Illumination and Contrast Correction Strategy using Bilateral Filtering and Binarization Comparison

Illumination normalization and contrast variation on images are one of the most challenging tasks in the image processing field. Normally, the degrade contrast images are caused by pose, occlusion, illumination, and luminosity. In this paper, a new contrast and luminosity correction technique is developed based on bilateral filtering and superimpose techniques. Background pixels was used in order to estimate the normalized background using their local mean and standard deviation. An experiment has been conducted on few badly illuminated images and document images which involve illumination and contrast problem. The results were evaluated based on Signal Noise Ratio (SNR) and Misclassification Error (ME). The performance of the proposed method based on SNR and ME was very encouraging. The results also show that the proposed method is more effective in normalizing the illumination and contrast compared to other illumination techniques such as homomorphic filtering, high pass filter and double mean filtering (DMV)

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

identification of common parameters in an onion crop (Allium cepa) by PDI

Para comprender el crecimiento de un cultivo, es necesario conocer e identificar los parámetros que influyen en su desarrollo. Para ello se requieren herramientas adecuadas, derivadas de la combinación de la agricultura con las tecnologías electrónicas existentes hasta hoy en día; las cuales ayudan a identificar información y características que interfieren en los procesos fisiológicos de las plantas. El objetivo de esta investigación fue aplicar PDI a imágenes aéreas, tomadas sobre un cultivo de cebolla en la región zacatecana, para encontrar las problemáticas que afectan su crecimiento. Se desarrolló e implementó un algoritmo, en el lenguaje de programación Python 3.6®, con la finalidad de estimar de manera automática, algunas anomalías comunes a nivel parcelario en cebolla, como: la maleza, la densidad poblacional de vegetación y exceso de humedad incluyendo fugas, encontrando un porcentaje de 90, 95.08 y 80.44 respectivamente, los porcentajes mencionados fueron obtenidos en función de la comparación automática-visual

Recent Advances and Applications of Machine Learning in Metal Forming Processes

Machine learning (ML) technologies are emerging in Mechanical Engineering, driven by the increasing availability of datasets, coupled with the exponential growth in computer performance. In fact, there has been a growing interest in evaluating the capabilities of ML algorithms to approach topics related to metal forming processes, such as: Classification, detection and prediction of forming defects; Material parameters identification; Material modelling; Process classification and selection; Process design and optimization. The purpose of this Special Issue is to disseminate state-of-the-art ML applications in metal forming processes, covering 10 papers about the abovementioned and related topics

Recent advances and applications of machine learning in metal forming processes

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Surface and Sub-Surface Analyses for Bridge Inspection

The development of bridge inspection solutions has been discussed in the recent past. In this dissertation, significant development and improvement on the state-of-the-art in the field of bridge inspection using multiple sensors (e.g. ground penetrating radar (GPR) and visual sensor) has been proposed. In the first part of this research (discussed in chapter 3), the focus is towards developing effective and novel methods for rebar detection and localization for sub-surface bridge inspection of steel rebars. The data has been collected using Ground Penetrating Radar (GPR) sensor on real bridge decks. In this regard, a number of different approaches have been successively developed that continue to improve the state-of-the-art in this particular research area. The second part (discussed in chapter 4) of this research deals with the development of an automated system for steel bridge defect detection system using a Multi-Directional Bicycle Robot. The training data has been acquired from actual bridges in Vietnam and validation is performed on data collected using Bicycle Robot from actual bridge located in Highway-80, Lovelock, Nevada, USA. A number of different proposed methods have been discussed in chapter 4. The final chapter of the dissertation will conclude the findings from the different parts and discuss ways of improving on the existing works in the near future

Incorporating automated rail fatigue damage detection algorithms with crack growth modelling

This thesis examines the feasibility of incorporating Non Destructive Testing (NDT) of rail surface damage by means of combining image processing with damage prediction models. As rail traffic and adherence to safety measures become increasingly strict on the network, the associated maintenance cost of rail infrastructure must be kept at a minimum. Proactive maintenance is crucial to maintaining the competitive advantage of rail transport. A considerable amount of research has been done on improving the practical tediousness associated with popular condition monitoring techniques in rail industry e.g. Ultrasonic, and Eddy current method. This thesis aims to fill the gap of yet to be explored benefit, of combining detection and prediction of RCF damage. This research project will contribute to the rail industry by simplifying maintenance operations and support decision making. In this thesis, a summary of existing image-based NDT and crack growth models is presented as a foundation on which the novel application is built.It could be said that similar research mainly focuses on quantifying severity of damage without predicting crack behaviour. The simulated results of the proposed image processing algorithm confirm superiority of local illumination invariant enhancement, multi-window segmentation, and cascaded feature extraction. The influential parameters of these methods are consistent within each image data set but differ across all sets. This is observed to be as a result of difference in environmental and reflection properties of acquired images.A sensitivity analysis of the proposed algorithm on data set 2 suggests a non-linear relationship between severity of damage and pixel mean intensity including variance. Taking to account fracture mechanics aspect of this thesis, the influence of crack geometry on growth rate and path has been established by case study of newly initiated and critically grown cracks. It was further established that larger cracks are observed to grow faster than smaller ones. In addition, the influence of track curve radius and supporting structures on wheel rail contact dynamics is well understood from the structural mechanic’s tests related to contact forces and bending moment. These translate to increase or decrease in contact stresses, strains, and the propagation rate of defects. Unlike other predictive models, the method developed in this thesis focuses on replicating the actual surface condition of the rail prior to estimating the fracture parameters (using detailed 3D Finite Element model) that dictate residual life of the rail asset. The model makes it possible to combine two separate maintenance activities i.e. detection and prediction without inducing down time of the service. A direct impact of this novel application is the utilisation of the actual crack boundary for prediction of fracture behaviour. It is insinuated that stress distribution of actual crack boundary differs from elliptical equivalent assumptions. Further work would include improving detection aspect of the novel application to avoid intersecting boundary coordinates, which are not readily imported into the Linear Elastic Fracture Mechanics (LEFM) prediction model. It is also beneficial to expand the prediction aspect of the research work to include influence of neighbouring cracks and fluid entrapment for more flexible analysis of other environmental and contact conditions. To improve on current work, it will be useful to conduct laboratory investigations on the influence of Image Acquisition System (IAS) light source in relation to illumination inequality within the captured image. Also fracture mechanics experimental validation can be used to assert the accuracy of the metho

Polymer Processing and Surfaces

This book focuses on fundamental and applied research on polymer processing and its effect on the final surface as the optimization of polymer surface properties results in the unique applicability of these over other materials. The development and testing of the next generation of polymeric and composite materials is of particular interest. Special attention is given to polymer surface modification, external stimuli-responsive surfaces, coatings, adhesion, polymer and composites fatigue analysis, evaluation of the surface quality and microhardness, processing parameter optimization, characterization techniques, among others

MATLAB

A well-known statement says that the PID controller is the "bread and butter" of the control engineer. This is indeed true, from a scientific standpoint. However, nowadays, in the era of computer science, when the paper and pencil have been replaced by the keyboard and the display of computers, one may equally say that MATLAB is the "bread" in the above statement. MATLAB has became a de facto tool for the modern system engineer. This book is written for both engineering students, as well as for practicing engineers. The wide range of applications in which MATLAB is the working framework, shows that it is a powerful, comprehensive and easy-to-use environment for performing technical computations. The book includes various excellent applications in which MATLAB is employed: from pure algebraic computations to data acquisition in real-life experiments, from control strategies to image processing algorithms, from graphical user interface design for educational purposes to Simulink embedded systems