A Software Package For Biomedical Image Processing And Analysis

The present report is devoted to the study of distinct ionization waves in terms of temporally-, spatially-, and wavelength-resolved analyses. The study is based on the technique of two-dimension fast imaging. However, appropriately selected ultraviolet to near infrared optical filters are employed to capture the propagation of specific species and digital image processing techniques are applied to explore the recorded snapshots. N2(SPS), (FNS), He I, OH(A–X), and O I, i.e., emissive neutral and ionic species, are investigated. On the other hand, the propagation of the NO γ species is studied by means of laser-induced fluorescence spectroscopy, since the light intensity due to spontaneous emission of this species was not readily detectable. Digital image processing techniques are also applied for the NO γ case. The crucial role of the above species in fields like plasma biomedicine and material processing is extensively recognized, and the present work: (i) provides gathered information on the propagation of these species within the atmospheric air; and (ii) introduces image processing algorithms to extract information which otherwise would remain hidden or uncorrelated with other plasma parameters. The present results unveil specific emission patterns due to the propagation of the N2(SPS), (FNS), He I, OH(A–X), and O I species. The intensity patterns consist of a first peak located in the vicinity of the reactor orifice, a second peak moving away from the reactor orifice, and a continuum which couples the two peaks. However, the detailed features of each pattern depend on the type of species considered. The fluorescence of the NO γ species also suggests the division of the area downstream of the reactor orifice into two regions where distinct ionization-excitation effects take place. Propagation speeds of the species up to about 2 × 105 m s−1 were measured. Finally, qualitative correlation between the species propagation (as it is pronounced by the emission patterns) and the local electric field (as it was numerically calculated in a similar setup) is demonstrated.

A Landsat image of the multispectral scanner system covering an area lying between the Aqabah Gulf and the southern margin of the Dead Sea was analyzed by digital image processing techniques to delineate various geological and structural features of southwest Jordan area. Two major techniques in digital image processing were employed. They are preprocessing and enhancement, and their constituent treatment processes. Types of lithology, lineaments and topographic contrasts of southwest Jordan were used as test criteria. Results of comparison indicate that the combination of images processed by first principal component, second principal component and filtered first principal component as assigned to the hue, saturation and intensity system coordinates, respectively, provided better results than products of other digital techniques. Such good results enable geologists to map major lithologies, lineaments and other structural features effectively, as well as to assess topographic variations.

Neste trabalho, três diferentes técnicas para medir e monitorar a abertura de fissura e a posição da linha neutra são investigadas, sendo elas: strain gauges, análise digital de imagens e transdutores de deslocamento. Foram ensaiadas à flexão vigas de concreto reforçado com fibras de aço, nas quais foram monitoradas as cargas, os deslocamentos, as deformações à compressão, a abertura de fissura e a posição da linha neutra. Para as técnicas dos transdutores de deslocamento e da análise digital de imagens são apresentadas formulações matemáticas que devem ser empregadas para a correção dos valores de abertura de fissura e posição da linha neutra em função do deslocamento e do giro da viga durante o ensaio de flexão. Os resultados mostraram que as técnicas do strain gauges e dos transdutores de deslocamento foram mais eficientes para monitorar a posição da linha neutra. Na técnica da análise digital de imagens observou-se que um pequeno erro na medição das deformações nos pontos da grade de referência colada na lateral da viga ocasionou um grande erro no valor da posição da linha neutra medido. A abertura de fissura só foi possível ser medida por meio das técnicas dos transdutores de deslocamento e da análise digital de imagens, sendo que ambas apresentaram bons resultados. Verificou-se que a melhor técnica para monitorar tanto a posição da linha neutra quanto a abertura de fissura foi a dos transdutores de deslocamento, além de ser a técnica que apresenta maior facilidade de aplicação.

Digital image processing, post-processing, and data integration techniques as applied to airborne and satellite remotely sensed data for the purpose of extracting useful Earth resources information will be discussed in this chapter. Image preprocessing and data reduction tools are described in the previous chapter. The concepts discussed in this chapter include: • Image processing techniques such as unsupervised image classifications, supervised image classifications, neural network classifiers, simulated annealing classifiers, and fuzzy logic classification systems • The most widely accepted indices and land use/land cover classification schemes • Post-processing techniques such as filtering and change detection • Accuracy assessment and validation of results • Data integration and spatial modeling including examples of integration of remotely sensed data with other conventional survey and map form data for Earth observation purposes

Versatile image processing technique for fuel science: A review.

Schlieren imaging is a widely used technique for flow visualization in turbulence and combustion investigations due to its high sensitivity, flexibility and easiness in use. With the development of digital imaging and image processing techniques, it is possible to retrieve velocity measurements using time-resolved schlieren imaging sequences. In this paper, an optimization and parametric study has been conducted on a newly proposed schlieren motion estimation (SME) algorithm, based on the high speed schlieren images of a jet flow and the transient ignition process of impinging flames. The SME algorithm is optimized using a graduated non-convexity (GNC) computing scheme, which employs a three stage strategy by linearly combining a convex quadratic function and a slightly non-convex generalized Charbonnier function. The Euler–Lagrange equations have been derived, while the penalty function was separated so that penalty functions can be changed conveniently. Parametric investigations have been conducted to discuss the influence of weight parameters, while the suitable ranges have been obtained after intensive calculations. Comprehensive comparisons have been made between the SME and GNC-SME methods, which indicates that the GNC scheme can preserve the boundary well and avoid local divergence and over-smoothness at the same time. The suitable weight parameter range is also broadened by using the GNC technique. The better robustness of GNC-SME method makes it more adaptive to various applications.

The aim of this study was to provide important insights into the effects of four different dental polishing protocols (one single-step and one multi-step either followed or not by diamond paste polishing) on the 3D surface morphology of two representative dental resin-based nanocomposites (a nanofilled and a nanohybrid composite) by means of digital image analysis and processing techniques. The 3D surface morphology was investigated by atomic force microscopy. Segmentation, statistics of height distributions (described by statistical parameters, according to ISO 25178-2: 2012) and Minkowski functionals were applied to the images to characterize the spatial patterns of analyzed samples at micrometer scale. The nanofilled composite had significantly lower values of height parameters in comparison with nanohybrid one. Multi-step polishing protocol generated a statistically significant smoother finish for both tested materials, than one-step polishing protocol, even when it was followed by diamond paste polishing. Diamond paste polishing generated a statistically significant smoother surface of tested samples. This suite of surface analysis tools is important in the research and manufacture of these dental resin-based nanocomposites, where material surfaces have a key role in the functionality of objects.

Osteoporosis is a bone disease characterized by the loss of bone mass and by bone microarchitectural modifications. Bone mass (or bone density) can be precisely (and expensively) measured by specialized equipment (such as DEXA); microarchitectural modification are yet subjectively graded and evaluated by the radiologist. The goal of this research is to investigate the possible automatic detection of osteoporosis, based on digital image processing and analysis techniques (MPEG-7 image content description scheme) applied to digitized X-ray films of the calcaneum bones.

Edge detection is a fundamental and important tool in image processing and computer vision. The research topic discusses edge extraction of a digital image using various digital image processing techniques. Digital image edge identification using variety of digital image processing methods. The most popular technique for identifying discontinuities in intensity levels is edge detection. The actual image contains noise that could affect the digital image's quality. Some edge detection filters were used such as Canny, Sobel, and Prewitt. Laplace of Gaussian (LOG) edge recognition, Robert boundary detection, zero edge recognition and analysis. In light of the results of the comparison of edge filters the best edge filter had been obtained. Also, a hybrid method that merges between Canny filter and morphology operations were produced for edge detection. The research aims to reach an appropriate image purification by using different types of filters and to reduce distortions at the edges of the image and to determine which type of filter is the best. As well as, a comparison operation is applied between the traditional method and the hybrid method. Following the results explained by the filters used and displaying the resulting images. The results evaluated from hybrid filter show that this method is optimal than the traditional filters based on the Blind/Reference less Image Spatial Quality Evaluator (BRISQUE) with a value equals 43.43. A smaller score indicates better perceptual quality. Also, the edged images quality consequences from the traditional filters were measured by this metric. The results produced from the traditional filters prove that the best filter for edge image detection is Canny filter based on Blind/Reference less Image Spatial Quality Evaluator (BRISQUE) that reaches 46.01. In addition, the correlation coefficient was estimated to find which of the resulting images are better and closer to the original image. While for correlation coefficient the better filter was Prewitt filter with 0.3133 value. This study program was applied under the MATLAB R2020b system.

Kinetics of polymer crystallisation

High precision identification of feature points is an important technology and one of the bases of computer vision, image analysis and image processing. In the practical applications, the feature points can not be identified easily in various conditions of light illumination, visual angle, texture, and perspective projection. And in many cases, the size of feature point is small, the context is uncertain and the shape of feature point is different from each other. According to the properties of actual vision images, a novel method of feature point identification using multi-scale detecting technology is presented. In this thesis, an automatic circle feature point detection system is developed based on digital image processing techniques, in which, the feature points are detected in two scales. In large-scale recognition, the image pre-processing is carried out to reduce the impact of image noise, and the feature points with various shape deformation can be found out. And then, the founded points are checked along with small scale detecting. The relationship of the points and their mappings in three dimensional space is obtained and used to judge if the point is a real feature point one by one. Thus the deformed feature points in various perspective projection conditions can be recognized correctly. Experimental results show that this approach for feature points identification is not only fast but also robust. The proposed technology is a kind of useful method for contour extraction and feature points identification in the fields of computer vision and image analysis.

We have investigated the sites of microtubule (MT) assembly in neurons during axon growth by taking advantage of the relationship between the proportion of tyrosinated alpha-tubulin (tyr-tubulin) in MTs and their age. Specifically, young (newly assembled) MTs contain more tyr-tubulin than older (more long-lived) MTs. To quantify the relative proportion of tyr-tubulin in MTs, cultured rat sympathetic neurons were permeabilized under conditions that stabilize existing MTs and remove unassembled tubulin. The MTs were then double-stained with antibodies to tyr-tubulin (as a measure of the amount of tyr-tubulin in MTs) and to beta-tubulin (as a measure of total MT mass), using immunofluorescence procedures. Cells were imaged with a cooled charge-coupled device camera and the relative proportion of tyr-tubulin in the MTs was quantified by computing the ratio of the tyr-tubulin fluorescence to the beta-tubulin fluorescence using a novel application of digital image processing and analysis techniques. The amount of tyr-tubulin in the MTs was highest in the cell body and at the growth cone; peak ratios in these two regions were approximately 10-fold higher than for the axon shaft. Moving out from the cell body into the axon, the tyr-tubulin content declined over an average distance of 40 microns to reach a constant low value within the axon shaft and then rose again more distally, over an average distance of 110 microns, to reach a peak at the growth cone (average axon length = 358 microns). These observations indicate that newly assembled MTs are concentrated in the proximal and distal regions of growing axons and therefore that the cell body and growth cone are the most active sites of MT assembly dynamics in neurons that are actively extending axons.

Microscopy is one of the most important techniques in microbial ecology, since this is the most direct approach to examine the microbe's world from its own perspective and spatial scale. The value of quantitative microscopy in studies of microbial ecology can be increased even further when used in conjunction with computer assisted image analysis. There are two main advantages of using digital image processing and pattern recognition techniques in conjunction with microscopy for quantitative studies of microbial ecology. First, automatic image analysis reduces the amount of tedious work with microscopes needed to accurately quantify in situ morphological diversity, abundance and metabolic activity of microbes. Secondly, these techniques provide an important quantitative tool that can significantly enhance the polyphasic analysis of the structure, diversity, spatial features, and functions of complex microbial communities in situ without cultivation.

The generation processes of microscopic images in as Backscattered Scanning Electrons (BSE) are produced by complex interaction between incident electrons beam within the specimen. Different authors have correlated the energy of impact released with the mean atomic number (Z) of the phase to study, and deducing that the nature of the scattering events induced by the electron beam is strongly controlled by the Z value of them. If we compared the amount of electron backscattering with respect to response of the beam energies and so deduced a mathematical functions, for each specimen studied, and respectively by to digital images processing (based on the linear transformation of levels grey range in those energies) allows to sharpen in the discrimination and quantification of some phases in cements that, due to overlap processes, until now, could not be isolated. By means theses theoretical studios it is possible, for example, to identify interstitial cations that impinge on Z factor of phase deducing for each types of energies answer a series of mathematical functions, fitting a coefficient and across digital image techniques allows to sharpen in the discrimination and quantification of certain phases in cements that, as well, is noted in grey levels of digital image. In electron microscope have to settle down a strict work conditions (DW=10 mm, V0=20 KeV), and from a pattern specimen, found the grey level of image histogram for those working conditions, and fitting to the linear function, even if operated with BSE, the theoretic phases deduced from the EDX and the quantitative analysis of the stoichiometric formula. Given a coefficient (ç) its effective Z it's calculated; the deviation, therefore, gives the interstitial cations presence. With this tool, for example, the ettringite of gypsum is discriminates; or C-S-H products and the C3S. Once obtained the greys levels image of surface to examine and by means of threshold images process (a value of limit grey level or phase identification) he is immediate to obtain stereological relations (working with planar surfaces, which facilitate the treatment and the development of algorithms of mathematical morphology) and quantitative character phases of each phase

This article reviews the various image processing techniques in MATLAB and also hardware implementation in FPGA using Xilinx system generator. Image processing can be termed as processing of images using mathematical operations by using various forms of signal processing techniques. The main aim of image processing is to extract important features from an image data and process it in a desired manner and to visually enhance or to statistically evaluate the desired aspect of the image. This article provides an insight into the various approaches of Digital Image processing techniques in Matlab. This article also provides an introduction to FPGA and also a step by step tutorial in handling Xilinx System Generator. The Xilinx System Generator tool is a new application in image processing and offers a friendly environment design for the processing. This tool support software simulation, but the most important is that can synthesize in FPGAs hardware, with the parallelism, robust and speed, this features are essentials in image processing. Implementation of these algorithms on a FPGA is having advantage of using large memory and embedded multipliers. Advances in FPGA technology with the development of sophisticated and efficient tools for modelling, simulation and synthesis have made FPGA a highly useful platform.