Application of texture analysis in tear film surface assessment based on videokeratoscopy

Purpose Videokeratoscopy images can be used for the non-invasive assessment of the tear film. In this work the applicability of an image processing technique, textural-analysis, for the assessment of the tear film in Placido disc images has been investigated. Methods In the presence of tear film thinning/break-up, the reflected pattern from the videokeratoscope is disturbed in the region of tear film disruption. Thus, the Placido pattern carries information about the stability of the underlying tear film. By characterizing the pattern regularity, the tear film quality can be inferred. In this paper, a textural features approach is used to process the Placido images. This method provides a set of texture features from which an estimate of the tear film quality can be obtained. The method is tested for the detection of dry eye in a retrospective dataset from 34 subjects (22-normal and 12-dry eye), with measurements taken under suppressed blinking conditions. Results To assess the capability of each texture-feature to discriminate dry eye from normal subjects, the receiver operating curve (ROC) was calculated and the area under the curve (AUC), specificity and sensitivity extracted. For the different features examined, the AUC value ranged from 0.77 to 0.82, while the sensitivity typically showed values above 0.9 and the specificity showed values around 0.6. Overall, the estimated ROCs indicate that the proposed technique provides good discrimination performance. Conclusions Texture analysis of videokeratoscopy images is applicable to study tear film anomalies in dry eye subjects. The proposed technique appears to have demonstrated its clinical relevance and utility.

Analysis of Strain Rates and Microstructural Evaluation during Metal Forming: Role of Surface Texture and Friction

The surface texture of a die plays an important role in friction during metal forming. In the present study, unidirectional and random surface finishes were produced on hardened steel plate surfaces. To understand the influence of surface texture on friction, experiments were conducted using Al-Mg alloy pins that slid against steel plates of different surface textures. In the sliding experiments, a high coefficient of friction was observed when the pins slid perpendicular to the unidirectional grinding marks and low friction occurred when the pins slid on the random surfaces. Finite element simulations were performed using the measured friction values to understand the stress and strain evolutions in the deforming material using dies with various friction. The numerical results showed that the states of stress and strain rates are strongly influenced by the friction at the interface and hence would influence the final material microstructure. To substantiate the numerical results, laboratory compression tests were conducted. Different surface textures were obtained in order to experience different friction values at different locations. A large variation in the microstructure at these locations was observed during experiments, verifying that surface texture and die friction significantly influence fundamental material formation behavior.

Digital image processing techniques for pavement macro-texture analysis

Road surface macro-texture is an indicator used to determine the skid resistance levels in pavements. Existing methods of quantifying macro-texture include the sand patch test and the laser profilometer. These methods utilise the 3D information of the pavement surface to extract the average texture depth. Recently, interest in image processing techniques as a quantifier of macro-texture has arisen, mainly using the Fast Fourier Transform (FFT). This paper reviews the FFT method, and then proposes two new methods, one using the autocorrelation function and the other using wavelets. The methods are tested on pictures obtained from a pavement surface extending more than 2km's. About 200 images were acquired from the surface at approx. 10m intervals from a height 80cm above ground. The results obtained from image analysis methods using the FFT, the autocorrelation function and wavelets are compared with sensor measured texture depth (SMTD) data obtained from the same paved surface. The results indicate that coefficients of determination (R2) exceeding 0.8 are obtained when up to 10% of outliers are removed.

Particulate texture image analysis with applications

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

Maximum Spreading of Liquid Drops Impacting on Groove-Textured Surfaces: Effect of Surface Texture

Maximum, spreading of liquid drops impacting on solid surfaces textured with unidirectional parallel grooves is studied for drop Weber number in the range 1-100 focusing on the role of texture geometry and wettability. The maximum spread factor of impacting drops measured perpendicular to grooves; beta(m,perpendicular to) is seen to be less than, that:measured parallel to grooves, beta(m,perpendicular to).The difference between beta(m,perpendicular to), and beta(m,parallel to) increases with drop impact velocity. This deviation of beta(m,perpendicular to) from beta(m,parallel to) is analyzed by considering the possible mechanisms, correspond, ing to experimental observations (1) impregnation of drop into the grooves, (2) convex shape of liquid vapor interface near contact line at maximum spreading, and (3) contact line pinning of spreading drop at the pillar edges by incorporating them into an energy conservation-based model. The analysis reveals that contact line pinning offers a physically meaningful justification of the observed: deviation of beta(m,perpendicular to) from beta(m,parallel to) compared to other possible candidates. A unified model, incorporating all the above-mentioned mechanisms, is formulated, which predicts beta(m,perpendicular to) on several groove-textured surfaces made of intrinsically hydrophilic and hydrophobic materials with an average error of 8.3%. The effect of groove-texture geometrical parameters,on maximum drop spreading is explained using this unified model. A special case of the unified model, with contact line pinning, absent, predicts beta(m,parallel to) with an average error of 6.3%.

Texture analysis of high resolution MRI allows discrimination between febrile and afebrile initial precipitating injury in mesial temporal sclerosis

A computational pipeline combining texture analysis and pattern classification algorithms was developed for investigating associations between high-resolution MRI features and histological data. This methodology was tested in the study of dentate gyrus images of sclerotic hippocampi resected from refractory epilepsy patients. Images were acquired using a simple surface coil in a 3.0T MRI scanner. All specimens were subsequently submitted to histological semiquantitative evaluation. The computational pipeline was applied for classifying pixels according to: a) dentate gyrus histological parameters and b) patients' febrile or afebrile initial precipitating insult history. The pipeline results for febrile and afebrile patients achieved 70% classification accuracy, with 78% sensitivity and 80% specificity [area under the reader observer characteristics (ROC) curve: 0.89]. The analysis of the histological data alone was not sufficient to achieve significant power to separate febrile and afebrile groups. Interesting enough, the results from our approach did not show significant correlation with histological parameters (which per se were not enough to classify patient groups). These results showed the potential of adding computational texture analysis together with classification methods for detecting subtle MRI signal differences, a method sufficient to provide good clinical classification. A wide range of applications of this pipeline can also be used in other areas of medical imaging. Magn Reson Med, 2012. (c) 2012 Wiley Periodicals, Inc.

Studies on friction and formation of transfer layer when Al-4Mg alloy pins slid at various numbers of cycles on steel plates of different surface texture

In the present investigation, various kinds of textures, namely, unidirectional, 8-ground, and random were attained on the die surfaces. Roughness of the textures was varied using different grits of emery papers or polishing powders. Then pins made of Al-4Mg alloys were slid against steel plates at various numbers of cycles, namely 1, 2, 6, 10 and 20 under both dry and lubricated conditions using an inclined pin-on-plate sliding tester. The morphologies of the worn surfaces of the pins and the formation of transfer layer on the counter surfaces were observed using a scanning electron microscope. Surface roughness parameters of the plate were measured using an optical profilometer. It was observed that the coefficient of friction and formation of transfer layer during the first few cycles depend on the die surface textures under both dry and lubricated conditions. It was also observed that under lubricated condition, the coefficient of friction decreases with number of cycles for all kinds of textures. However, under dry condition, it ecreases for unidirectional and 8-ground surfaces while for random surfaces it increases with number of cycles

Study of Friction and Transfer Layer Formation in Copper-Steel Tribo-System: Role of Surface Texture and Roughness Parameters

In the present investigation, experiments were conducted on a tribological couple-copper pin against steel plate-using an inclined pin-on-plate sliding tester to understand the role of surface texture and roughness parameters of the plate on the coefficient friction and transfer layer formation. Two surface characteristics of the steel plates-roughness and texture-were varied in the tests. It was observed that the transfer layer formation and the coefficient of friction along with its two components, namely, the adhesion and plowing, are controlled by the surface texture of the plate. The plowing component of friction was highest for the surface texture that promotes plane strain conditions while it was lowest for the texture that favors plane stress conditions at the interface. Dimensionless quantifiable roughness parameters were formulated to describe the degree of plowing and hence the plane strain/stress type deformations taking place at the asperity level.

Influence of roughness parameters and surface texture on friction during sliding of pure lead over 080 M40 steel

In the present investigation, tests were conducted on a tribological couple made of cylindrical lead pin with spherical tip against 080 M40 steel plates of different textures with varying roughness under both dry and lubricated conditions using an inclined pin-on-plate sliding tester. Surface roughness parameters of the steel plates were measured using optical profilometer. The morphologies of the worn surfaces of the pins and the formation of transfer layer on the counter surfaces were observed using a scanning electron microscope. It was observed that the coefficient of friction and the formation of transfer layer depend primarily on the surface texture of hard surfaces. A newly formulated non-dimensional hybrid roughness parameter called 'xi' (a product of number of peaks and maximum profile peak height) of the tool surface plays an important role in determining the frictional behaviour of the surfaces studied. The effect of surfaces texture on coefficient of friction was attributed to the variation of plowing component of friction, which in turn depends on the roughness parameter 'xi'.

Influence of surface texture and roughness parameters on friction and transfer layer formation during sliding of aluminium pin on steel plate

Surface texture of harder mating surfaces plays an important role during sliding against softer materials and hence the importance of characterizing the surfaces in terms of roughness parameters. In the present investigation, basic studies were conducted using inclined pin-on-plate sliding tester to understand the surface texture effect of hard surfaces on coefficient of friction and transfer layer formation. A tribological couple made of a super purity aluminium pin against steel plate was used in the tests. Two surface parameters of steel plates, namely roughness and texture, were varied in the tests. It was observed that the transfer layer formation and the coefficient of friction along with its two components, namely, the adhesion and plowing, are controlled by the surface texture and are independent of surface roughness (R-a). Among the various surface roughness parameters, the average or the mean slope of the profile was found to explain the variations best. Under lubricated conditions, stick-slip phenomena was observed, the amplitude of which depends on the plowing component of friction. The presence of stick-slip motion under lubricated conditions could be attributed to the molecular deformation of the lubricant component confined between asperities. (C) 2009 Elsevier B. V. All rights reserved.

Studies on friction and transfer layer: role of surface texture

Friction influences the nature of transfer layer formed at the interface between tool and metal during sliding. In the present investigation, experiments were conducted using “Inclined Scratch Tester” to understand the effect of surface texture of hard surfaces on coefficient of friction and transfer layer formation. EN8 steel flats were ground to attain surfaces of different textures with different roughness. Then super purity aluminium pins were scratched against the prepared steel flats. Scanning electron micrographs of the contact surfaces of pins and flats were used to reveal the morphology of transfer layer. It was observed that the coefficient of friction and the formation of transfer layer depend primarily on the texture of hard surfaces, but independent of surface roughness of hard surfaces. It was observed that on surfaces that promote plane strain conditions near the surface, the transfer of material takes place due to the plowing action of the asperities. But, on a surface that promotes plane stress conditions the transfer layer was more due to the adhesion component of friction. It was observed that the adhesion component increases for surfaces that have random texture but was constant for the other surfaces

Role of Surface Texture, Roughness, and Hardness on Friction During Unidirectional Sliding

In the present investigation, experiments were conducted by unidirectional sliding of pins made of FCC metals (Pb, Al, and Cu) with significantly different hardness values against the steel plates of various surface textures and roughness using an inclined pin-on-plate sliding apparatus in ambient conditions under both the dry and lubricated conditions. For a given material pair, it was observed that transfer layer formation and the coefficient of friction along with its two components, namely adhesion and plowing, are controlled by the surface texture of the harder mating surfaces and are less dependent of surface roughness (R (a)) of the harder mating surfaces. The effect of surface texture on the friction was attributed to the variation of the plowing component of friction for different surfaces. It was also observed that the variation of plowing friction as a function of hardness depends on surface textures. More specifically, the plowing friction varies with hardness of the soft materials for a given type of surface texture and it is independent of hardness of soft materials for other type of surface texture. These variations could be attributed to the extent of plane strain conditions taking place at the asperity level during sliding. It was also observed that among the surface roughness parameters, the mean slope of the profile, Delta (a), correlated best with the friction. Furthermore, dimensionless quantifiable roughness parameters were formulated to describe the degree of plowing taking place at the asperity level.