Texture and Colour in Image Analysis

Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews

Computer aided detection of defects in FRP bridge decks using infrared thermography

The objective of this research is to develop a turn-key system that is able to interface with the FLIR ThermaCAM S60 infrared camera and automatically capture and analyze defects in infrared images of FRP bridge decks. Infrared thermography is one of the nondestructive evaluation (NDE) techniques that are being used to locate defects (debonds and delaminations) in bridge components. It is a rapid data collection and interpretation technique having high sensitivity and reliability. Analysis of infrared images by human interpretation is dependent on the users knowledge and hence introduces ambiguity in the defect detection process.;This thesis investigates the use of an automated defect detection system to locate defects in infrared images of FRP bridge decks to eliminate/reduce human intervention. Air-filled and water-filled debonds were inserted between the wearing surface and the underlying FRP deck. Also, simulated subsurface delaminations (of various sizes and thickness) were created at the flange-to-flange junction between two FRP deck modules. (Abstract shortened by UMI.)

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed

Vehicle classification in intelligent transport systems: an overview, methods and software perspective

Vehicle Classification (VC) is a key element of Intelligent Transportation Systems (ITS). Diverse ranges of ITS applications like security systems, surveillance frameworks, fleet monitoring, traffic safety, and automated parking are using VC. Basically, in the current VC methods, vehicles are classified locally as a vehicle passes through a monitoring area, by fixed sensors or using a compound method. This paper presents a pervasive study on the state of the art of VC methods. We introduce a detailed VC taxonomy and explore the different kinds of traffic information that can be extracted via each method. Subsequently, traditional and cutting edge VC systems are investigated from different aspects. Specifically, strengths and shortcomings of the existing VC methods are discussed and real-time alternatives like Vehicular Ad-hoc Networks (VANETs) are investigated to convey physical as well as kinematic characteristics of the vehicles. Finally, we review a broad range of soft computing solutions involved in VC in the context of machine learning, neural networks, miscellaneous features, models and other methods

Examining Uptake of Nanomaterials by Eukaryotic Cells with Digital Image Cytometry

Due to their small size and related interesting properties, artificial nanoma-terials are utilized for a great number of biological and medical applications. Cell entry routes, intracellular trafficking and processing of nanoparticles, which determine their fate, efficiency, and toxicity, are depending on various parameters of the specific nanomaterial, such as size, surface charge, surface chemistry and elasticity. Nanoparticle-cell interactions are typically elucidated by means of fluorescence microscopy. Cell functions can be observed by a multiplicity of commercially available probes. For the quantification of cell features from images (image cytometry), computer-based algorithms are favoured to avoid bias introduced by the subjective perception of the observer. By applying high throughput microscopy in combination with digital image cytometry the screening of high numbers of cells is made possible. With the large quantity of obtained data, cell populations can be identified and, in general, results that are statistically meaningful are obtained. In the first part of this work this method is applied in order to examine the cellular responses upon exposure to plasmonic poly(methacrylic acid)-coated gold nanoparticles (Au NPs) with respect to morphology and viability of human endothelial and epithelial cells (HUVECs and HeLa cells). Au NPs of 4-5 nm size were chosen which had been thoroughly characterized in terms of their physico-chemical parameters. These particles bear interesting properties for biomedical applications and, for several years, have been in the focus of research. In this work significant impacts on mitochondrial and lysosomal morphology upon exposure to the Au NPs are reported. The alteration of the structure of the cytoskeleton and a dramatically reduced proliferation are described. Interestingly, the smallest dose inducing the described cellular responses was of one or two magnitudes lower than those, where acute cytotoxicity and an increase in the production of reactive oxygen species (ROS) were observed. In the second part the process of endocytosis of polymer capsules is examined. These systems are seen as a promising tool for intracellular cargo delivery and release. After lipid raft-mediated phagocytosis, the capsules are transferred from the neutral extracellular medium to increasingly acidic intracellular vesicles. By embedding a pH-sensitive fluorescent dye into the cavity of the capsule the uptake process and the associated acidification can be monitored time-dependently. It is demonstrated that the kinetic of the acidification process strongly depends on the stiffness of the capsules. Soft particles with minor stiffness are transported faster into lysosomal structures than stiffer ones. Additionally, these sensor particles are used to confirm the importance of the V1G1-subunit of the vacuolar ATPase being responsible for vesicle acidification

Change detection in combination with spatial models and its effectiveness on underwater scenarios

This thesis proposes a novel change detection approach for underwater scenarios and combines it with different especially developed spatial models, this allows accurate and spatially coherent detection of any moving objects with a static camera in arbitrary environments. To deal with the special problems of underwater imaging pre-segmentations based on the optical flow and other special adaptions were added to the change detection algorithm so that it can better handle typical underwater scenarios like a scene crowded by a whole fish swarm

Fuzzy machine vision based inspection

Machine vision system has been fostered to solve many realistic problems in various fields. Its role in achieving superior quality and productivity is of paramount importance. But, for such system to be attractive, it needs to be fast, accurate and cost-effective. This dissertation is based on a number of practical machine vision based inspection projects obtained from the automotive industry. It presents a collection of developed efficient fuzzy machine vision approaches endorsed with experimental results. It also covers the conceptual design, development and testing of various fuzzy machine vision based inspection approaches for different industrial applications. To assist in developing and evaluating the performance of the proposed approaches, several parts are tested under varying lighting conditions. This research deals with two important aspects of machine vision based inspection. In the first part, it concentrates on the topics of component detection and component orientation identification. The components used in this part are metal clips mounted on a dash panel frame that is installed in the door of trucks. Therefore, we propose a fuzzy machine vision based clip detection model and a fuzzy machine vision based clip orientation identification model to inspect the proper placement of clips on dash panels. Both models are efficient and fast in terms of accuracy and processing time. In the second part of the research, we are dealing with machined part defects such as broken edge, porosity and tool marks. The se defects occur on the surface of die cast aluminum automotive pump housings. As a result, an automated fuzzy machine vision based broken edge detection method, an efficient fuzzy machine vision based porosity detection technique and a neuro-fuzzy part classification model based on tool marks are developed. Computational results show that the proposed approaches are effective in yielding satisfactory results to the tested image databases. There are four main contributions to this work. The first contribution is the development of the concept of composite matrices in conjunction with XOR feature extractor using fuzzy subtractive clustering for clip detection. The second contribution is about a proposed model based on grouping and counting pixels in pre-selective areas which tracks pixel colors in separated RGB channels to determine whether the orientation of the clip is acceptable or not. The construction of three novel edge based features embedded in fuzzy C-means clustering for broken edge detection marks the third contribution. At last, the fourth contribution presents the core of porosity candidates concept and its correlation with twelve developed matrices. This, in turn, results in the development of five different features used in our fuzzy machine vision based porosity detection approach

Fluorescence Methods for Investigation of Living Cells and Microorganisms

Fluorescence methods play a leading role in the investigation of biological objects. They are the only non-destructive methods for investigating living cells and microorganisms in vivo. Using intrinsic and artificial fluorescence methods provides deep insight into mechanisms underlying physiological and biochemical processes. This book covers a wide range of modern methods involved in experimental biology. It illustrates the use of fluorescence microscopy and spectroscopy, confocal laser scanning microscopy, flow cytometry, delayed fluorescence, pulse-amplitude-modulation fluorometry, and fluorescent dye staining protocols. This book provides an overview of practical and theoretical aspects of fluorescence methods and their successful application in the investigation of static and dynamic processes in living cells and microorganisms

Genetic and Phenotypic Variation in Tree Crops Biodiversity

Recently, there has been a dramatic increase in the use of DNA-derived data and innovative phenotyping to obtain insights into the causative genes underlying traits of agronomical interest or to characterize tree genetic resources. The latter, in particular, could represent an important source of genetic diversity that can be readily used to enhance the adaptability to limiting environmental factors and resistance to biotic stresses or to promote novel genotypes with improved agronomic traits. On the whole, the studies collected in this book report on tree crop biodiversity characterization that could provide the essential building blocks to ensure future improvements in production and quality, as well as for innovations in tree crop development and utilization