Study of grey relational grade identification for ferrography based on characteristic analysis of wear debris

Attention has been focused on how to achieve intelligent automation in ferrographic diagnosis in order to overcome the subjectivity of the diagnosis process. The present paper reports on a technique of characteristic measurement developed on the basis of the VC++ 6.0 programming platform, with characteristic parameters such as area, roundness, and aspect ratio being extracted from images of wear debris based on digital image analysis. However, the extraction of characteristic parameters from a ferrographic image is not the ultimate purpose of ferrographic diagnosis. The wear particles should be classified into several pre‐decision categories and their statistical distribution should also be calculated. The grey relational grade theory is introduced in this paper as a way to recognise wear debris and a new software system has been developed to deal with the problems occurring in the automation of ferrographic diagnosis. It is shown that the identification rules can be used to treat some real wear debris images with generally satisfactory results.     

Reconstruction of optical pathlength distributions from images obtained by a wide-field differential interference contrast microscope

An image processing algorithm is presented to reconstruct optical pathlength distributions from images of nonabsorbing weak phase objects, obtained by a differential interference contrast (DIC) microscope, equipped with a charge-coupled device camera. The method is demonstrated on DIC images of transparent latex spheres and unstained bovine spermatozoa. The images were obtained with a wide-field DIC microscope, using monochromatic light. After image acquisition, the measured intensities were converted to pathlength differences. Filtering in the Fourier domain was applied to correct for the typical shadow-cast effect of DIC images. The filter was constructed using the lateral shift introduced in the microscope, and parameters describing the spectral distribution of the signal-to-noise ratio. By varying these parameters and looking at the resulting images, an appropriate setting for the filter parameters was found. In the reconstructed image each grey value represents the optical pathlength at that particular location, enabling quantitative analysis of object parameters using standard image processing techniques. The advantage of using interferometric techniques is that measurements can be done on transparent objects, without staining, enabling observations on living cells. Quantitative use of images obtained by a wide-field DIC microscope becomes possible with this technique, using relatively simple means.     

Characterization of the three-dimensional structure of a metallic foam during compressive deformation

X‐ray microtomography has been employed to collect three‐dimensional images of aluminium closed‐cell foam, enabling the internal structure to be characterized in three dimensions. An experimental technique and image analysis approach has been developed, and is described, in terms of the labelling of cells and the extraction of quantitative data such as the cell volume and cell compression. An in situ compressive deformation experiment has been performed on a single sample in order to illustrate the approach. The effect of the three‐dimensional cellular structure on the mechanisms of deformation suggests not only the position of large cell volumes to be very important in the local concentration of stress, but also the distribution of cell volumes of immediate neighbours.     

Strain mapping accuracy improvement using super‐resolution techniques

Super‐resolution (SR) software‐based techniques aim at generating a final image by combining several noisy frames with lower resolution from the same scene. A comparative study on high‐resolution high‐angle annular dark field images of InAs/GaAs QDs has been carried out in order to evaluate the performance of the SR technique. The obtained SR images present enhanced resolution and higher signal‐to‐noise (SNR) ratio and sharpness regarding the experimental images. In addition, SR is also applied in the field of strain analysis using digital image processing applications such as geometrical phase analysis and peak pairs analysis. The precision of the strain mappings can be improved when SR methodologies are applied to experimental images.     

An Investigation of Lubricant Film Thickness in Sliding Compliant Contacts

An optical interferometric technique has been used to investigate fluid film thickness in sliding, isoviscous elastohydrodynamic contacts (I-EHL). Monochromatic two-beam interferometry has been employed to map lubricant film thickness across a range of applied loads and entrainment speeds. The contact was formed between an elastomer sphere and plain glass disc, illuminated under red light, λ= 630 nm. Experimental work has employed sunflower oil and glycerol/water solutions as the test lubricants, due to their similar refractive indices and varying viscosity. A black-and-white-image-intensified camera has been employed to capture interference images and a computer processing technique used to analyse these images, pixel by pixel, and create film thickness maps based on their gray-scale intensity representations. Comparison of film thickness results to theoretical models shows reasonable qualitative agreement. Experimental results show both a reduced horseshoe, which is limited to the rear of the contact, and wedge-shaped film thickness profile within the Hertzian contact region. This is unlike conventional hard EHL contacts where the horseshoe-shaped pressure constriction extends around the contact toward the inlet. Experimental results suggest that film thickness profiles take on a convergent wedge shape similar to that used in many hydrodynamic bearings. It is likely that this wedge is largely responsible for generating fluid pressure and therefore the load-carrying capacity of the contact.     

Signal‐to‐noise ratio enhancement on SEM images using a cubic spline interpolation with Savitzky–Golay filters and weighted least squares error

A new technique based on cubic spline interpolation with Savitzky–Golay smoothing using weighted least squares error filter is enhanced for scanning electron microscope (SEM) images. A diversity of sample images is captured and the performance is found to be better when compared with the moving average and the standard median filters, with respect to eliminating noise. This technique can be implemented efficiently on real‐time SEM images, with all mandatory data for processing obtained from a single image. Noise in images, and particularly in SEM images, are undesirable. A new noise reduction technique, based on cubic spline interpolation with Savitzky–Golay and weighted least squares error method, is developed. We apply the combined technique to single image signal‐to‐noise ratio estimation and noise reduction for SEM imaging system. This autocorrelation‐based technique requires image details to be correlated over a few pixels, whereas the noise is assumed to be uncorrelated from pixel to pixel. The noise component is derived from the difference between the image autocorrelation at zero offset, and the estimation of the corresponding original autocorrelation. In the few test cases involving different images, the efficiency of the developed noise reduction filter is proved to be significantly better than those obtained from the other methods. Noise can be reduced efficiently with appropriate choice of scan rate from real‐time SEM images, without generating corruption or increasing scanning time.     

Structure similarity‐guided image binarization for automatic segmentation of epidermis surface microstructure images

Partitioning epidermis surface microstructure (ESM) images into skin ridge and skin furrow regions is an important preprocessing step before quantitative analyses on ESM images. Binarization segmentation is a potential technique for partitioning ESM images because of its computational simplicity and ease of implementation. However, even for some state‐of‐the‐art binarization methods, it remains a challenge to automatically segment ESM images, because the grey‐level histograms of ESM images have no obvious external features to guide automatic assessment of appropriate thresholds. Inspired by human visual perceptual functions of structural feature extraction and comparison, we propose a structure similarity‐guided image binarization method. The proposed method seeks for the binary image that best approximates the input ESM image in terms of structural features. The proposed method is validated by comparing it with two recently developed automatic binarization techniques as well as a manual binarization method on 20 synthetic noisy images and 30 ESM images. The experimental results show: (1) the proposed method possesses self‐adaption ability to cope with different images with same grey‐level histogram; (2) compared to two automatic binarization techniques, the proposed method significantly improves average accuracy in segmenting ESM images with an acceptable decrease in computational efficiency; (3) and the proposed method is applicable for segmenting practical EMS images. (Matlab code of the proposed method can be obtained by contacting with the corresponding author.)     

Study of hole-entry hybrid journal bearing system considering combined influence of thermal and elastic effects

A theoretical model is developed to study the performance of a hole-entry hybrid journal bearing system by considering variation of viscosity due to temperature rise of the lubricant in the analysis. The deformation of bush due to fluid-film pressure and temperature has been considered to establish the modified fluid-film profile. The journal temperature is computed on the basis of the fluid-film temperature. The relevant governing equations have been solved using the finite element method and a suitable iterative technique. The thermoelastohydrostatic performance of an orifice compensated symmetric and asymmetric hole-entry hybrid journal bearing configurations has been studied for the chosen bearing operating and geometric parameters. The results presented in the study indicate that the variation of viscosity due to temperature rise of the lubricant fluid-film have a quite appreciable influence on the static and dynamic performance of a hole-entry hybrid journal bearing system.     

A study on the behavior characteristics of diesel spray by using a high pressure injection system with common rail apparatus

The effects of change in injection pressure on spray structure in high temperature and pressure field have been investigated. The analysis of liquid and vapor phases of injected fuel is important for emissions control of diesel engines. Therefore, this work examines the evaporating spray structure using a constant volume vessel. The injection pressure is selected as the experimental parameter, is changed from 22 MPa to 112 MPa using a high pressure injection system (ECD-U2). Also, we conducted simulation study by modified KIVA-II code. The results of simulation study are compared with experimental results. The images of liquid and vapor phase for free spray were simultaneously taken by exciplex fluorescence method. As experimental results, the vapor concentration of injected fuel is leaner due to the increase of atomization in the case of the high injection pressure than in that of the low injection pressure. The calculated results obtained by modified KIVA-II code show good agreements with experimental results.     

A study on the behavior of evaporating diesel spray using LIEF measurement and kiva code

The effects of change in injection pressure on spray structure in high temperature and pressure field have been investigated. The analysis of liquid and vapor phases of injected fuel is important for emissions control of diesel engines. Therefore, this work examines the evaporating spray structure using a constant volume vessel. The injection pressure is selected as the experimental parameter, is changed from 400 bar to 800 bar by using a common rail injection system. Also, we conducted simulation study by modified KIVA-II code. The results of simulation study are compared with experimental results. The images of liquid and vapor phase for free spray were simultaneously taken by exciplex fluorescence method. As experimental results, the vapor concentration of injected fuel is leaner due to the increase of atomization in the case of the high injection pressure than in that of the low injection pressure. The calculated results obtained by modified KIVA-II code show good agreements with experimental results.     

An automated feedback system with the hybrid model of scoring and classification for solving over-segmentation problems in RNAi high content screening

Background: High content screening (HCS) via automated fluorescence microscopy is a powerful technology for generating cellular images that are rich in phenotypic information. RNA interference is a revolutionary approach for silencing gene expression and has become an important method for studying genes through RNA interference‐induced cellular phenotype analysis. The convergence of the two technologies has led to large‐scale, image‐based studies of cellular phenotypes under systematic perturbations of RNA interference. However, existing high content screening image analysis tools are inadequate to extract content regarding cell morphology from the complex images, thus they limit the potential of genome‐wide RNA interference high content screening screening for simple marker readouts. In particular, over‐segmentation is one of the persistent problems of cell segmentation; this paper describes a new method to alleviate this problem. Methods: To solve the issue of over‐segmentation, we propose a novel feedback system with a hybrid model for automated cell segmentation of images from high content screening. A Hybrid learning model is developed based on three scoring models to capture specific characteristics of over‐segmented cells. Dead nuclei are also removed through a statistical model. Results: Experimental validation showed that the proposed method had 93.7% sensitivity and 94.23% specificity. When applied to a set of images of F‐actin‐stained Drosophila cells, 91.3% of over‐segmented cells were detected and only 2.8% were under‐segmented. Conclusions: The proposed feedback system significantly reduces over‐segmentation of cell bodies caused by over‐segmented nuclei, dead nuclei, and dividing cells. This system can be used in the automated analysis system of high content screening images.     

Column ratio mapping: a processing technique for atomic resolution high-angle annular dark-field (HAADF) images

An image processing technique is presented for atomic resolution high-angle annular dark-field (HAADF) images that have been acquired using scanning transmission electron microscopy (STEM). This technique is termed column ratio mapping and involves the automated process of measuring atomic column intensity ratios in high-resolution HAADF images. This technique was developed to provide a fuller analysis of HAADF images than the usual method of drawing single intensity line profiles across a few areas of interest. For instance, column ratio mapping reveals the compositional distribution across the whole HAADF image and allows a statistical analysis and an estimation of errors. This has proven to be a very valuable technique as it can provide a more detailed assessment of the sharpness of interfacial structures from HAADF images. The technique of column ratio mapping is described in terms of a [110]-oriented zinc-blende structured AlAs/GaAs superlattice using the 1 angstroms-scale resolution capability of the aberration-corrected SuperSTEM 1 instrument.     

A modified formula for accurate determination of three‐dimensional birefringence of fiber using modified subfringe integration method

The development of the use of interferometric techniques in the study of the optical properties of materials encouraged many researchers to work on the derivation and development of the theoretical considerations and the equations used in the calculations of those properties. The form of these equations depends on the technique used and the cross section of the sample, and also on the method of calculating the optical path difference of light across the sample studied. A modified formula to calculate the three‐dimensional birefringence distribution of the fiber, without the need to determine the refractive indices of the fiber in the parallel and perpendicular directions, was presented. The phase distribution of the simulated and experiment interferograms was obtained using subfringe integration method. The results obtained from the new method were compared with the calculated results of a well‐known method (Z method) and the figures presented showed that the results of the two methods were close to each other.     

An ensemble classification of exudates in color fundus images using an evolutionary algorithm based optimal features selection

Atomic recognition of the Exudates (EXs), the major symbol of diabetic retinopathy is essential for automated retinal images analysis. In this article, we proposed a novel machine learning technique for early detection and classification of EXs in color fundus images. The major challenge observed in the classification technique is the selection of optimal features to reduce computational time and space complexity and to provide a high degree of classification accuracy. To address these challenges, this article proposed an evolutionary algorithm based solution for optimal feature selection, which accelerates the classification process and reduces computational complexity. Similarly, three well‐known classifiers that is, Naïve Bayes classifier, Support Vector Machine, and Artificial Neural Network are used for the classification of EXs. Moreover, an ensemble‐based classifier is used for the selection of best classifier on the basis of majority voting technique. Experiments are performed on three well‐known benchmark datasets and a real dataset developed at local Hospital. It has been observed that the proposed technique achieved an accuracy of 98% in the detection and classification of EXs in color fundus images.     

Analysis of rough line contacts operating under mixed elastohydrodynamic lubrication conditions

Heavily loaded machine elements, such as gears, usually operate in the mixed lubrication regime. Surface roughness has a significant effect on the pressure distribution, the subsurface stress field, and the friction coefficient. Based on the superposition of a dry rough and a fully flooded smooth contact, a mixed lubrication model has been developed. The roughness profile is assumed to be known. Surface deformation is calculated by taking into account the pressure distribution that is built up by asperity contacts, asperity interactions, and lubricant flow. Thermal and sliding effects are incorporated into the analysis. Non‐Newtonian lubricant behaviour is considered by using a power‐law rheological model. The pressure distribution, subsurface stress field, and friction coefficient were calculated from the model at several points along the contact path for an FZG type C gear pair. It was shown that a significant part of the load is carried by the contacting asperities. The position of the maximum shear stress is very close to the surface.     

Image enhancement for increased dot-counting efficiency in FISH

Background: The most commonly used molecular cytogenetic technique is fluorescence in situ hybridization (FISH). It has been widely applied in many areas of diagnosis and research, including pre‐natal and post‐natal screening of chromosomal aberrations, pre‐implantation genetic diagnosis, cancer cytogenetics, gene mapping, molecular pathology and developmental molecular biology. The analysis of FISH images consists of detecting fluorescent dots, after which the number of dots per cell can be counted or their relative positions can be measured. A major impediment in the analysis of FISH specimens is signal (dot) quality, which is influenced by the hybridization efficiency and/or the sensitivity of the camera that records the images. Method: In this paper, we present an approach to improve the efficiency of detecting fluorescent signals in FISH images by recovering the radiance map of the camera. This allows us to generate a high‐dynamic‐range image wherein an extended range of the sample radiance captured by the camera can be visualized at distinct intensity values. The resulting higher‐order numeric complexity of the transformed image is adjusted (or simplified) by examining the intensity distribution in each of the three colour channels (red, green and blue), and remapping the intensity values to generate a high‐contrast image with a lower‐order (compressed) dynamic range. The remapping is based on a criterion that optimizes the detection of the hybridized signals, allowing attenuation of saturated intensity values while amplifying low‐intensity signals. Results: A simple dot‐counting algorithm is used to automatically process 2000 FISH images. The images are taken for lymphocytes from cultured blood specimens for cytogenetic testing. Images are manually analyzed by an expert to obtain ground truth for dot counts. A quantitative analysis is performed by comparing results of automated dot detection on images before and after enhancement with the developed algorithms. In addition, common errors in dot counting due to split dots, dust, poor segmentation and overlapping signals are analyzed and the robustness of the developed approach against these errors evaluated. It is observed that dot‐detection efficiency is increased by an average of 9% across all colour channels while reducing errors in missed and false dot counts. Conclusions: Our proposed method and results demonstrate that dot‐counting specificity and sensitivity can be improved by pre‐processing and enhancing the image using the radiance curve of the camera and generating a high‐contrast, remapped high‐dynamic‐range image prior to using any algorithm for dot counting.     

Performance of new signal‐to‐noise ratio estimation for SEM images based on single image noise cross‐correlation

A new technique for estimation of signal‐to‐noise ratio in scanning electron microscope images is reported. The method is based on the image noise cross‐correlation estimation model recently developed. We derive the basic performance limits on a single image signal‐to‐noise ratio estimation using the Cramer–Rao inequality. The results are compared with those from existing estimation methods including the nearest neighbourhood (the simple method), the first order linear interpolator, and the autoregressive based estimator. The comparisons were made using several tests involving different images within the performance bounds. From the results obtained, the efficiency and accuracy of image noise cross‐correlation estimation technique is considerably better than the other three methods.     

Minimizing scanning electron microscope artefacts by filter design

A new type of non‐linear filter for digital images has been developed. By using distance transforms we estimate the average point spread function for a set of fibre cross‐sectional images. Then a fast filter technique, based on lookup tables for distance layers, attenuates the uneven background response from the scanning electron microscope. Compared to the convolution‐based techniques that we tried, this approach caused less blurring effects on our fibre images and also made the background pixels more homogeneous. The only assumption we make is that we can roughly segment the background pixels by using a pixel‐wise classifier. Although the assumption that the uneven background response can be described by a circular point spread function is only approximately true in the case discussed here, this method greatly attenuates the effect and provides a fast and general filtering method that can also be of use for other applications.