Fractal analysis of eroded surfaces by digital image processing

Jet impingement erosion test rig has been used to erode titanium alloy specimens (Ti-4Al-4V). Eroded surface profiles have been obtained by vertical sectioning method for light microscopy observation. Mixed fractals have been measured from profile images by a digital image processing and analysis technique. The use of this technique allows glimpsing a quantitative correlation among material properties, fractal surface topography and erosion phenomena. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Quantitative fractography by digital image processing: NIH Image macro tools for stereo pair analysis and 3-D reconstruction

A set of NIH Image macro programs was developed to make qualitative and quantitative analyses from digital stereo pictures produced by scanning electron microscopes. These tools were designed for image alignment, anaglyph representation, animation, reconstruction of true elevation surfaces, reconstruction of elevation profiles, true-scale elevation mapping and, for the quantitative approach, surface area and roughness calculations. Limitations on time processing, scanning techniques and programming concepts are also discussed.

Quantitative characterization of multi-phase materials by digital image processing

An automatic image processing and analysis technique has been developed for quantitative characterization of multi-phase materials. For the development of this technique is used the Khoros system that offers the basic morphological tools and a flexible, visual programming language. These techniques are implemented in a highly user oriented image processing environment that allows the user to adapt each step of the processing to his special requirements.To illustrate the implementation and performance of this technique, images of two different materials are processed for microstructure characterization. The result is presented through the determination of volume fraction of the different phases or precipitates.

Quantitative fractography under light microscopy: A digital image processing approach

This work is an example of the improvement on quantitative fractography by means of digital image processing and light microscopy. Two techniques are presented to investigate the quantitative fracture behavior of Ti-4Al-4V heat-treated alloy specimens, under Charpy impact testing. The first technique is the Minkowski method for fractal dimension measurement from surface profiles, revealing the multifractal character of Ti-4Al-4V fracture. It was not observed a clear positive correlation of fractal values against Charpy energies for Ti-4Al-4V alloy specimens, due to their ductility, microstructural heterogeneities and the dynamic loading characteristics at region near the V-notch. The second technique provides an entire elevation map of fracture surface by extracting in-focus regions for each picture from a stack of images acquired at successive focus positions, then computing the surface roughness. Extended-focus reconstruction has been used to explain the behavior along fracture surface. Since these techniques are based on light microscopy, their inherent low cost is very interesting for failure investigations.

Identification of Landslide Scars in the Region of the Serra do Mar, São Paulo State, Brazil, Using Digital Image Processing and Spatial Analysis Tools

The objective of the present study, developed in a mountainous region in Brazil where many landslides occur, is to present a method for detecting landslide scars that couples image processing techniques with spatial analysis tools. An IKONOS image was initially segmented, and then classified through a Batthacharrya classifier, with an acceptance limit of 99%, resulting in 216 polygons identified with a spectral response similar to landslide scars. After making use of some spatial analysis tools that took into account a susceptibility map, a map of local drainage channels and highways, and the maximum expected size of scars in the study area, some features misinterpreted as scars were excluded. The 43 resulting features were then compared with visually interpreted landslide scars and field observations. The proposed method can be reproduced and enhanced by adding filtering criteria and was able to find new scars on the image, with a final error rate of 2.3%.

An image processing method for morphology characterization and pitting corrosion evaluation

A digital image processing and analysis method has been developed to classify shape and evaluate size and morphology parameters of corrosion pits. This method seems to be effective to analyze surfaces with low or high degree of pitting formation. Theoretical geometry data have been compared against experimental data obtained for titanium and aluminum alloys subjected to different corrosion tests. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Estimation of crowd density using image processing

Human beings perceive images through their properties, like colour, shape, size, and texture. Texture is a fertile source of information about the physical environment. Images of low density crowds tend to present coarse textures, while images of dense crowds tend to present fine textures. This paper describes a new technique for automatic estimation of crowd density, which is a part of the problem of automatic crowd monitoring, using texture information based on grey-level transition probabilities on digitised images. Crowd density feature vectors are extracted from such images and used by a self organising neural network which is responsible for the crowd density estimation. Results obtained respectively to the estimation of the number of people in a specific area of Liverpool Street Railway Station in London (UK) are presented.

Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

Assessment of the mechanics of a tissue-engineered rat trachea in an image-processing environment

OBJECTIVES: Despite the recent success regarding the transplantation of tissue-engineered airways, the mechanical properties of these grafts are not well understood. Mechanical assessment of a tissue-engineered airway graft before implantation may be used in the future as a predictor of function. The aim of this preliminary work was to develop a noninvasive image-processing environment for the assessment of airway mechanics.METHOD: Decellularized, recellularized and normal tracheas (groups DECEL, RECEL, and CONTROL, respectively) immersed in Krebs-Henseleit solution were ventilated by a small-animal ventilator connected to a Fleisch pneumotachograph and two pressure transducers (differential and gauge). A camera connected to a stereomicroscope captured images of the pulsation of the trachea before instillation of saline solution and after instillation of Krebs-Henseleit solution, followed by instillation with Krebs-Henseleit with methacholine 0.1 M (protocols A, K and KMCh, respectively). The data were post-processed with computer software and statistical comparisons between groups and protocols were performed.RESULTS: There were statistically significant variations in the image measurements of the medial region of the trachea between the groups (two-way analysis of variance [ANOVA], p<0.01) and of the proximal region between the groups and protocols (two-way ANOVA, p<0.01).CONCLUSIONS: The technique developed in this study is an innovative method for performing a mechanical assessment of engineered tracheal grafts that will enable evaluation of the viscoelastic properties of neo-tracheas prior to transplantation.

Classification of polymers insulators hydrophobicity basead on digital image processing

Although the hydrophobicity is usually an arduous parameter to be determined in the field, it has been pointed out as a good option to monitor aging of polymeric outdoor insulators. Concerning this purpose, digital image processing of photos taken from wet insulators has been the main technique nowadays. However, important challenges on this technique still remain to be overcome, such as; images from non-controlled illumination conditions can interfere on analyses and no existence of standard surfaces with different levels of hydrophobicity. In this paper, the photo image samples were digitally filtered to reduce the illumination influence, and hydrophobic surface samples were prepared from wetting silicon surfaces with solution of water-alcohol. Furthermore norevious studies triying to quantify and relate these properties in a mathematical function were found, that could be used in the field by the electrical companies. Based on such considerations, high quality images of countless hydrophobic surfaces were obtained and three different image processing methodologies, the fractal dimension and two Haralick textures descriptors, entropy and homogeneity, associated with several digital filters, were compared. The entropy parameter Haralick's descriptors filtered with the White Top-Hat filter presented the best result to classify the hydrophobicity.

Computational modelling of human stem cell-derived cardiomyocytes - Texture descriptors for biological image processing

This thesis investigates two distinct research topics. The main topic (Part I) is the computational modelling of cardiomyocytes derived from human stem cells, both embryonic (hESC-CM) and induced-pluripotent (hiPSC-CM). The aim of this research line lies in developing models of the electrophysiology of hESC-CM and hiPSC-CM in order to integrate the available experimental data and getting in-silico models to be used for studying/making new hypotheses/planning experiments on aspects not fully understood yet, such as the maturation process, the functionality of the Ca2+ hangling or why the hESC-CM/hiPSC-CM action potentials (APs) show some differences with respect to APs from adult cardiomyocytes. Chapter I.1 introduces the main concepts about hESC-CMs/hiPSC-CMs, the cardiac AP, and computational modelling. Chapter I.2 presents the hESC-CM AP model, able to simulate the maturation process through two developmental stages, Early and Late, based on experimental and literature data. Chapter I.3 describes the hiPSC-CM AP model, able to simulate the ventricular-like and atrial-like phenotypes. This model was used to assess which currents are responsible for the differences between the ventricular-like AP and the adult ventricular AP. The secondary topic (Part II) consists in the study of texture descriptors for biological image processing. Chapter II.1 provides an overview on important texture descriptors such as Local Binary Pattern or Local Phase Quantization. Moreover the non-binary coding and the multi-threshold approach are here introduced. Chapter II.2 shows that the non-binary coding and the multi-threshold approach improve the classification performance of cellular/sub-cellular part images, taken from six datasets. Chapter II.3 describes the case study of the classification of indirect immunofluorescence images of HEp2 cells, used for the antinuclear antibody clinical test. Finally the general conclusions are reported.

CT perfusion image processing: analysis of liver tumors

Perfusion CT imaging of the liver has potential to improve evaluation of tumour angiogenesis. Quantitative parameters can be obtained applying mathematical models to Time Attenuation Curve (TAC). However, there are still some difficulties for an accurate quantification of perfusion parameters due, for example, to algorithms employed, to mathematical model, to patient’s weight and cardiac output and to the acquisition system. In this thesis, new parameters and alternative methodologies about liver perfusion CT are presented in order to investigate the cause of variability of this technique. Firstly analysis were made to assess the variability related to the mathematical model used to compute arterial Blood Flow (BFa) values. Results were obtained implementing algorithms based on “ maximum slope method” and “Dual input one compartment model” . Statistical analysis on simulated data demonstrated that the two methods are not interchangeable. Anyway slope method is always applicable in clinical context. Then variability related to TAC processing in the application of slope method is analyzed. Results compared with manual selection allow to identify the best automatic algorithm to compute BFa. The consistency of a Standardized Perfusion Index (SPV) was evaluated and a simplified calibration procedure was proposed. At the end the quantitative value of perfusion map was analyzed. ROI approach and map approach provide related values of BFa and this means that pixel by pixel algorithm give reliable quantitative results. Also in pixel by pixel approach slope method give better results. In conclusion the development of new automatic algorithms for a consistent computation of BFa and the analysis and definition of simplified technique to compute SPV parameter, represent an improvement in the field of liver perfusion CT analysis.

Structural analysis of a UAV wing through image processing and FEM

Analisi strutturale dell’ala di un UAV (velivolo senza pilota a bordo), sviluppata usando varie metodologie: misurazioni sperimentali statiche e dinamiche, e simulazioni numeriche con l’utilizzo di programmi agli elementi finiti. L’analisi statica è stata a sua volta portata avanti seguendo due differenti metodi: la classica e diretta determinazione degli spostamenti mediante l’utilizzo di un catetometro e un metodo visivo, basato sull’elaborazione di immagini e sviluppato appositamente a tale scopo in ambiente Matlab. Oltre a ciò è stata svolta anche una analisi FEM volta a valutare l’errore che si ottiene affrontando il problema con uno studio numerico. Su tale modello FEM è stata svolta anche una analisi di tipo dinamico con lo scopo di confrontare tali dati con i dati derivanti da un test dinamico sperimentale per ottenere informazioni utili per una seguente possibile analisi aeroelastica.

BEYOND ROOTS ALONE: NOVEL METHODOLOGIES FOR ANALYZING COMPLEX SOIL AND MINIRHIZOTRON IMAGERY USING IMAGE PROCESSING AND GIS TOOLS

Quantifying belowground dynamics is critical to our understanding of plant and ecosystem function and belowground carbon cycling, yet currently available tools for complex belowground image analyses are insufficient. We introduce novel techniques combining digital image processing tools and geographic information systems (GIS) analysis to permit semi-automated analysis of complex root and soil dynamics. We illustrate methodologies with imagery from microcosms, minirhizotrons, and a rhizotron, in upland and peatland soils. We provide guidelines for correct image capture, a method that automatically stitches together numerous minirhizotron images into one seamless image, and image analysis using image segmentation and classification in SPRING or change analysis in ArcMap. These methods facilitate spatial and temporal root and soil interaction studies, providing a framework to expand a more comprehensive understanding of belowground dynamics.