full Text Available The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI. In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII. The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.

Breast density pattern characterization by histogram features and texture descriptors

Directory of Open Access Journals (Sweden)

Pedro Cunha Carneiro

2017-04-01

Full Text Available Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammographic images into categories of breast density using an Artificial Neural Network. Methods We used 307 mammographic images from the INbreast digital database, extracting histogram features and texture descriptors of all mammograms and selecting them with the K-means technique. Then, these groups of selected features were used as inputs of an Artificial Neural Network to classify the images automatically into the four categories reported by radiologists. Results An average accuracy of 92.9% was obtained in a few tests using only some of the Haralick texture descriptors. Also, the accuracy rate increased to 98.95% when texture descriptors were mixed with some features based on a histogram. Conclusion Texture descriptors have proven to be better than gray levels features at differentiating the breast densities in mammographic images. From this paper, it was possible to automate the feature selection and the classification with acceptable error rates since the extraction of the features is suitable to the characteristics of the images involving the problem.

Texture design for light touch perception

NARCIS (Netherlands)

Zhang, S.; Zeng, X.; Matthews, D.T.A.; Igartua, A.; Rodriguez Vidal, E.; Fortes, J. Contreras; Van Der Heide, E.

This study focused on active light touch with predefined textures specially-designed for tactile perception. The counter-body material is stainless steel sheet. Three geometric structures (grid, crater and groove) were fabricated by pulsed laser surface texturing. A total number of twenty volunteers

Rational design of organic semiconductors for texture control and self-patterning on halogenated surfaces

KAUST Repository

Ward, Jeremy W.

2014-05-15

Understanding the interactions at interfaces between the materials constituting consecutive layers within organic thin-film transistors (OTFTs) is vital for optimizing charge injection and transport, tuning thin-film microstructure, and designing new materials. Here, the influence of the interactions at the interface between a halogenated organic semiconductor (OSC) thin film and a halogenated self-assembled monolayer on the formation of the crystalline texture directly affecting the performance of OTFTs is explored. By correlating the results from microbeam grazing incidence wide angle X-ray scattering (μGIWAXS) measurements of structure and texture with OTFT characteristics, two or more interaction paths between the terminating atoms of the semiconductor and the halogenated surface are found to be vital to templating a highly ordered morphology in the first layer. These interactions are effective when the separating distance is lower than 2.5 dw, where dw represents the van der Waals distance. The ability to modulate charge carrier transport by several orders of magnitude by promoting "edge-on" versus "face-on" molecular orientation and crystallographic textures in OSCs is demonstrated. It is found that the "edge-on" self-assembly of molecules forms uniform, (001) lamellar-textured crystallites which promote high charge carrier mobility, and that charge transport suffers as the fraction of the "face-on" oriented crystallites increases. The role of interfacial halogenation in mediating texture formation and the self-patterning of organic semiconductor films, as well as the resulting effects on charge transport in organic thin-film transistors, are explored. The presence of two or more anchoring sites between a halogenated semiconductor and a halogenated self-assembled monolayer, closer than about twice the corresponding van der Waals distance, alter the microstructure and improve electrical properties. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Injection moulding of plastic parts with laser textured surfaces with optical applications

Science.gov (United States)

Pina-Estany, J.; García-Granada, A. A.; Corull-Massana, E.

2018-05-01

The purpose of this work is to manufacture micro and nanotextured surfaces on plastic injection moulds with the aim of replicating them and obtaining plastic parts with optical applications. Different patterns are manufactured with nanosecond and femtosecond lasers in order to obtain three different optical applications: (i) homogeneous light diffusion (ii) 1D light directionality and (iii) 2D light directionality. Induction heating is used in the injections in order to improve the textures degree of replication. The steel mould and the plastic parts are analyzed with a confocal/focus variation microscope and with a surface roughness tester. A mock-up and a luminance camera are used to evaluate the homogeneity and luminance of the homogeneous light diffusion application in comparison with the current industrial solutions.

Bayesian exploration for intelligent identification of textures

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Jeremy A. Fishel

2012-06-01

Full Text Available In order to endow robots with humanlike abilities to characterize and identify objects, they must be provided with tactile sensors and intelligent algorithms to select, control and interpret data from useful exploratory movements. Humans make informed decisions on the sequence of exploratory movements that would yield the most information for the task, depending on what the object may be and prior knowledge of what to expect from possible exploratory movements. This study is focused on texture discrimination, a subset of a much larger group of exploratory movements and percepts that humans use to discriminate, characterize, and identify objects. Using a testbed equipped with a biologically inspired tactile sensor (the BioTac® we produced sliding movements similar to those that humans make when exploring textures. Measurement of tactile vibrations and reaction forces when exploring textures were used to extract measures of textural properties inspired from psychophysical literature (traction, roughness, and fineness. Different combinations of normal force and velocity were identified to be useful for each of these three properties. A total of 117 textures were explored with these three movements to create a database of prior experience to use for identifying these same textures in future encounters. When exploring a texture, the discrimination algorithm adaptively selects the optimal movement to make and property to measure based on previous experience to differentiate the texture from a set of plausible candidates, a process we call Bayesian exploration. Performance of 99.6% in correctly discriminating pairs of similar textures was found to exceed human capabilities. Absolute classification from the entire set of 117 textures generally required a small number of well-chosen exploratory movements (median=5 and yielded a 95.4% success rate. The method of Bayesian exploration developed and tested in this paper may generalize well to other

Extending ultra-short pulse laser texturing over large area

Energy Technology Data Exchange (ETDEWEB)

Mincuzzi, G., E-mail: girolamo.mincuzzi@alphanov.com; Gemini, L.; Faucon, M.; Kling, R.

2016-11-15

Highlights: • We carried out metal surface texturing (Ripples, micro grooves, Spikes) using a high power, high repetition rate, industrial, Ultra-short pulses laser. • Extremely Fast processing is shown (Laser Scan speed as high as 90 m/s) with a polygon scanner head. • Stainless steel surface blackening with Ultra-short pulses laser has been obtained with unprecedented scanspeed. • Full SEM surface characterization was carried out for all the different structures obtained. • Reflectance measurements were carried out to characterize surface reflectance. - Abstract: Surface texturing by Ultra-Short Pulses Laser (UPL) for industrial applications passes through the use of both fast beam scanning systems and high repetition rate, high average power P, UPL. Nevertheless unwanted thermal effects are expected when P exceeds some tens of W. An interesting strategy for a reliable heat management would consists in texturing with a low fluence values (slightly higher than the ablation threshold) and utilising a Polygon Scanner Heads delivering laser pulses with unrepeated speed. Here we show for the first time that with relatively low fluence it is possible over stainless steel, to obtain surface texturing by utilising a 2 MHz femtosecond laser jointly with a polygonal scanner head in a relatively low fluence regime (0.11 J cm{sup −2}). Different surface textures (Ripples, micro grooves and spikes) can be obtained varying the scan speed from 90 m s{sup −1} to 25 m s{sup −1}. In particular, spikes formation process has been shown and optimised at 25 m s{sup −1} and a full morphology characterization by SEM has been carried out. Reflectance measurements with integrating sphere are presented to compare reference surface with high scan rate textures. In the best case we show a black surface with reflectance value < 5%.

Unsupervised feature learning for autonomous rock image classification

Science.gov (United States)

Shu, Lei; McIsaac, Kenneth; Osinski, Gordon R.; Francis, Raymond

2017-09-01

Autonomous rock image classification can enhance the capability of robots for geological detection and enlarge the scientific returns, both in investigation on Earth and planetary surface exploration on Mars. Since rock textural images are usually inhomogeneous and manually hand-crafting features is not always reliable, we propose an unsupervised feature learning method to autonomously learn the feature representation for rock images. In our tests, rock image classification using the learned features shows that the learned features can outperform manually selected features. Self-taught learning is also proposed to learn the feature representation from a large database of unlabelled rock images of mixed class. The learned features can then be used repeatedly for classification of any subclass. This takes advantage of the large dataset of unlabelled rock images and learns a general feature representation for many kinds of rocks. We show experimental results supporting the feasibility of self-taught learning on rock images.

Formation of biaxial texture in metal films by selective ion beam etching

Energy Technology Data Exchange (ETDEWEB)

Park, S.J. [Department of Materials Science and Engineering, University of Florida, 106 Rhines Hall, P.O. Box 116400, Gainesville, FL 32611 (United States); Norton, D.P. [Department of Materials Science and Engineering, University of Florida, 106 Rhines Hall, P.O. Box 116400, Gainesville, FL 32611 (United States)]. E-mail: dnort@mse.ufl.edu; Selvamanickam, Venkat [IGC-SuperPower, LLC, 450 Duane Avenue, Schenectady, NY 12304 (United States)

2006-05-15

The formation of in-plane texture via ion bombardment of uniaxially textured metal films was investigated. In particular, selective grain Ar ion beam etching of uniaxially textured (0 0 1) Ni was used to achieve in-plane aligned Ni grains. Unlike conventional ion beam assisted deposition, the ion beam irradiates the uniaxially textured film surface with no impinging deposition flux. The initial uniaxial texture is established via surface energy minimization with no ion irradiation. Within this sequential texturing method, in-plane grain alignment is driven by selective etching and grain overgrowth. Biaxial texture was achieved for ion beam irradiation at elevated temperature.

Formation of biaxial texture in metal films by selective ion beam etching

International Nuclear Information System (INIS)

Park, S.J.; Norton, D.P.; Selvamanickam, Venkat

2006-01-01

The formation of in-plane texture via ion bombardment of uniaxially textured metal films was investigated. In particular, selective grain Ar ion beam etching of uniaxially textured (0 0 1) Ni was used to achieve in-plane aligned Ni grains. Unlike conventional ion beam assisted deposition, the ion beam irradiates the uniaxially textured film surface with no impinging deposition flux. The initial uniaxial texture is established via surface energy minimization with no ion irradiation. Within this sequential texturing method, in-plane grain alignment is driven by selective etching and grain overgrowth. Biaxial texture was achieved for ion beam irradiation at elevated temperature

Texture Analysis of Hydrophobic Polycarbonate and Polydimethylsiloxane Surfaces via Persistent Homology

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Ali Nabi Duman

2017-09-01

Full Text Available Due to recent climate change-triggered, regular dust storms in the Middle East, dust mitigation has become the critical issue for solar energy harvesting devices. One of the methods to minimize and prevent dust adhesion and create self-cleaning abilities is to generate hydrophobic characteristics on surfaces. The purpose of this study is to explore the topological features of hydrophobic surfaces. We use non-standard techniques from topological data analysis to extract morphological features from the AFM images. Our method recovers most of the previous qualitative observations in a robust and quantitative way. Persistence diagrams, which is a summary of topological structures, witness quantitatively that the crystallized polycarbonate (PC surface possesses spherulites, voids, and fibrils, and the texture height and spherulite concentration increases with the increased immersion period. The approach also shows that the polydimethylsiloxane (PDMS exactly copied the structures at the PC surface but 80 to 90 percent of the nanofibrils were not copied at PDMS surface. We next extract a feature vector from each persistence diagram to show which experiments hold features with similar variance using principal component analysis (PCA. The K-means clustering algorithm is applied to the matrix of feature vectors to support the PCA result, grouping experiments with similar features.

Surface water classification and monitoring using polarimetric synthetic aperture radar

Science.gov (United States)

Irwin, Katherine Elizabeth

Surface water classification using synthetic aperture radar (SAR) is an established practice for monitoring flood hazards due to the high temporal and spatial resolution it provides. Surface water change is a dynamic process that varies both spatially and temporally, and can occur on various scales resulting in significant impacts on affected areas. Small-scale flooding hazards, caused by beaver dam failure, is an example of surface water change, which can impact nearby infrastructure and ecosystems. Assessing these hazards is essential to transportation and infrastructure maintenance. With current satellite missions operating in multiple polarizations, spatio-temporal resolutions, and frequencies, a comprehensive comparison between SAR products for surface water monitoring is necessary. In this thesis, surface water extent models derived from high resolution single-polarization TerraSAR-X (TSX) data, medium resolution dual-polarization TSX data and low resolution quad-polarization RADARSAT-2 (RS-2) data are compared. There exists a compromise between acquiring SAR data with a high resolution or high information content. Multi-polarization data provides additional phase and intensity information, which makes it possible to better classify areas of flooded vegetation and wetlands. These locations are often where fluctuations in surface water occur and are essential for understanding dynamic underlying processes. However, often multi-polarized data is acquired at a low resolution, which cannot image these zones effectively. High spatial resolution, single-polarization TSX data provides the best model of open water. However, these single-polarization observations have limited information content and are affected by shadow and layover errors. This often hinders the classification of other land cover types. The dual-polarization TSX data allows for the classification of flooded vegetation, but classification is less accurate compared to the quad-polarization RS-2 data

Regenerated collagen fibers with grooved surface texture: Physicochemical characterization and cytocompatibility

International Nuclear Information System (INIS)

Wang, Xiang; Wu, Tong; Wang, Wei; Huang, Chen; Jin, Xiangyu

2016-01-01

A novel type of protein fibers, regenerated collagen fibers (RC) from cattle skin, was prepared through wet-spinning. Due to the combined effect of solvent exchange and subsequent drawing process, the fibers were found to have a grooved surface texture. The grooves provided not only ordered topographical cues, but also increased surface area. Protein content of the RC fibers was confirmed by Fourier Transform infrared spectroscopy (FTIR) and ninhydrin color reaction. The fibers could be readily fabricated into nonwovens or other textiles, owning to their comparable physical properties to other commercialized fibers. Cell growth behavior on RC nonwovens suggested both early adhesion and prompt proliferation. The high moisture regain, good processability, along with the excellent cytocompatibility indicated that the RC fibers and nonwovens developed in this study might offer a good candidate for biomedical and healthcare applications. - Highlights: • Wet-spun regenerated collagen fibers having aligned surface grooves • Comparable physiochemical properties to commercialized fibers • Readily processed into nonwovens • Excellent cytocompatibility with prompt cell adhesion and proliferation

Regenerated collagen fibers with grooved surface texture: Physicochemical characterization and cytocompatibility

Energy Technology Data Exchange (ETDEWEB)

Wang, Xiang [Engineering Research Center of Technical Textiles, Ministry of Education, College of Textiles, Donghua University, Shanghai 201620 (China); Wu, Tong [College of Chemistry, Chemical Engineering and Biotechnology, Donghua University, Shanghai 201620 (China); Wang, Wei [Engineering Research Center of Technical Textiles, Ministry of Education, College of Textiles, Donghua University, Shanghai 201620 (China); Huang, Chen, E-mail: hc@dhu.edu.cn [Engineering Research Center of Technical Textiles, Ministry of Education, College of Textiles, Donghua University, Shanghai 201620 (China); Jin, Xiangyu [Engineering Research Center of Technical Textiles, Ministry of Education, College of Textiles, Donghua University, Shanghai 201620 (China)

2016-01-01

A novel type of protein fibers, regenerated collagen fibers (RC) from cattle skin, was prepared through wet-spinning. Due to the combined effect of solvent exchange and subsequent drawing process, the fibers were found to have a grooved surface texture. The grooves provided not only ordered topographical cues, but also increased surface area. Protein content of the RC fibers was confirmed by Fourier Transform infrared spectroscopy (FTIR) and ninhydrin color reaction. The fibers could be readily fabricated into nonwovens or other textiles, owning to their comparable physical properties to other commercialized fibers. Cell growth behavior on RC nonwovens suggested both early adhesion and prompt proliferation. The high moisture regain, good processability, along with the excellent cytocompatibility indicated that the RC fibers and nonwovens developed in this study might offer a good candidate for biomedical and healthcare applications. - Highlights: • Wet-spun regenerated collagen fibers having aligned surface grooves • Comparable physiochemical properties to commercialized fibers • Readily processed into nonwovens • Excellent cytocompatibility with prompt cell adhesion and proliferation.

Object-based Dimensionality Reduction in Land Surface Phenology Classification

Directory of Open Access Journals (Sweden)

Brian E. Bunker

2016-11-01

Full Text Available Unsupervised classification or clustering of multi-decadal land surface phenology provides a spatio-temporal synopsis of natural and agricultural vegetation response to environmental variability and anthropogenic activities. Notwithstanding the detailed temporal information available in calibrated bi-monthly normalized difference vegetation index (NDVI and comparable time series, typical pre-classification workflows average a pixel’s bi-monthly index within the larger multi-decadal time series. While this process is one practical way to reduce the dimensionality of time series with many hundreds of image epochs, it effectively dampens temporal variation from both intra and inter-annual observations related to land surface phenology. Through a novel application of object-based segmentation aimed at spatial (not temporal dimensionality reduction, all 294 image epochs from a Moderate Resolution Imaging Spectroradiometer (MODIS bi-monthly NDVI time series covering the northern Fertile Crescent were retained (in homogenous landscape units as unsupervised classification inputs. Given the inherent challenges of in situ or manual image interpretation of land surface phenology classes, a cluster validation approach based on transformed divergence enabled comparison between traditional and novel techniques. Improved intra-annual contrast was clearly manifest in rain-fed agriculture and inter-annual trajectories showed increased cluster cohesion, reducing the overall number of classes identified in the Fertile Crescent study area from 24 to 10. Given careful segmentation parameters, this spatial dimensionality reduction technique augments the value of unsupervised learning to generate homogeneous land surface phenology units. By combining recent scalable computational approaches to image segmentation, future work can pursue new global land surface phenology products based on the high temporal resolution signatures of vegetation index time series.

Parsimonious classification of binary lacunarity data computed from food surface images using kernel principal component analysis and artificial neural networks.

Science.gov (United States)

Iqbal, Abdullah; Valous, Nektarios A; Sun, Da-Wen; Allen, Paul

2011-02-01

Lacunarity is about quantifying the degree of spatial heterogeneity in the visual texture of imagery through the identification of the relationships between patterns and their spatial configurations in a two-dimensional setting. The computed lacunarity data can designate a mathematical index of spatial heterogeneity, therefore the corresponding feature vectors should possess the necessary inter-class statistical properties that would enable them to be used for pattern recognition purposes. The objectives of this study is to construct a supervised parsimonious classification model of binary lacunarity data-computed by Valous et al. (2009)-from pork ham slice surface images, with the aid of kernel principal component analysis (KPCA) and artificial neural networks (ANNs), using a portion of informative salient features. At first, the dimension of the initial space (510 features) was reduced by 90% in order to avoid any noise effects in the subsequent classification. Then, using KPCA, the first nineteen kernel principal components (99.04% of total variance) were extracted from the reduced feature space, and were used as input in the ANN. An adaptive feedforward multilayer perceptron (MLP) classifier was employed to obtain a suitable mapping from the input dataset. The correct classification percentages for the training, test and validation sets were 86.7%, 86.7%, and 85.0%, respectively. The results confirm that the classification performance was satisfactory. The binary lacunarity spatial metric captured relevant information that provided a good level of differentiation among pork ham slice images. Copyright © 2010 The American Meat Science Association. Published by Elsevier Ltd. All rights reserved.

Histogram-based adaptive gray level scaling for texture feature classification of colorectal polyps

Science.gov (United States)

Pomeroy, Marc; Lu, Hongbing; Pickhardt, Perry J.; Liang, Zhengrong

2018-02-01

Texture features have played an ever increasing role in computer aided detection (CADe) and diagnosis (CADx) methods since their inception. Texture features are often used as a method of false positive reduction for CADe packages, especially for detecting colorectal polyps and distinguishing them from falsely tagged residual stool and healthy colon wall folds. While texture features have shown great success there, the performance of texture features for CADx have lagged behind primarily because of the more similar features among different polyps types. In this paper, we present an adaptive gray level scaling and compare it to the conventional equal-spacing of gray level bins. We use a dataset taken from computed tomography colonography patients, with 392 polyp regions of interest (ROIs) identified and have a confirmed diagnosis through pathology. Using the histogram information from the entire ROI dataset, we generate the gray level bins such that each bin contains roughly the same number of voxels Each image ROI is the scaled down to two different numbers of gray levels, using both an equal spacing of Hounsfield units for each bin, and our adaptive method. We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas), we find that the adaptive gray level scaling can improve performance based on the area under the receiver operating characteristic curve by up to 4.6%.

Automatic classification of cardioembolic and arteriosclerotic ischemic strokes from apparent diffusion coefficient datasets using texture analysis and deep learning

Science.gov (United States)

Villafruela, Javier; Crites, Sebastian; Cheng, Bastian; Knaack, Christian; Thomalla, Götz; Menon, Bijoy K.; Forkert, Nils D.

2017-03-01

Stroke is a leading cause of death and disability in the western hemisphere. Acute ischemic strokes can be broadly classified based on the underlying cause into atherosclerotic strokes, cardioembolic strokes, small vessels disease, and stroke with other causes. The ability to determine the exact origin of an acute ischemic stroke is highly relevant for optimal treatment decision and preventing recurrent events. However, the differentiation of atherosclerotic and cardioembolic phenotypes can be especially challenging due to similar appearance and symptoms. The aim of this study was to develop and evaluate the feasibility of an image-based machine learning approach for discriminating between arteriosclerotic and cardioembolic acute ischemic strokes using 56 apparent diffusion coefficient (ADC) datasets from acute stroke patients. For this purpose, acute infarct lesions were semi-atomically segmented and 30,981 geometric and texture image features were extracted for each stroke volume. To improve the performance and accuracy, categorical Pearson's χ2 test was used to select the most informative features while removing redundant attributes. As a result, only 289 features were finally included for training of a deep multilayer feed-forward neural network without bootstrapping. The proposed method was evaluated using a leave-one-out cross validation scheme. The proposed classification method achieved an average area under receiver operator characteristic curve value of 0.93 and a classification accuracy of 94.64%. These first results suggest that the proposed image-based classification framework can support neurologists in clinical routine differentiating between atherosclerotic and cardioembolic phenotypes.

Wet-Chemical Surface Texturing of Sputter-Deposited ZnO:Al Films as Front Electrode for Thin-Film Silicon Solar Cells

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Xia Yan

2015-01-01

Full Text Available Transparent conductive oxides (TCOs play a major role as the front electrodes of thin-film silicon (Si solar cells, as they can provide optical scattering and hence improved photon absorption inside the devices. In this paper we report on the surface texturing of aluminium-doped zinc oxide (ZnO:Al or AZO films for improved light trapping in thin-film Si solar cells. The AZO films are deposited onto soda-lime glass sheets via pulsed DC magnetron sputtering. Several promising AZO texturing methods are investigated using diluted hydrochloric (HCl and hydrofluoric acid (HF, through a two-step etching process. The developed texturing procedure combines the advantages of the HCl-induced craters and the smaller and jagged—but laterally more uniform—features created by HF etching. In the two-step process, the second etching step further enhances the optical haze, while simultaneously improving the uniformity of the texture features created by the HCl etch. The resulting AZO films show large haze values of above 40%, good scattering into large angles, and a surface angle distribution that is centred at around 30°, which is known from the literature to provide efficient light trapping for thin-film Si solar cells.

Uav-Based Crops Classification with Joint Features from Orthoimage and Dsm Data

Science.gov (United States)

Liu, B.; Shi, Y.; Duan, Y.; Wu, W.

2018-04-01

Accurate crops classification remains a challenging task due to the same crop with different spectra and different crops with same spectrum phenomenon. Recently, UAV-based remote sensing approach gains popularity not only for its high spatial and temporal resolution, but also for its ability to obtain spectraand spatial data at the same time. This paper focus on how to take full advantages of spatial and spectrum features to improve crops classification accuracy, based on an UAV platform equipped with a general digital camera. Texture and spatial features extracted from the RGB orthoimage and the digital surface model of the monitoring area are analysed and integrated within a SVM classification framework. Extensive experiences results indicate that the overall classification accuracy is drastically improved from 72.9 % to 94.5 % when the spatial features are combined together, which verified the feasibility and effectiveness of the proposed method.

Defect detection and classification of machined surfaces under multiple illuminant directions

Science.gov (United States)

Liao, Yi; Weng, Xin; Swonger, C. W.; Ni, Jun

2010-08-01

Continuous improvement of product quality is crucial to the successful and competitive automotive manufacturing industry in the 21st century. The presence of surface porosity located on flat machined surfaces such as cylinder heads/blocks and transmission cases may allow leaks of coolant, oil, or combustion gas between critical mating surfaces, thus causing damage to the engine or transmission. Therefore 100% inline inspection plays an important role for improving product quality. Although the techniques of image processing and machine vision have been applied to machined surface inspection and well improved in the past 20 years, in today's automotive industry, surface porosity inspection is still done by skilled humans, which is costly, tedious, time consuming and not capable of reliably detecting small defects. In our study, an automated defect detection and classification system for flat machined surfaces has been designed and constructed. In this paper, the importance of the illuminant direction in a machine vision system was first emphasized and then the surface defect inspection system under multiple directional illuminations was designed and constructed. After that, image processing algorithms were developed to realize 5 types of 2D or 3D surface defects (pore, 2D blemish, residue dirt, scratch, and gouge) detection and classification. The steps of image processing include: (1) image acquisition and contrast enhancement (2) defect segmentation and feature extraction (3) defect classification. An artificial machined surface and an actual automotive part: cylinder head surface were tested and, as a result, microscopic surface defects can be accurately detected and assigned to a surface defect class. The cycle time of this system can be sufficiently fast that implementation of 100% inline inspection is feasible. The field of view of this system is 150mm×225mm and the surfaces larger than the field of view can be stitched together in software.

How wear affects road surface texture and its impact on tire/road noise

OpenAIRE

Siebert, Doreen

2017-01-01

Mechanical pavement wear in the Nordic countries is essentially influenced by the use of studded tires during long winter seasons. The abrasive effect of the studded tires is the cause of significant damage on the pavement and a contributor to rutting. In addition, the mechanical aggregate removal due to the studded tires is the reason for significant changes in the road surface texture. At traditional dense asphalt pavements, the mechanical wear is initiated by the abrasion of the mortar, wh...

Solder wetting behavior enhancement via laser-textured surface microcosmic topography

Energy Technology Data Exchange (ETDEWEB)

Chen, Haiyan [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi’an 710072 (China); Shaanxi Key Laboratory of Friction Welding Technologies, Xi’an 710072 (China); Peng, Jianke [Shaanxi Key Laboratory of Friction Welding Technologies, Xi’an 710072 (China); Fu, Li, E-mail: fuli@nwpu.edu.cn [State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi’an 710072 (China); Shaanxi Key Laboratory of Friction Welding Technologies, Xi’an 710072 (China); Wang, Xincheng [Shaanxi Key Laboratory of Friction Welding Technologies, Xi’an 710072 (China); Xie, Yan [School of Materials Science and Engineering, Tianjin University, Tianjin 300072 (China)

2016-04-15

Graphical abstract: - Highlights: • The wetting angle of lead free solder on Cu was reduced by surface microstructure. • The wetting form of Sn-Ag-Cu solder on Cu was “non-composite surface”. • The experimental results had a sound fit with the theoretical calculation. - Abstract: In order to reduce or even replace the use of Sn-Pb solder in electronics industry, the laser-textured surface microstructures were used to enhance the wetting behavior of lead free solder during soldering. According to wetting theory and Sn-Ag-Cu lead free solder performance, we calculated and designed four microcosmic structures with the similar shape and different sizes to control the wetting behavior of lead free solder. The micro-structured surfaces with different dimensions were processed on copper plates by fiber femtosecond laser, and the effect of microstructures on wetting behavior was verified experimentally. The results showed that the wetting angle of Sn-Ag-Cu solder on the copper plate with microstructures decreased effectively compared with that on the smooth copper plate. The wetting angles had a sound fit with the theoretical values calculated by wetting model. The novel method provided a feasible route for adjusting the wetting behavior of solders and optimizing solders system.

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery.

Directory of Open Access Journals (Sweden)

Ahmad Chaddad

Full Text Available This paper proposes to characterize the continuum of colorectal cancer (CRC using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma.In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG filter, discrete wavelets (DW and gray level co-occurrence matrices (GLCM. To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models.Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01. Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%.These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images.

Ageing effects on the wettability behavior of laser textured silicon

International Nuclear Information System (INIS)

Nunes, B.; Serro, A.P.; Oliveira, V.; Montemor, M.F.; Alves, E.; Saramago, B.; Colaco, R.

2011-01-01

In the present work we investigate the ageing of acid cleaned femtosecond laser textured silicon surfaces. Changes in the surface structure and chemistry were analysed by Rutherford backscattering spectrometry (RBS) and X-ray photoelectron spectroscopy (XPS), in order to explain the variation with time of the water contact angles of the laser textured surfaces. It is shown that highly hydrophobic silicon surfaces are obtained immediately after laser texturing and cleaning with acid solutions (water contact angle > 120 o ). However these surfaces are not stable and ageing leads to a decrease of the water contact angle which reaches a value of 80 o . XPS analysis of the surfaces shows that the growth of the native oxide layer is most probably responsible for this behavior.

Fast wettability transition from hydrophilic to superhydrophobic laser-textured stainless steel surfaces under low-temperature annealing

Science.gov (United States)

Ngo, Chi-Vinh; Chun, Doo-Man

2017-07-01

Recently, the fabrication of superhydrophobic metallic surfaces by means of pulsed laser texturing has been developed. After laser texturing, samples are typically chemically coated or aged in ambient air for a relatively long time of several weeks to achieve superhydrophobicity. To accelerate the wettability transition from hydrophilicity to superhydrophobicity without the use of additional chemical treatment, a simple annealing post process has been developed. In the present work, grid patterns were first fabricated on stainless steel by a nanosecond pulsed laser, then an additional low-temperature annealing post process at 100 °C was applied. The effect of 100-500 μm step size of the textured grid upon the wettability transition time was also investigated. The proposed post process reduced the transition time from a couple of months to within several hours. All samples showed superhydrophobicity with contact angles greater than 160° and sliding angles smaller than 10° except samples with 500 μm step size, and could be applied in several potential applications such as self-cleaning and control of water adhesion.

Atomic Oxygen Erosion Yield Dependence Upon Texture Development in Polymers

Science.gov (United States)

Banks, Bruce A.; Loftus, Ryan J.; Miller, Sharon K.

2016-01-01

The atomic oxygen erosion yield (volume of a polymer that is lost due to oxidation per incident atom) of polymers is typically assumed to be reasonably constant with increasing fluence. However polymers containing ash or inorganic pigments, tend to have erosion yields that decrease with fluence due to an increasing presence of protective particles on the polymer surface. This paper investigates two additional possible causes for erosion yields of polymers that are dependent upon atomic oxygen. These are the development of surface texture which can cause the erosion yield to change with fluence due to changes in the aspect ratio of the surface texture that develops and polymer specific atomic oxygen interaction parameters. The surface texture development under directed hyperthermal attack produces higher aspect ratio surface texture than isotropic thermal energy atomic oxygen attack. The fluence dependence of erosion yields is documented for low Kapton H (DuPont, Wilmington, DE) effective fluences for a variety of polymers under directed hyperthermal and isotropic thermal energy attack.

Modelling with response surface methodology of the effects of egg yolk, egg white and sodium carbonate on some textural properties of beef patties.

Science.gov (United States)

Parlak, Ozgür; Zorba, Omer; Kurt, Sükrü

2014-04-01

This study was accomplished to determine the effects of egg yolk, egg white and sodium carbonate on textural properties of beef patties by using Central Composite Design of Response Surface Methodology. Meat patties were prepared using beef, lamb tail fat and spices. Effects of addition of egg yolk powder (0-1%), egg white powder (0-1%) and sodium carbonate (0-1%) on textural properties were studied by using a texture analyzer. The TPA and cutting force tests were measured in the samples. Effects of sodium carbonate were found to be significant (P  0.05). The levels of sodium carbonate up to 0.72% improved the textural properties of beef patties.

Fractographic classification in metallic materials by using 3D processing and computer vision techniques

Directory of Open Access Journals (Sweden)

Maria Ximena Bastidas-Rodríguez

2016-09-01

Full Text Available Failure analysis aims at collecting information about how and why a failure is produced. The first step in this process is a visual inspection on the flaw surface that will reveal the features, marks, and texture, which characterize each type of fracture. This is generally carried out by personnel with no experience that usually lack the knowledge to do it. This paper proposes a classification method for three kinds of fractures in crystalline materials: brittle, fatigue, and ductile. The method uses 3D vision, and it is expected to support failure analysis. The features used in this work were: i Haralick’s features and ii the fractal dimension. These features were applied to 3D images obtained from a confocal laser scanning microscopy Zeiss LSM 700. For the classification, we evaluated two classifiers: Artificial Neural Networks and Support Vector Machine. The performance evaluation was made by extracting four marginal relations from the confusion matrix: accuracy, sensitivity, specificity, and precision, plus three evaluation methods: Receiver Operating Characteristic space, the Individual Classification Success Index, and the Jaccard’s coefficient. Despite the classification percentage obtained by an expert is better than the one obtained with the algorithm, the algorithm achieves a classification percentage near or exceeding the 60 % accuracy for the analyzed failure modes. The results presented here provide a good approach to address future research on texture analysis using 3D data.

Texture recognition of medical images with the ICM method

International Nuclear Information System (INIS)

Kinser, Jason M.; Wang Guisong

2004-01-01

The Integrated Cortical Model (ICM) is based upon several models of the mammalian visual cortex and produces pulse images over several iterations. These pulse images tend to isolate segments, edges, and textures that are inherent in the input image. To create a texture recognition engine the pulse spectrum of individual pixels are collected and used to develop a recognition library. Recognition is performed by comparing pulse spectra of unclassified regions of images with the known regions. Because signatures are smaller than images, signature-based computation is quite efficient and parasites can be recognized quickly. The precision of this method depends on the representative of signatures and classification. Our experiment results support the theoretical findings and show perspectives of practical applications of ICM-based method. The advantage of ICM method is using signatures to represent objects. ICM can extract the internal features of objects and represent them with signatures. Signature classification is critical for the precision of recognition

Effects of textured insoles on balance in people with Parkinson's disease.

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Feng Qiu

Full Text Available BACKGROUND: Degradation of the somatosensory system has been implicated in postural instability and increased falls risk for older people and Parkinson's disease (PD patients. Here we demonstrate that textured insoles provide a passive intervention that is an inexpensive and accessible means to enhance the somatosensory input from the plantar surface of the feet. METHODS: 20 healthy older adults (controls and 20 participants with PD were recruited for the study. We evaluated effects of manipulating somatosensory information from the plantar surface of the feet using textured insoles. Participants performed standing tests, on two different surfaces (firm and foam, under three footwear conditions: 1 barefoot; 2 smooth insoles; and 3 textured insoles. Standing balance was evaluated using a force plate yielding data on the range of anterior-posterior and medial-lateral sway, as well as standard deviations for anterior-posterior and medial-lateral sway. RESULTS: On the firm surface with eyes open both the smooth and textured insoles reduced medial-lateral sway in the PD group to a similar level as the controls. Only the textured insole decreased medial-lateral sway and medial-lateral sway standard deviation in the PD group on both surfaces, with and without visual input. Greatest benefits were observed in the PD group while wearing the textured insoles, and when standing on the foam surface with eyes closed. CONCLUSIONS: Data suggested that textured insoles may provide a low-cost means of improving postural stability in high falls-risk groups, such as people with PD.

MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

Energy Technology Data Exchange (ETDEWEB)

Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J., E-mail: bje@mayo.edu [Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Coufalova, Lucie [Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Department of Neurosurgery of First Faculty of Medicine, Charles University in Prague, Military University Hospital, Prague 128 21 (Czech Republic); International Clinical Research Center, St. Anne’s University Hospital Brno, Brno 656 91 (Czech Republic); Lachance, Daniel H. [Department of Neurology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Parney, Ian F. [Department of Neurologic Surgery, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Carter, Rickey E. [Department of Health Sciences Research, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Buckner, Jan C. [Department of Medical Oncology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States)

2016-06-15

Purpose: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O{sup 6}-methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. Methods: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. Results: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. Conclusions: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.

Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature.

Science.gov (United States)

Shigeta, Hironori; Mashita, Tomohiro; Kikuta, Junichi; Seno, Shigeto; Takemura, Haruo; Ishii, Masaru; Matsuda, Hideo

2017-10-01

Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.

MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

International Nuclear Information System (INIS)

Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J.; Coufalova, Lucie; Lachance, Daniel H.; Parney, Ian F.; Carter, Rickey E.; Buckner, Jan C.

2016-01-01

Purpose: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O 6 -methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. Methods: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. Results: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. Conclusions: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.

Experimental and Numerical Investigation on Tribological Performance of Grooved Texture

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CHEN Ping

2016-06-01

Full Text Available In order to study the influence of the angle and arrangement forms of micro-grooves on the tribological performance of the contact surface, the finite element analysis software was used to simulate the grooved textures with different angles and arrangements. The YLP-20 laser processing system was used to process grooved texture on stainless steel disk surfaces, and the Tribometer (UMT-2 was also used to conduct tribological test under the condition of rotation. The results show that the numerical simulation values are basically consistent with experimental results of grooved textures, and the tribological performance of the friction pairs with textures is also improved. The grooved textures with different angles and arrangement forms have different influence on tribological performance of friction pairs. When the friction velocity is less than 300r/min, the parallel texture with 0° has smaller friction coefficients. While the friction velocity is larger than 300r/min, the parallel texture with 90° has a better ability of reducing friction. Therefore, different grooved textures should be chosen according to operation conditions.

Nanosecond laser texturing of uniformly and non-uniformly wettable micro structured metal surfaces for enhanced boiling heat transfer

Energy Technology Data Exchange (ETDEWEB)

Zupančič, Matevž, E-mail: matevz.zupancic@fs.uni-lj.si; Može, Matic; Gregorčič, Peter; Golobič, Iztok

2017-03-31

Highlights: • Surfaces with periodically changed wettability were produced by a ns marking laser. • Heat transfer was investigated on uniformly and non-uniformly wettable surfaces. • Microporous surfaces with non-uniform wettability enhance boiling heat transfer. • The most bubble nucleations were observed in the vicinity of the microcavities. • Results agree with the predictions of the nucleation criteria. - Abstract: Microstructured uniformly and non-uniformly wettable surfaces were created on 25-μm-thin stainless steel foils by laser texturing using a marking nanosecond Nd:YAG laser (λ = 1064 nm) and utilizing various laser fluences and scan line separations. High-speed photography and high-speed IR thermography were used to investigate nucleate boiling heat transfer on the microstructured surfaces. The most pronounced results were obtained on a surface with non-uniform microstructure and non-uniform wettability. The obtained results show up to a 110% higher heat transfer coefficients and 20–40 times higher nucleation site densities compared to the untextured surface. We show that the number of active nucleation sites is significantly increased in the vicinity of microcavities that appeared in areas with the smallest (10 μm) scan line separation. Furthermore, this confirms the predictions of nucleation criteria and proves that straightforward, cost-effective nanosecond laser texturing allows the production of cavities with diameters of up to a few micrometers and surfaces with non-uniform wettability. Additionally, this opens up important possibilities for a more deterministic control over the complex boiling process.

Exploiting High Resolution Multi-Seasonal Textural Measures and Spectral Information for Reedbed Mapping

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Alex Okiemute Onojeghuo

2016-02-01

Full Text Available Reedbeds across the UK are amongst the most important habitats for rare and endangered birds, wildlife and organisms. However, over the past century, this valued wetland habitat has experienced a drastic reduction in quality and spatial coverage due to pressures from human related activities. To this end, conservation organisations across the UK have been charged with the task of conserving and expanding this threatened habitat. With this backdrop, the study aimed to develop a methodology for accurate reedbed mapping through the combined use of multi-seasonal texture measures and spectral information contained in high resolution QuickBird satellite imagery. The key objectives were to determine the most effective single-date (autumn or summer and multi-seasonal QuickBird imagery suitable for reedbed mapping over the study area; to evaluate the effectiveness of combining multi-seasonal texture measures and spectral information for reedbed mapping using a variety of combinations; and to evaluate the most suitable classification technique for reedbed mapping from three selected classification techniques, namely maximum likelihood classifier, spectral angular mapper and artificial neural network. Using two selected grey-level co-occurrence textural measures (entropy and angular second moment, a series of experiments were conducted using varied combinations of single-date and multi-seasonal QuickBird imagery. Overall, the results indicate the multi-seasonal pansharpened multispectral bands (eight layers combined with all eight grey level co-occurrence matrix texture measures (entropy and angular second moment computed using windows 3 × 3 and 7 × 7 produced the optimal reedbed (76.5% and overall classification (78.1% accuracies using the maximum likelihood classifier technique. Using the optimal 16 layer multi-seasonal pansharpened multispectral and texture combined image dataset, a total reedbed area of 9.8 hectares was successfully mapped over the

Laser texturing of Hastelloy C276 alloy surface for improved hydrophobicity and friction coefficient

Science.gov (United States)

Yilbas, B. S.; Ali, H.

2016-03-01

Laser treatment of Hastelloy C276 alloy is carried out under the high pressure nitrogen assisting gas environment. Morphological and metallurgical changes in the laser treated layer are examined using the analytical tools including, scanning electron and atomic force microscopes, X-ray diffraction, energy dispersive spectroscopy, and Fourier transform infrared spectroscopy. Microhardness is measured and the residual stress formed in the laser treated surface is determined from the X-ray data. The hydrophibicity of the laser treated surface is assessed using the sessile drop method. Friction coefficient of the laser treated layer is obtained incorporating the micro-tribometer. It is found that closely spaced laser canning tracks create a self-annealing effect in the laser treated layer and lowers the thermal stress levels through modifying the cooling rates at the surface. A dense structure, consisting of fine size grains, enhances the microhardness of the surface. The residual stress formed at the surface is compressive and it is in the order of -800 MPa. Laser treatment improves the surface hydrophobicity significantly because of the formation of surface texture composing of micro/nano-pillars.

HEp-2 Cell Classification Using Shape Index Histograms With Donut-Shaped Spatial Pooling

DEFF Research Database (Denmark)

Larsen, Anders Boesen Lindbo; Vestergaard, Jacob Schack; Larsen, Rasmus

2014-01-01

We present a new method for automatic classification of indirect immunoflourescence images of HEp-2 cells into different staining pattern classes. Our method is based on a new texture measure called shape index histograms that captures second-order image structure at multiple scales. Moreover, we...... datasets. Our results show that shape index histograms are superior to other popular texture descriptors for HEp-2 cell classification. Moreover, when comparing to other automated systems for HEp-2 cell classification we show that shape index histograms are very competitive; especially considering...

Filter and Filter Bank Design for Image Texture Recognition

Energy Technology Data Exchange (ETDEWEB)

Randen, Trygve

1997-12-31

The relevance of this thesis to energy and environment lies in its application to remote sensing such as for instance sea floor mapping and seismic pattern recognition. The focus is on the design of two-dimensional filters for feature extraction, segmentation, and classification of digital images with textural content. The features are extracted by filtering with a linear filter and estimating the local energy in the filter response. The thesis gives a review covering broadly most previous approaches to texture feature extraction and continues with proposals of some new techniques. 143 refs., 59 figs., 7 tabs.

Quantitative characterization of texture used for identification of eggs of bovine parasitic nematodes

DEFF Research Database (Denmark)

Sommer, C.

1998-01-01

This study investigates the use of texture, i.e. the grey level variation in digital images, as a basis for identification of strongylid eggs. Texture features were defined by algorithms applied to digital images of eggs from the bovine parasitic nematodes, Ostertagia ostertagi, Cooperia oncophora...... criterion based on these ten texture features, an average of 91.2% of eggs from the three species were correctly classified. All O. radiatum eggs were correctly classified, 11.8% of O. ostertagi and C. oncophora were reciprocally misclassified, and 2.9% of O. ostertagi were identified as O. radiatum. When...... the ten texture features were used singly an average of 51.2 to 37.9% of the species could be classified correctly. When texture was used together with the shape and size features, a higher percentage of eggs were correctly classified compared with the classification based on either texture, or shape...

Hyperspectral image classification based on local binary patterns and PCANet

Science.gov (United States)

Yang, Huizhen; Gao, Feng; Dong, Junyu; Yang, Yang

2018-04-01

Hyperspectral image classification has been well acknowledged as one of the challenging tasks of hyperspectral data processing. In this paper, we propose a novel hyperspectral image classification framework based on local binary pattern (LBP) features and PCANet. In the proposed method, linear prediction error (LPE) is first employed to select a subset of informative bands, and LBP is utilized to extract texture features. Then, spectral and texture features are stacked into a high dimensional vectors. Next, the extracted features of a specified position are transformed to a 2-D image. The obtained images of all pixels are fed into PCANet for classification. Experimental results on real hyperspectral dataset demonstrate the effectiveness of the proposed method.

Identification and classification of similar looking food grains

Science.gov (United States)

Anami, B. S.; Biradar, Sunanda D.; Savakar, D. G.; Kulkarni, P. V.

2013-01-01

This paper describes the comparative study of Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers by taking a case study of identification and classification of four pairs of similar looking food grains namely, Finger Millet, Mustard, Soyabean, Pigeon Pea, Aniseed, Cumin-seeds, Split Greengram and Split Blackgram. Algorithms are developed to acquire and process color images of these grains samples. The developed algorithms are used to extract 18 colors-Hue Saturation Value (HSV), and 42 wavelet based texture features. Back Propagation Neural Network (BPNN)-based classifier is designed using three feature sets namely color - HSV, wavelet-texture and their combined model. SVM model for color- HSV model is designed for the same set of samples. The classification accuracies ranging from 93% to 96% for color-HSV, ranging from 78% to 94% for wavelet texture model and from 92% to 97% for combined model are obtained for ANN based models. The classification accuracy ranging from 80% to 90% is obtained for color-HSV based SVM model. Training time required for the SVM based model is substantially lesser than ANN for the same set of images.

Effect of dental tool surface texture and material on static friction with a wet gloved fingertip.

Science.gov (United States)

Laroche, Charles; Barr, Alan; Dong, Hui; Rempel, David

2007-01-01

Hand injuries are an important cause of pain and disability among dentists and dental hygienists and may be due to the high pinch forces involved in periodontal work. The pinch forces required to perform scaling may be reduced by increasing the friction between the tool and fingers. The purpose of this study was to determine whether modifying the tool material, surface texture, or glove type altered the coefficient of static friction for a wet gloved finger. Seven tools with varying surface topography were machined from 13 mm diameter stainless steel and Delrin and mounted to a 6-component force plate. The textures tested were a fine, medium and coarse diamond knurled pattern and a medium and fine annular pattern (concentric rings). Thirteen subjects pulled their gloved, wet thumb pad along the long axis of the tool while maintaining a normal force of 40 N. Latex and nitrile gloves were tested. The coefficient of static friction was calculated from the shear force history. The mean coefficients of static friction ranged from 0.20 to 0.65. The coefficient of static friction was higher for a smooth tool of Delrin than one of stainless steel. Differences in the coefficient of static friction were observed between the coarse and medium knurled patterns and the fine knurled and annular patterns. Coefficients of static friction were higher for the nitrile glove than the latex glove for tools with texture. These findings may be applied to the design of hand tools that require fine motor control with a wet, gloved hand.

Fine Resolution Probabilistic Land Cover Classification of Landscapes in the Southeastern United States

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Joseph St. Peter

2018-03-01

Full Text Available Land cover classification provides valuable information for prioritizing management and conservation operations across large landscapes. Current regional scale land cover geospatial products within the United States have a spatial resolution that is too coarse to provide the necessary information for operations at the local and project scales. This paper describes a methodology that uses recent advances in spatial analysis software to create a land cover classification over a large region in the southeastern United States at a fine (1 m spatial resolution. This methodology used image texture metrics and principle components derived from National Agriculture Imagery Program (NAIP aerial photographic imagery, visually classified locations, and a softmax neural network model. The model efficiently produced classification surfaces at 1 m resolution across roughly 11.6 million hectares (28.8 million acres with less than 10% average error in modeled probability. The classification surfaces consist of probability estimates of 13 visually distinct classes for each 1 m cell across the study area. This methodology and the tools used in this study constitute a highly flexible fine resolution land cover classification that can be applied across large extents using standard computer hardware, common and open source software and publicly available imagery.

Extracting Corresponding Point Based on Texture Synthesis for Nearly Flat Textureless Object Surface

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Min Mao

2015-01-01

Full Text Available Since the image feature points are always gathered at the range with significant intensity change, such as textured portions or edges of an image, which can be detected by the state-of-the-art intensity based point-detectors, there is nearly no point in the areas of low textured detected by classical interest-point detectors. In this paper we describe a novel algorithm based on affine transform and graph cut for interest point detecting and matching from wide baseline image pairs with weakly textured object. The detection and matching mechanism can be separated into three steps: firstly, the information on the large textureless areas will be enhanced by adding textures through the proposed texture synthesis algorithm TSIQ. Secondly, the initial interest-point set is detected by classical interest-point detectors. Finally, graph cuts are used to find the globally optimal set of matching points on stereo pairs. The efficacy of the proposed algorithm is verified by three kinds of experiments, that is, the influence of point detecting from synthetic texture with different texture sample, the stability under the different geometric transformations, and the performance to improve the quasi-dense matching algorithm, respectively.

Textured ZnO thin films by RF magnetron sputtering

CERN Document Server

Ginting, M; Kang, K H; Kim, S K; Yoon, K H; Park, I J; Song, J S

1999-01-01

Textured thin films ZnO has been successfully grown by rf magnetron sputtering method using a special technique of introducing a small amount of water and methanol on the deposition chamber. The grain size of the textured surface is highly dependent on the argon pressure during the deposition. The pressure in this experiment was varied from 50 mTorr down to 5 mTorr and the highest grain size of the film is obtained at 5 mTorr. The total transmittance of the films are more than 85% in the wavelength of 400 to 800 nm, and haze ratio of about 14% is obtained at 400 nm wavelength. Beside the textured surface, these films also have very low resistivity, which is lower than 1.4x10 sup - sup 3 OMEGA centre dot cm. X-ray analysis shows that the films with textured surface have four diffraction peaks on the direction of (110), (002), (101) and (112), while the non-textured films have only (110) and (002) peaks. Due to the excellent characteristics of this film, it will make the film very good TCO alternatives for the ...

A new scheme for urban impervious surface classification from SAR images

Science.gov (United States)

Zhang, Hongsheng; Lin, Hui; Wang, Yunpeng

2018-05-01

Urban impervious surfaces have been recognized as a significant indicator for various environmental and socio-economic studies. There is an increasingly urgent demand for timely and accurate monitoring of the impervious surfaces with satellite technology from local to global scales. In the past decades, optical remote sensing has been widely employed for this task with various techniques. However, there are still a range of challenges, e.g. handling cloud contamination on optical data. Therefore, the Synthetic Aperture Radar (SAR) was introduced for the challenging task because it is uniquely all-time- and all-weather-capable. Nevertheless, with an increasing number of SAR data applied, the methodology used for impervious surfaces classification remains unchanged from the methods used for optical datasets. This shortcoming has prevented the community from fully exploring the potential of using SAR data for impervious surfaces classification. We proposed a new scheme that is comparable to the well-known and fundamental Vegetation-Impervious surface-Soil (V-I-S) model for mapping urban impervious surfaces. Three scenes of fully polarimetric Radsarsat-2 data for the cities of Shenzhen, Hong Kong and Macau were employed to test and validate the proposed methodology. Experimental results indicated that the overall accuracy and Kappa coefficient were 96.00% and 0.8808 in Shenzhen, 93.87% and 0.8307 in Hong Kong and 97.48% and 0.9354 in Macau, indicating the applicability and great potential of the new scheme for impervious surfaces classification using polarimetric SAR data. Comparison with the traditional scheme indicated that this new scheme was able to improve the overall accuracy by up to 4.6% and Kappa coefficient by up to 0.18.

Investigation of the biofouling properties of several algae on different textured chemical modified silicone surfaces

Energy Technology Data Exchange (ETDEWEB)

Xu, Jihai [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Zhao, Wenjie, E-mail: zhaowj@nimte.ac.cn [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Peng, Shusen; Zeng, Zhixiang; Zhang, Xin [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Wu, Xuedong, E-mail: xdwu@nimte.ac.cn [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Xue, Qunji [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China)

2014-08-30

Highlights: • Engineered pillars, pits and grooves spaced 3–12 μm apart were fabricated on siloxane modified acrylic resin films. • The effect of feature size, geometry, and wettability on the settlement of different algae was evaluated. • The feature size and geometry displayed a substantial correlation with the antifouling properties. • A comparatively physical fouling deterrent mechanism was analyzed. - Abstract: Engineered pillars, pits and grooves spaced 3, 6, 9 and 12 μm apart were fabricated on siloxane modified acrylic resin films. The effect of feature size, geometry, and wettability on the settlement of different algae was evaluated. These films showed various antifouling performances to Ulothrix, Closterium and Navicula. For Navicula (length: 10–12 μm), the feature size and geometry displayed a substantial correlation with the antifouling properties. The film with pillars spaced 3 μm reduced Navicula settlement by 73% compared to the control surface. For Closterium (length: 45–55 μm), their responses were governed by the same underlying thermodynamic principles as wettability, the largest reduction in Closterium, 81%, was obtained on the surface with grooves spaced 12 μm apart. For Ulothrix (length: 5–8 mm), the surface also showed the best antifouling performance, the reduction ratio of the settlement on the surface with grooves spaced 12 μm apart could even reach 92%. At last, physical fouling deterrent mechanisms for the films with various textures were analyzed in detail. The feature size and geometry display a substantial correlation with the antifouling properties when the size of fouling algae is close to the textures. With the increasing size for algae, antifouling performance was getting better on surface with pillars or grooves because the algae are bridged between two or more features other than stabilizing its entire mass on one single feature or able to settle between features.

Investigation of the biofouling properties of several algae on different textured chemical modified silicone surfaces

International Nuclear Information System (INIS)

Xu, Jihai; Zhao, Wenjie; Peng, Shusen; Zeng, Zhixiang; Zhang, Xin; Wu, Xuedong; Xue, Qunji

2014-01-01

Highlights: • Engineered pillars, pits and grooves spaced 3–12 μm apart were fabricated on siloxane modified acrylic resin films. • The effect of feature size, geometry, and wettability on the settlement of different algae was evaluated. • The feature size and geometry displayed a substantial correlation with the antifouling properties. • A comparatively physical fouling deterrent mechanism was analyzed. - Abstract: Engineered pillars, pits and grooves spaced 3, 6, 9 and 12 μm apart were fabricated on siloxane modified acrylic resin films. The effect of feature size, geometry, and wettability on the settlement of different algae was evaluated. These films showed various antifouling performances to Ulothrix, Closterium and Navicula. For Navicula (length: 10–12 μm), the feature size and geometry displayed a substantial correlation with the antifouling properties. The film with pillars spaced 3 μm reduced Navicula settlement by 73% compared to the control surface. For Closterium (length: 45–55 μm), their responses were governed by the same underlying thermodynamic principles as wettability, the largest reduction in Closterium, 81%, was obtained on the surface with grooves spaced 12 μm apart. For Ulothrix (length: 5–8 mm), the surface also showed the best antifouling performance, the reduction ratio of the settlement on the surface with grooves spaced 12 μm apart could even reach 92%. At last, physical fouling deterrent mechanisms for the films with various textures were analyzed in detail. The feature size and geometry display a substantial correlation with the antifouling properties when the size of fouling algae is close to the textures. With the increasing size for algae, antifouling performance was getting better on surface with pillars or grooves because the algae are bridged between two or more features other than stabilizing its entire mass on one single feature or able to settle between features

Texture and microstructure analysis of epitaxial oxide layers prepared on textured Ni-12wt%Cr tapes

Energy Technology Data Exchange (ETDEWEB)

Huehne, R; Kursumovic, A; Tomov, R I; Glowacki, B A [Department of Materials Science and IRC in Superconductivity, University of Cambridge, Pembroke Street, Cambridge, CB2 3QZ (United Kingdom); Holzapfel, B [Institut fuer Festkoerper- und Werkstoffforschung, Helmholtzstrasse 20, 01069 Dresden (Germany); Evetts, J E [Department of Materials Science and IRC in Superconductivity, University of Cambridge, Pembroke Street, Cambridge, CB2 3QZ (United Kingdom)

2003-05-07

Oxide layers for the preparation of YBa{sub 2}Cu{sub 3}O{sub 7-x} coated conductors were grown on highly textured Ni-12wt%Cr tapes in pure oxygen using surface oxidation epitaxy at temperatures between 1000 deg. C and 1300 deg. C. Microstructural investigations revealed a layered oxide structure. The upper layer consists mainly of dense cube textured NiO. This is followed by a porous layer containing NiO and NiCr{sub 2}O{sub 4} particles. A detailed texture analysis showed a cube-on-cube relationship of the NiCr{sub 2}O{sub 4} spinel to the metal substrate. Untextured Cr{sub 2}O{sub 3} particles in a nickel matrix were found in a third layer arising from internal oxidation of the alloy. A high surface roughness and mechanical instability of the oxide were observed, depending on oxidation temperature and film thickness. However, mechanically stable oxide layers have been prepared using an additional annealing step in a protective atmosphere. Additionally, mechanical polishing or a second buffer layer, which grows with a higher smoothness, may be applied to reduce the surface roughness for coated conductor applications.

Plasma-nitriding assisted micro-texturing into stainless steel molds

Directory of Open Access Journals (Sweden)

Aizawa Tatsuhiko

2015-01-01

Full Text Available Micro-texturing has grown up to be one of the most promising procedures. This related application required for large-area, fine micro-texturing onto the stainless steel mold materials. A new method other than laser-machining, micro-milling or micro-EDM was awaited for further advancement of this micro-texturing. In the present paper, a plasma nitriding assisted micro-texturing was developed to make various kinds of micro-patterns onto the martensitic stainless steels. First, original patterns were printed onto the surface of substrate by using the ink-jet printer. Then, the masked substrate was subjected to high density plasma nitriding; the un-masked surfaces were nitrided to have higher hardness. This nitrided substrate was further treated by sand-blasting to selectively dig the soft, masked surfaces. Finally, the micro-patterned martensitic stainless steel substrate was fabricated as a mold to duplicate these micro-patterns onto the work materials. The spatial resolution and depth profile controllability of this plasma nitriding assisted micro-texturing was investigated for variety of initial micro-patterns. The original size and dimension of initial micro-patterns were precisely compared with the three dimensional geometry of micro-textures after blasting treatment. The plastic cover case for smart cellular phones was employed to demonstrate how useful this processing is in practice.

Artificial intelligence systems based on texture descriptors for vaccine development.

Science.gov (United States)

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2011-02-01

The aim of this work is to analyze and compare several feature extraction methods for peptide classification that are based on the calculation of texture descriptors starting from a matrix representation of the peptide. This texture-based representation of the peptide is then used to train a support vector machine classifier. In our experiments, the best results are obtained using local binary patterns variants and the discrete cosine transform with selected coefficients. These results are better than those previously reported that employed texture descriptors for peptide representation. In addition, we perform experiments that combine standard approaches based on amino acid sequence. The experimental section reports several tests performed on a vaccine dataset for the prediction of peptides that bind human leukocyte antigens and on a human immunodeficiency virus (HIV-1). Experimental results confirm the usefulness of our novel descriptors. The matlab implementation of our approaches is available at http://bias.csr.unibo.it/nanni/TexturePeptide.zip.

SU-D-213AB-06: Surface Texture and Insertion Speed Effect on Needle Friction.

Science.gov (United States)

Abdullah, A; Golecki, C; Barnett, A; Moore, J

2012-06-01

High frictional forces between the needle surface and tissue cause tissue deflection which hinders accurate needle placement for procedures such as brachytherapy and needle biopsy. Accurate needle placement isimportant to maximize procedure efficacy. This work investigates how needle surface roughness and insertion speed affect the frictional forcebetween a needle and tissue. A friction experiment was conducted to measure the force of friction between bovine liver and three 11 gauge needles having Ra surface roughness of 3.43, 1.33, and 0.2 μm. Each of the three needles were mounted on a linear slide and were advanced and retracted through bovine liver at speeds of 50, 100, 150, and 200 mm/s for a total of 12 trials. In each trial the needle was advanced and retracted in 10 cycles producing a steady state insertion force and a steady state retraction force for each cycle. A force sensor connecting the needle to the linear slide recorded the resistance force of the needle sliding through the liver. The liver was mounted in a box with a pneumatic cylinder which compressed the liver sample by 11.65 kPa. The roughest needle (Ra = 3.43 μm) on average produced 68, 73, 74, and 73% lower friction force than the smoothest needle (Ra = 0.2 μm) for the speeds of 50, 100, 150, and 200mm/s, respectively. The second roughest needle (Ra = 1.33 μm) on average produced 25, 45, 60 and 64% lower friction force than the smoothest needle (Ra = 0.2 μm) for the speeds of 50, 100, 150, and 200 mm/s, respectively. Rougher needle surface texture and higher insertion speed reduced frictional forces between the tissue and the needle. Future studies will examine how frictional forces can be modeled and predicted given surface texture and insertion speed. © 2012 American Association of Physicists in Medicine.

Fiber vs Rolling Texture: Stress State Dependence for Cold-Drawn Wire

Science.gov (United States)

Zorina, M. A.; Karabanalov, M. S.; Stepanov, S. I.; Demakov, S. L.; Loginov, Yu. N.; Lobanov, M. L.

2018-02-01

The texture of the cold-drawn copper wire was investigated along the radius using electron backscatter diffraction. The complex fiber texture of the central region of the wire was considered as the rolling texture consisting of a set of preferred orientations. The texture of the periphery region was revealed to be similar to the shear texture. The orientation-dependent properties of the wire were proven to be determined by the texture of the near-surface layers.

Structural coloration of metallic surfaces with micro/nano-structures induced by elliptical vibration texturing

Science.gov (United States)

Yang, Yang; Pan, Yayue; Guo, Ping

2017-04-01

Creating orderly periodic micro/nano-structures on metallic surfaces, or structural coloration, for control of surface apparent color and optical reflectivity has been an exciting research topic over the years. The direct applications of structural coloration include color marking, display devices, and invisibility cloak. This paper presents an efficient method to colorize metallic surfaces with periodic micro/nano-gratings using elliptical vibration texturing. When the tool vibration is coupled with a constant cutting velocity, controlled periodic ripples can be generated due to the overlapping tool trajectory. These periodic ripples with a wavelength near visible spectrum can act as micro-gratings to introduce iridescent colors. The proposed technique also provides a flexible method for color marking of metallic surfaces with arbitrary patterns and images by precise control of the spacing distance and orientation of induced micro/nano-ripples. Theoretical analysis and experimental results are given to demonstrate structural coloration of metals by a direct mechanical machining technique.

Textural, surface, thermal and sorption properties of the functionalized activated carbons and carbon nanotubes

Directory of Open Access Journals (Sweden)

Nowicki Piotr

2015-12-01

Full Text Available Two series of functionalised carbonaceous adsorbents were prepared by means of oxidation and nitrogenation of commercially available activated carbon and multi-walled carbon nanotubes. The effect of nitrogen and oxygen incorporation on the textural, surface, thermal and sorption properties of the adsorbents prepared was tested. The materials were characterized by elemental analysis, low-temperature nitrogen sorption, thermogravimetric study and determination of the surface oxygen groups content. Sorptive properties of the materials obtained were characterized by the adsorption of methylene and alkali blue 6B as well as copper(II ions. The final products were nitrogen- and oxygen-enriched mesoporous adsorbents of medium-developed surface area, showing highly diverse N and O-heteroatom contents and acidic-basic character of the surface. The results obtained in our study have proved that through a suitable choice of the modification procedure of commercial adsorbents it is possible to produce materials with high sorption capacity towards organic dyes as well as copper(II ions.

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon

Science.gov (United States)

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E.; Moran, Emilio

2009-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin. PMID:19789716

A Comparative Study of Landsat TM and SPOT HRG Images for Vegetation Classification in the Brazilian Amazon.

Science.gov (United States)

Lu, Dengsheng; Batistella, Mateus; de Miranda, Evaristo E; Moran, Emilio

2008-01-01

Complex forest structure and abundant tree species in the moist tropical regions often cause difficulties in classifying vegetation classes with remotely sensed data. This paper explores improvement in vegetation classification accuracies through a comparative study of different image combinations based on the integration of Landsat Thematic Mapper (TM) and SPOT High Resolution Geometric (HRG) instrument data, as well as the combination of spectral signatures and textures. A maximum likelihood classifier was used to classify the different image combinations into thematic maps. This research indicated that data fusion based on HRG multispectral and panchromatic data slightly improved vegetation classification accuracies: a 3.1 to 4.6 percent increase in the kappa coefficient compared with the classification results based on original HRG or TM multispectral images. A combination of HRG spectral signatures and two textural images improved the kappa coefficient by 6.3 percent compared with pure HRG multispectral images. The textural images based on entropy or second-moment texture measures with a window size of 9 pixels × 9 pixels played an important role in improving vegetation classification accuracy. Overall, optical remote-sensing data are still insufficient for accurate vegetation classifications in the Amazon basin.

Characterisation of radiotherapy planning volumes using textural analysis

Energy Technology Data Exchange (ETDEWEB)

Nailon, William H.; Redpath, Anthony T.; McLaren, Duncan B. (Dept. of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Edinburgh (United Kingdom))

2008-08-15

Computer-based artificial intelligence methods for classification and delineation of the gross tumour volume (GTV) on computerised tomography (CT) and magnetic resonance (MR) images do not, at present, provide the accuracy required for radiotherapy applications. This paper describes an image analysis method for classification of distinct regions within the GTV, and other clinically relevant regions, on CT images acquired on eight bladder cancer patients at the radiotherapy planning stage and thereafter at regular intervals during treatment. Statistical and fractal textural features (N=27) were calculated on the bladder, rectum and a control region identified on axial, coronal and sagittal CT images. Unsupervised classification results demonstrate that with a reduced feature set (N=3) the approach offers significant classification accuracy on axial, coronal and sagittal CT image planes and has the potential to be developed further for radiotherapy applications, particularly towards an automatic outlining approach

Characterisation of radiotherapy planning volumes using textural analysis

International Nuclear Information System (INIS)

Nailon, William H.; Redpath, Anthony T.; McLaren, Duncan B.

2008-01-01

Computer-based artificial intelligence methods for classification and delineation of the gross tumour volume (GTV) on computerised tomography (CT) and magnetic resonance (MR) images do not, at present, provide the accuracy required for radiotherapy applications. This paper describes an image analysis method for classification of distinct regions within the GTV, and other clinically relevant regions, on CT images acquired on eight bladder cancer patients at the radiotherapy planning stage and thereafter at regular intervals during treatment. Statistical and fractal textural features (N=27) were calculated on the bladder, rectum and a control region identified on axial, coronal and sagittal CT images. Unsupervised classification results demonstrate that with a reduced feature set (N=3) the approach offers significant classification accuracy on axial, coronal and sagittal CT image planes and has the potential to be developed further for radiotherapy applications, particularly towards an automatic outlining approach

INLINING 3D RECONSTRUCTION, MULTI-SOURCE TEXTURE MAPPING AND SEMANTIC ANALYSIS USING OBLIQUE AERIAL IMAGERY

Directory of Open Access Journals (Sweden)

D. Frommholz

2016-06-01

Full Text Available This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for fac¸ade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the fac¸ades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM. The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA tool running a custom rule set to identify windows on the contained fac¸ade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric

Textural and surface characterization of cork-based sorbents for the removal of oil from water

OpenAIRE

Ariana Pintor; A.M. Silvestre-Albero; Catarina Ferreira; Joana Pereira; Vitor Vilar; Cidália Botelho; F. Rodríguez-Reinoso; Rui Boaventura

2013-01-01

This study evaluates the possibility of adding value to cork granulates, byproducts of cork processing, by using them as biosorbents and precursors of activated carbons. Activation was carried out by impregnation with phosphoric acid followed by pyrolysis under N2 flow. Furthermore, biosorbents were treated with a cationic surfactant and activated carbons were subject to a second pyrolysis under propene with the objective of improving hydrophobicity. Physico-chemical, textural, and surface ch...

Influence of laser parameters in surface texturing of Ti6Al4V and AA2024-T3 alloys

Science.gov (United States)

Ahuir-Torres, J. I.; Arenas, M. A.; Perrie, W.; de Damborenea, J.

2018-04-01

Laser texturing can be used for surface modification of metallic alloys in order to improve their properties under service conditions. The generation of textures is determined by the relationship between the laser processing parameters and the physicochemical properties of the alloy to be modified. In the present work the basic mechanism of dimple generation is studied in two alloys of technological interest, titanium alloy Ti6Al4V and aluminium alloy AA2024-T3. Laser treatment was performed using a pulsed solid state Nd: Vanadate (Nd: YVO4) laser with a pulse duration of 10 ps, operating at a wavelength of 1064 nm and 5 kHz repetition rate. Dimpled surface geometries were generated through ultrafast laser ablation while varying pulse energy between 1 μJ and 20 μJ/pulse and with pulse numbers from 10 to 200 pulses per spot. In addition, the generation of Laser Induced Periodic Surface Structures (LIPSS) nanostructures in both alloys, as well as the formation of random nanostructures in the impact zones are discussed.

Statistical analysis of texture in trunk images for biometric identification of tree species.

Science.gov (United States)

Bressane, Adriano; Roveda, José A F; Martins, Antônio C G

2015-04-01

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year. Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

TEXTURE ANALYSIS OF EXTRUDED APPLE POMACE - WHEAT SEMOLINA BLENDS

Directory of Open Access Journals (Sweden)

Ivan Bakalov

2016-03-01

Full Text Available Apple pomace - wheat semolina blends were extruded in a laboratory single screw extruder (Brabender 20 DN, Germany. Effects apple pomace content, moisture content, screw speed, and temperature of final cooking zone on texture of extrudates were studied applying response surface methodology. The texture characteristics of the extrudates were measured using a TA.XT Plus Texture Analyser, Stable Micro Systems.

Automated classifications of topography from DEMs by an unsupervised nested-means algorithm and a three-part geometric signature

Science.gov (United States)

Iwahashi, J.; Pike, R.J.

2007-01-01

An iterative procedure that implements the classification of continuous topography as a problem in digital image-processing automatically divides an area into categories of surface form; three taxonomic criteria-slope gradient, local convexity, and surface texture-are calculated from a square-grid digital elevation model (DEM). The sequence of programmed operations combines twofold-partitioned maps of the three variables converted to greyscale images, using the mean of each variable as the dividing threshold. To subdivide increasingly subtle topography, grid cells sloping at less than mean gradient of the input DEM are classified by designating mean values of successively lower-sloping subsets of the study area (nested means) as taxonomic thresholds, thereby increasing the number of output categories from the minimum 8 to 12 or 16. Program output is exemplified by 16 topographic types for the world at 1-km spatial resolution (SRTM30 data), the Japanese Islands at 270??m, and part of Hokkaido at 55??m. Because the procedure is unsupervised and reflects frequency distributions of the input variables rather than pre-set criteria, the resulting classes are undefined and must be calibrated empirically by subsequent analysis. Maps of the example classifications reflect physiographic regions, geological structure, and landform as well as slope materials and processes; fine-textured terrain categories tend to correlate with erosional topography or older surfaces, coarse-textured classes with areas of little dissection. In Japan the resulting classes approximate landform types mapped from airphoto analysis, while in the Americas they create map patterns resembling Hammond's terrain types or surface-form classes; SRTM30 output for the United States compares favorably with Fenneman's physical divisions. Experiments are suggested for further developing the method; the Arc/Info AML and the map of terrain classes for the world are available as online downloads. ?? 2006 Elsevier

Mechanical properties of ion-beam-textured surgical implant alloys

Science.gov (United States)

Weigand, A. J.

1977-01-01

An electron-bombardment Hg ion thruster was used as an ion source to texture surfaces of materials used to make orthopedic and/or dental prostheses or implants. The materials textured include 316 stainless steel, titanium-6% aluminum, 4% vanadium, and cobalt-20% chromium, 15% tungsten. To determine the effect of ion texturing on the ultimate strength and yield strength, stainless steel and Co-Cr-W alloy samples were tensile tested to failure. Three types of samples of both materials were tested. One type was ion-textured (the process also heats each sample to 300 C), another type was simply heated to 300 C in an oven, and the third type was untreated. Stress-strain diagrams, 0.2% offset yield strength data, total elongation data, and area reduction data are presented. Fatigue specimens of ion textured and untextured 316 stainless steel and Ti-6% Al-4% V were tested. Included as an ion textured sample is a Ti-6% Al-4% V sample which was ion machined by means of Ni screen mask so as to produce an array of 140 mu m x 140 mu m x 60 mu m deep pits. Scanning electron microscopy was used to characterize the ion textured surfaces.

Texturing of continuous LOD meshes with the hierarchical texture atlas

Science.gov (United States)

Birkholz, Hermann

2006-02-01

For the rendering of detailed virtual environments, trade-offs have to be made between image quality and rendering time. An immersive experience of virtual reality always demands high frame-rates with the best reachable image qual-ity. Continuous Level of Detail (cLoD) triangle-meshes provide an continuous spectrum of detail for a triangle mesh that can be used to create view-dependent approximations of the environment in real-time. This enables the rendering with a constant number of triangles and thus with constant frame-rates. Normally the construction of such cLoD mesh representations leads to the loss of all texture information of the original mesh. To overcome this problem, a parameter domain can be created, in order to map the surface properties (colour, texture, normal) to it. This parameter domain can be used to map the surface properties back to arbitrary approximations of the original mesh. The parameter domain is often a simplified version of the mesh to be parameterised. This limits the reachable simplification to the domain mesh which has to map the surface of the original mesh with the least possible stretch. In this paper, a hierarchical domain mesh is presented, that scales between very coarse domain meshes and good property-mapping.

An application to pulmonary emphysema classification based on model of texton learning by sparse representation

Science.gov (United States)

Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryojiro; Kanematsu, Masayuki; Fujita, Hiroshi

2012-03-01

We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

Controlling cell adhesion via replication of laser micro/nano-textured surfaces on polymers

Energy Technology Data Exchange (ETDEWEB)

Koufaki, Niki; Ranella, Anthi; Barberoglou, Marios; Psycharakis, Stylianos; Fotakis, Costas; Stratakis, Emmanuel [Institute of Electronic Structure and Laser (IESL), Foundation for Research and Technology-Hellas (FORTH), 711 10, Heraklion, Crete (Greece); Aifantis, Katerina E, E-mail: stratak@iesl.forth.gr [Lab of Mechanics and Materials, Aristotle University of Thessaloniki, Thessaloniki (Greece)

2011-12-15

The aim of this study is to investigate cell adhesion and viability on highly rough polymeric surfaces with gradient roughness ratios and wettabilities prepared by microreplication of laser micro/nano-textured Si surfaces. Negative replicas on polydimethylsiloxane as well as positive ones on a photocurable (organically modified ceramic) and a biodegradable (poly(lactide-co-glycolide)) polymer have been successfully reproduced. The final culture substrates comprised from forests of micron-sized conical spikes exhibiting a range of roughness ratios and wettabilities, was achieved by changing the laser fluence used to fabricate the original template surfaces. Cell culture experiments were performed with the fibroblast NIH/3T3 and PC12 neuronal cell lines in order to investigate how these surfaces are capable of modulating different types of cellular responses including, viability, adhesion and morphology. The results showed a preferential adhesion of both cell types on the microstructured surfaces compared to the unstructured ones. In particular, the fibroblast NIH/3T3 cells show optimal adhesion for small roughness ratios, independent of the surface wettability and polymer type, indicating a non-monotonic dependence of cell adhesion on surface energy. In contrast, the PC12 cells were observed to adhere well to the patterned surfaces independent of the roughness ratio and wettability. These experimental findings are correlated with micromechanical measurements performed on the unstructured and replicated surfaces and discussed on the basis of previous observations describing the relation of cell response to surface energy and rigidity.

Controlling cell adhesion via replication of laser micro/nano-textured surfaces on polymers

International Nuclear Information System (INIS)

Koufaki, Niki; Ranella, Anthi; Barberoglou, Marios; Psycharakis, Stylianos; Fotakis, Costas; Stratakis, Emmanuel; Aifantis, Katerina E

2011-01-01

The aim of this study is to investigate cell adhesion and viability on highly rough polymeric surfaces with gradient roughness ratios and wettabilities prepared by microreplication of laser micro/nano-textured Si surfaces. Negative replicas on polydimethylsiloxane as well as positive ones on a photocurable (organically modified ceramic) and a biodegradable (poly(lactide-co-glycolide)) polymer have been successfully reproduced. The final culture substrates comprised from forests of micron-sized conical spikes exhibiting a range of roughness ratios and wettabilities, was achieved by changing the laser fluence used to fabricate the original template surfaces. Cell culture experiments were performed with the fibroblast NIH/3T3 and PC12 neuronal cell lines in order to investigate how these surfaces are capable of modulating different types of cellular responses including, viability, adhesion and morphology. The results showed a preferential adhesion of both cell types on the microstructured surfaces compared to the unstructured ones. In particular, the fibroblast NIH/3T3 cells show optimal adhesion for small roughness ratios, independent of the surface wettability and polymer type, indicating a non-monotonic dependence of cell adhesion on surface energy. In contrast, the PC12 cells were observed to adhere well to the patterned surfaces independent of the roughness ratio and wettability. These experimental findings are correlated with micromechanical measurements performed on the unstructured and replicated surfaces and discussed on the basis of previous observations describing the relation of cell response to surface energy and rigidity.

Feasibility of opportunistic osteoporosis screening in routine contrast-enhanced multi detector computed tomography (MDCT) using texture analysis.

Science.gov (United States)

Mookiah, M R K; Rohrmeier, A; Dieckmeyer, M; Mei, K; Kopp, F K; Noel, P B; Kirschke, J S; Baum, T; Subburaj, K

2018-04-01

This study investigated the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. The results showed an acceptable reproducibility of texture features, and these features could discriminate healthy/osteoporotic fracture cohort with an accuracy of 83%. This aim of this study is to investigate the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. We performed texture analysis at the spine in routine MDCT exams and investigated the effect of intravenous contrast medium (IVCM) (n = 7), slice thickness (n = 7), the long-term reproducibility (n = 9), and the ability to differentiate healthy/osteoporotic fracture cohort (n = 9 age and gender matched pairs). Eight texture features were extracted using gray level co-occurrence matrix (GLCM). The independent sample t test was used to rank the features of healthy/fracture cohort and classification was performed using support vector machine (SVM). The results revealed significant correlations between texture parameters derived from MDCT scans with and without IVCM (r up to 0.91) slice thickness of 1 mm versus 2 and 3 mm (r up to 0.96) and scan-rescan (r up to 0.59). The performance of the SVM classifier was evaluated using 10-fold cross-validation and revealed an average classification accuracy of 83%. Opportunistic osteoporosis screening at the spine using specific texture parameters (energy, entropy, and homogeneity) and SVM can be performed in routine contrast-enhanced MDCT exams.

Study the effect of surface texturing on the stress distribution of UHMWPE as a bearing material during rolling motion

NARCIS (Netherlands)

Jamari, J.; Ismail, R.; Anwar, I.B.; Saputra, E.; Tauviqirrahman, M.; Heide, E. van der

2016-01-01

Tribological properties of materials used in biomedical implants will critically affect the performance of the implant. Ultra-high molecular weight polyethylene (UHMWPE) material is popular due to its great properties. Surface texturing is one of the methods to minimize friction and wear. In this

Laser surface texturing for high control of interference fit joint load bearing

Science.gov (United States)

Obeidi, M. Ahmed; McCarthy, E.; Brabazon, D.

2017-10-01

Laser beams attract the attention of researchers, engineers and manufacturer as they can deliver high energy with finite controlled processing parameters and heat affected zone (HAZ) on almost all kind of materials [1-3]. Laser beams can be generated in the broad range of wavelengths, energies and beam modes in addition to the unique property of propagation in straight lines with less or negligible divergence [3]. These features made lasers preferential for metal treatment and surface modification over the conventional machining and heat treatment methods. Laser material forming and processing is prosperous and competitive because of its flexibility and the creation of new solutions and techniques [3-5]. This study is focused on the laser surface texture of 316L stainless steel pins for the application of interference fit, widely used in automotive and aerospace industry. The main laser processing parameters applied are the power, frequency and the overlapping laser beam scans. The produced samples were characterized by measuring the increase in the insertion diameter, insertion and removal force, surface morphology and cross section alteration and the modified layer chemical composition and residual stresses.

Speech-Language and Nutritional Sciences in hospital environment: analysis of terminology of food consistencies classification.

Science.gov (United States)

Amaral, Ana Cláudia Fernandes; Rodrigues, Lívia Azevedo; Furlan, Renata Maria Moreira Moraes; Vicente, Laélia Cristina Caseiro; Motta, Andréa Rodrigues

2015-01-01

To verify if there is an agreement between speech-language pathologists and nutritionists about the classification of food textures used in hospitals and their opinions about the possible consequences of differences in this classification. This is a descriptive, cross-sectional study with 30 speech-language pathologists and 30 nutritionists who worked in 14 hospitals of public and/or private network in Belo Horizonte, Brazil. The professionals answered a questionnaire, prepared by the researchers, and classified five different foods, with and without theoretical direction. The data were analyzed using Fisher's exact and Z -tests to compare ratios with a 5% significance level. Both speech-language therapists (100%) and nutritionists (90%) perceive divergence in the classification and, 86.2% and 100% of them, respectively, believe that this difference may affect the patients' recovery. Aspiration risk was the most mentioned problem. For the general classification of food textures, most of the professionals (88.5%) suggested four to six terms. As to the terminology used in the classification of food presented without theoretical direction, the professionals cited 49 terms and agreed only in the solid and liquid classifications. With theoretical direction, the professionals also agreed in the classification of thick and thin paste. Both the professionals recognized divergences in the classification of food textures and the consequent risk of damage to patient's recovery. The use of theoretical direction increased the agreement between these professionals.

An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

Science.gov (United States)

Rasouli, Mahdi; Chen, Yi; Basu, Arindam; Kukreja, Sunil L; Thakor, Nitish V

2018-04-01

Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic

A study of the flow boiling heat transfer in a minichannel for a heated wall with surface texture produced by vibration-assisted laser machining

International Nuclear Information System (INIS)

Piasecka, Magdalena; Strąk, Kinga; Grabas, Bogusław; Maciejewska, Beata

2016-01-01

The paper presents results concerning flow boiling heat transfer in a vertical minichannel with a depth of 1.7 mm and a width of 16 mm. The element responsible for heating FC-72, which flowed laminarly in the minichannel, was a plate with an enhanced surface. Two types of surface textures were considered. Both were produced by vibration-assisted laser machining. Infrared thermography was used to record changes in the temperature on the outer smooth side of the plate. Two-phase flow patterns were observed through a glass pane. The main aim of the study was to analyze how the two types of surface textures affect the heat transfer coefficient. A two-dimensional heat transfer approach was proposed to determine the local values of the heat transfer coefficient. The inverse problem for the heated wall was solved using a semi-analytical method based on the Trefftz functions. The results are presented as relationships between the heat transfer coefficient and the distance along the minichannel length and as boiling curves. The experimental data obtained for the two types of enhanced heated surfaces was compared with the results recorded for the smooth heated surface. The highest local values of the heat transfer coefficient were reported in the saturated boiling region for the plate with the type 1 texture produced by vibration-assisted laser machining. (paper)

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

Science.gov (United States)

Ortiz-Ramón, Rafael; Larroza, Andrés; Ruiz-España, Silvia; Arana, Estanislao; Moratal, David

2018-05-14

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Prognostic Value and Reproducibility of Pretreatment CT Texture Features in Stage III Non-Small Cell Lung Cancer

Energy Technology Data Exchange (ETDEWEB)

Fried, David V. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas (United States); Tucker, Susan L. [Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Zhou, Shouhao [Division of Quantitative Sciences, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Liao, Zhongxing [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Mawlawi, Osama [Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas (United States); Ibbott, Geoffrey [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas (United States); Court, Laurence E., E-mail: LECourt@mdanderson.org [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas (United States)

2014-11-15

Purpose: To determine whether pretreatment CT texture features can improve patient risk stratification beyond conventional prognostic factors (CPFs) in stage III non-small cell lung cancer (NSCLC). Methods and Materials: We retrospectively reviewed 91 cases with stage III NSCLC treated with definitive chemoradiation therapy. All patients underwent pretreatment diagnostic contrast enhanced computed tomography (CE-CT) followed by 4-dimensional CT (4D-CT) for treatment simulation. We used the average-CT and expiratory (T50-CT) images from the 4D-CT along with the CE-CT for texture extraction. Histogram, gradient, co-occurrence, gray tone difference, and filtration-based techniques were used for texture feature extraction. Penalized Cox regression implementing cross-validation was used for covariate selection and modeling. Models incorporating texture features from the 33 image types and CPFs were compared to those with models incorporating CPFs alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Patients were stratified based on whether their predicted outcome was above or below the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients and quantified using concordance correlation coefficients (CCC). We compared models incorporating the reproducibility seen on test-retest scans to our original models and determined the classification reproducibility. Results: Models incorporating both texture features and CPFs demonstrated a significant improvement in risk stratification compared to models using CPFs alone for OS (P=.046), LRC (P=.01), and FFDM (P=.005). The average CCCs were 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility within our models yielded 80.4% (±3.7% SD), 78.3% (±4.0% SD), and 78