In order to achieve extended life of asphalt pavement, one of key points is to achieve a good bonding between it’s components. This research paper presents findings on the topic of influence of polyethylene bitumen modification on the adhesion between bitumen and aggregate. A novel method of quantifying the bitumen coated area, based on computer image analysis, has been developed for this study. Two different methods of adhesion testing were employed, namely boiling water method and the rolling bottle method. Aggregates used in this study were granite and limestone. Based on 108 measurements, it was concluded that polyethylene modification has a negative impact on binder aggregate adhesion.

This paper presents application of optical microscope for evaluation of microtexture changes of coarse aggregate during simulated polishing in laboratory. Observations of the apparent changes on surfaces of seven different aggregates are presented. Simulation polishing of aggregate was performed in accordance with PN-EN 1097-8:2009. lmages of the aggregate surface were taken with the optical microscope in the reflection mode in particular stages of polishing. Digital images were analyzed. Standard deviation was determined on the basis of the histogram of intensities from digital images of the surfaces of aggregate grains which was assurned as the measure of changes in microtexture during simulated polishing (namely the σh parameter). Statistical analysis has shown that the changes of the σh parameter between the particular stages of polishing confirm certain trends related to the petrographic characteristic of the rocks. Aggregates which included minerals of similar hardness (granodiorite, dolomile, basalt) were more prone to polishing than gabbro and postglacial. Regeneration of the microtexture, the recovery to its original asperity, occurred in the case of quartz sandstone and steelmaking slag.

The paper presents test results for the assessment of the tracer content in a three-component (green peas, sorghum, maize) feed mixture that is based on the fluorescent method. The homogeneity of mixtures was determined on the basis of the maize content (as the key component), which was treated with fluorescent substance: tinopal, rhodamine B, uranine and eosin. The key components were wet-treated with fluorescent substances with different concentrations. Feed components were mixed in a vertical funnel-flow mixer. 10 samples were collected from each mixed batch. Samples were placed in a chamber equipped with UV light and, then, an image recorded as BMP file was generated. The image was analysed by means of the software programme Patan. On the basis of the analyses conducted, data on the maize content marked with a fluorescent marker were obtained. Additionally, the content of the key component was determined in a conventional manner – using an analytical scale. Results indicate the possibility of using this method for homogeneity assessment of the three-component grain mixture. From these tests, fluorescent substances that can be applied in the case of maize as a key component, together with their minimum concentrations, were identified: tinopal 0.3%, rhodamine B 0.001%.

The article proposes a method for measuring discomfort glare which uses numerical description of the phenomenon in the form of a digital luminance distribution map recorded on a CCD array. Essential procedures for determining partial quantities which are necessary for calculation of UGR index are discussed in detail, along with techniques for measuring position index and size of light sources, with regard to the parameters of the registering system and coordinates of the images of the sources on the array.

An automated method for crack identification and quantitative description of crack systems in concrete was developed in order to aid a service life assessment of concrete elements in structures. Flat polished specimens for crack analysis were impregnated with epoxy resin containing fluorescent dye. The examination of the crack system was performed in ultraviolet light using a stereomicroscope and an Image Pro Plus image analysis system on specimens cored out of several concrete structures. The laboratory tests were performed on cast specimens to establish correlations between water penetration and chloride diffusion and crack system parameters. The analysis of cracks in concrete cores taken from structures resulted in interesting conclusions based on the crack width distribution and crack localization with respect to steel reinforcement. The method was found very effective to support standard concrete diagnostics methods.

Monitoring of activated sludge flocs may provide important information for effective operation and control of wastewater treatment. The research objective is to demonstrate methodology for activated sludge image processing aimed to describe morphological characteristics of activated sludge flocs. The proposed software- -based method was presented and verified by analysis of several activated sludge samples. The results show high efficiency of image segmentation and floc recognition of more than 94% floc components. The analysis of a series of 50 pictures gives rapid and reliable results and can be performed in an automatic or semiautomatic mode. Given inherent heterogeneity of activated sludge flocs, multiple and repeated sample images capture (processing of 50 pictures at a time, repeated at least 4 times ) is recommended.

Analysis of the shape and location of abrasive grain tips as well as their changes during the grinding process, is the basis for forecasting the machining process results. This paper presents a methodology of using the watershed segmentation in identifying abrasive grains on the abrasive tool active surface. Some abrasive grain tips were selected to minimize the errors of detecting many tips on a single abrasive grain. The abrasive grains, singled out as a result of the watershed segmentation, were then analyzed to determine their geometric parameters. Moreover, the statistical parameters describing their locations on the abrasive tool active surface and the parameters characterizing intergranular spaces were determined.

The mechanical characteristics of the railway superstructure are related to the properties of the ballast, and especially to the particle size distribution of its grains. Under the constant stress-strain of carriages, the ballast can deteriorate over time, and consequently it should properly be monitored for safety reasons. The equipment which currently monitors the railway superstructure (like the Italian diagnostic train Archimede) do not make any “quantitative” evaluation of the ballast. The aim of this paper is therefore to propose a new methodology for extracting railway ballast particle size distribution by means of the image processing technique. The procedure has been tested on a regularly operating Italian railway line and the results have been compared with those obtained from laboratory experiments, thus assessing how effective is the methodology which could potentially be implemented also in diagnostic trains in the near future.

Fractal analysis is one of the rapidly evolving branches of mathematics and finds its application in different analyses such as pore space description. It constitutes a new approach to the issue of their natural irregularity and roughness. To be properly applied, it should be encompassed by an error estimation. The article presents and verifies uncertainties along with imperfections connected with image analysis and expands on the possible ways of their correction. One of key aspects of such research is finding both appropriate place and the number of photos to take. A coarse- grained sandstone thin section was photographed and then pictures were combined into one, bigger image. Fractal parameters distributions show their change and suggest that the accurately gathered group of photos include both highly and less porous regions. Their amount should be representative and adequate to the sample. The resolution influence on the fractal dimension and lacunarity values was examined. For SEM limestone images obtained using backscattered electrons, magnification in the range of 120x to 2000x was used. Additionally, a single pore was examined. The acquired results point to the fact that the values of fractal dimension are similar to a wide range of magnifications, while lacunarity changes each time. This is connected with changing homogeneity of the image. The article also undertakes a problem of determining fractal parameters spatial distribution based on binarization. The available methods assume that it is carried out after or before the image division into rectangles to create fractal dimension and lacunarity values for interpolation. An individual binarization, although time consuming, provides better results that resemble reality to a closer degree. It is not possible to define a single, correct methodology of error elimination. A set of hints has been presented that can improve results of further image analysis of pore space.

Surfactants can interfere with the biological wastewater treatment processes. They contribute to the changes in activated sludge floes structure. In order to quantify the influence of surfactants on sludge floes morphology the series of experiments in the flow continuous system were conducted. Sodium dodccyl sulphate, which belongs to the most ubiquitous anionic surfactant in everyday use, was selected to be the object of investigations. The results of its biodegradation in continuous flow system at influent concentration of 250 mg -dm' are presented. It turned out that SDS diminished the mean projected area of floes from 50 OOO to 15 OOO μm' with the increase of dilution rate from 0.029 to 0.192 h·1• At the same time the obtained data confirmed that there was a correlation between the morphological parameters of floes and other biomass indicators. The linear relation between mean projected area of floes and volatile suspended solids was found.

Endoscopy represents a commonly employed technique for canine enteropathies. Different trials in human intestinal endoscopy have suggested that the introduction of water for luminal distension, in place of air, improves the visualization of the mucosal texture and decreases pain.

The aim of the study was to compare water immersion (WI) vs. air insufflation (AI) during duodenoscopy in anesthetized dogs in terms of mucosal visualization and nociception.

Twenty-five dogs undergoing duodenoscopy were included. The same image of the descen- ding duodenum was recorded applying WI and AI. Each pair of images was analyzed using mor- phological skeletonization, an image entropy evaluation, and a subjective blind evaluation by three experienced endoscopists. To evaluate differences in nociception related to the procedure applied, heart rate and arterial blood pressure were measured before, during and after WI/AI. To compare the two methods, a t-test for paired data was applied for the image analysis, Fleiss’ Kappa evaluation for the subjective evaluation and a Friedman test for anesthetic parameters.

No differences were found between WI and AI using morphological skeletonization and entropy. The subjective evaluation identified the WI images as qualitatively better than the AI images, indicating substantial agreement between the operators. No differences in nociception were found.

The results of the study pointed out the absence of changes in pain response between WI and AI, likely due to the sufficient control of nociception by the anesthesia. Based on subjective evaluation, but not confirmed by the image analysis, WI provided better image quality than AI.

A new method for measurement of sludge blanket height (SBH) based on image analysis is presented. The proposed method uses a histogram back-projection algorithm to distinguish between the settling sludge and supernatant and can be used with sludge possessing different coloring characteristics both in the sludge color and the color of supernatant produced. Individual pixels in the acquired image are compared with a histogram of a representative sludge region. Therefore, the proposed method relies neither on the assumed shape of light intensity profile nor on the dominant sludge or supernatant color. Batch sedimentation tests are presented for different initial sludge concentrations and different background colors to simulate different sludge characteristics. Parameters of a settling velocity function are estimated based on the obtained results. Additionally, an algorithm is proposed that enables the zone settling velocity (ZSV) to be estimated before the batch sedimentation test is completed.

Image registration is a key component of various image processing operations which involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however inability to properly model object shape as well as contextual information had limited the attainable accuracy. In this paper, we propose a framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as Vector Machines, Cellular Neural Network (CNN), SIFT, coreset, and Cellular Automata. CNN has found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using corset optimization The salient features of this work are cellular neural network approach based SIFT feature point optimisation, adaptive resampling and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. System has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. Methodology also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

The paper discusses possible applications of the percolation theory in analysis of the microstructure images of polycrystalline materials.

Until now, practical use of this theory in metallographic studies has been an almost unprecedented practice. Observation of structures so

intricate with the help of this tool is far from the current field of its application. Due to the complexity of the problem itself, modern

computer programmes related with the image processing and analysis have been used. To enable practical implementation of the task

previously established, an original software has been created. Based on cluster analysis, it is used for the determination of percolation

phenomena in the examined materials. For comparative testing, two two-phase materials composed of phases of the same type (ADI

matrix and duplex stainless steel) were chosen. Both materials have an austenitic - ferritic structure. The result of metallographic image

analysis using a proprietary PERKOLACJA.EXE computer programme was the determination of the content of individual phases within

the examined area and of the number of clusters formed by these phases. The outcome of the study is statistical information, which

explains and helps in better understanding of the planar images and real spatial arrangement of the examined material structure. The results

obtained are expected to assist future determination of the effect that the internal structure of two-phase materials may have on a

relationship between the spatial structure and mechanical properties.

Image analysis allows to acquire a number of valuable quantitative informations on the observed structure and make appropriate conclusions. So far, a large part of analyzed images came only from light microscopes, where it was a possibility of accurately distinguish the different phases on the plane. However, the problem happened in the case of the observation of images obtained by scanning electron microscopy. In this case, the presence of various shades of gray, and the spaciousness of the image attained. To perform the analysis the matrix images of the ausferritic ductile iron were used. Full analysis was carried out using the computer program MicroMeter 1.03. Results obtained in the analysis were related directly to the results from X-ray diffraction. Obtained as a result of the analysis were related directly to the results from X-ray diffractometer. The following technique has weaknesses, including the misinterpretation by the operator microscope or program. After all, it was possible to obtain similar results to the result that has been obtained from X-ray diffractometer.

In this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones – the healthy blood cells (erythrocytes) and the pathologic ones (echinocytes). The separated blood cells are analysed in terms of their most important features by the eigenfaces method. The features are the basis for designing the neural network classifier, learned to distinguish between erythrocytes and echinocytes. As the result, the proposed system is able to analyse the smear blood images in a fully automatic way and to deliver information on the number and statistics of the red blood cells, both healthy and pathologic. The system was examined in two case studies, involving the canine and human blood, and then consulted with the experienced medicine specialists. The accuracy of classification of red blood cells into erythrocytes and echinocytes reaches 96%.

The paper provides statistical analysis of the photographs of four various granular materials (peas, pellets, triticale, wood chips). For analysis, the (parametric) ANOVA and the (nonparametric) Kruskal-Wallis tests were applied. Additionally, the (parametric) two-sample t-test and (non-parametric) Wilcoxon Rank-Sum Test for pairwise comparisons were performed. In each case, the Bonferroni correction was used. The analysis shows a statistical evidence of the presence of differences between the respective average discrete pixel intensity distributions (PID), induced by the histograms in each group of photos, which cannot be explained only by the existing differences among single granules of different materials. The proposed approach may contribute to the development of a fast inspection method for comparison and discrimination of granular materials differing from the reference material, in the production process.

The paper describes modification to Fm3–m (space group no. 225) lattice of aluminium based α-solid solution observed in Zn-Al alloys required to properly correlate quantitative data from X-ray diffraction analysis with results obtained from quantitative scanning electron microscopy image analysis and those predicted from Zn-Al binary phase diagram. Results suggests that 14 at.% of Zn as a solute atom should be introduced in crystal lattice of aluminium to obtain correct estimation of phase quantities determined by quantitative X-ray diffraction analysis. It was shown that this modification holds for Cu mould cast as well as annealed and water-cooled samples of Zn-3wt.%. Al and Zn-5wt.% Al.

In the vast archives and libraries of the world, countless historical documents are tucked away, often difficult to access. Thankfully, the digitization process has made it easier to view these invaluable records. However, simply digitizing them is not enough – the real challenge lies in making them searchable and computer-readable. Many of these documents were handwritten, which means they need to undergo handwriting recognition. The first step in this process is to divide the document into lines. This article introduces a solution to this problem using tensor voting. The algorithm starts by conducting voting on the binary image itself. Then, using the local maxima found in the resulting tensor field, the lines of text are precisely tracked and labeled. To ensure its effectiveness, the algorithm’s performance was tested on the data-set delivered by the organizers of the ICDAR 2009 competition and evaluated using the criteria from this contest.