Author: Kasthurira Gopalakrishnan
Publisher:
ISBN:
Category : Pavements, Concrete
Languages : en
Pages : 49
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Book Description
State highway agencies (SHAs) routinely employ semi-automated and automated image-based methods for network-level pavement-cracking data collection, and there are different types of pavement-cracking data collected by SHAs for reporting and management purposes. The main objective of this proof-of-concept research was to develop a shape-based pavement-crack-detection approach for the reliable detection and classification of cracks from acquired two-dimensional (2D) concrete and asphalt pavement surface images. The developed pavement-crack-detection algorithm consists of four stages: local filtering, maximum component extraction, polynomial fitting of possible crack pixels, and shape metric computation and filtering. After completing the crack-detection process, the width of each crack segment is computed to classify the cracks. In order to verify the developed crack-detection approach, a series of experiments was conducted on real pavement images without and with cracks at different severities. The developed shape-based pavement crack detection algorithm was able to detect cracks at different severities from both asphalt and concrete pavement images. Further, the developed algorithm was able to compute crack widths from the images for crack classification and reporting purposes. Additional research is needed to improve the robustness and accuracy of the developed approach in the presence of anomalies and other surface irregularities.
Author: Robert P. Loce
Publisher: John Wiley & Sons
ISBN: 1118971639
Category : Technology & Engineering
Languages : en
Pages : 632
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Book Description
Acts as single source reference providing readers with an overview of how computer vision can contribute to the different applications in the field of road transportation This book presents a survey of computer vision techniques related to three key broad problems in the roadway transportation domain: safety, efficiency, and law enforcement. The individual chapters present significant applications within those problem domains, each presented in a tutorial manner, describing the motivation for and benefits of the application, and a description of the state of the art. Key features: Surveys the applications of computer vision techniques to road transportation system for the purposes of improving safety and efficiency and to assist law enforcement. Offers a timely discussion as computer vision is reaching a point of being useful in the field of transportation systems. Available as an enhanced eBook with video demonstrations to further explain the concepts discussed in the book, as well as links to publically available software and data sets for testing and algorithm development. The book will benefit the many researchers, engineers and practitioners of computer vision, digital imaging, automotive and civil engineering working in intelligent transportation systems. Given the breadth of topics covered, the text will present the reader with new and yet unconceived possibilities for application within their communities.
Author: Mahdi Rezaei
Publisher: Springer
ISBN: 3319505513
Category : Mathematics
Languages : en
Pages : 236
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Book Description
This book summarises the state of the art in computer vision-based driver and road monitoring, focussing on monocular vision technology in particular, with the aim to address challenges of driver assistance and autonomous driving systems. While the systems designed for the assistance of drivers of on-road vehicles are currently converging to the design of autonomous vehicles, the research presented here focuses on scenarios where a driver is still assumed to pay attention to the traffic while operating a partially automated vehicle. Proposing various computer vision algorithms, techniques and methodologies, the authors also provide a general review of computer vision technologies that are relevant for driver assistance and fully autonomous vehicles. Computer Vision for Driver Assistance is the first book of its kind and will appeal to undergraduate and graduate students, researchers, engineers and those generally interested in computer vision-related topics in modern vehicle design.
Author: Dongming Feng
Publisher: John Wiley & Sons
ISBN: 1119566584
Category : Science
Languages : en
Pages : 260
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Book Description
Provides comprehensive coverage of theory and hands-on implementation of computer vision-based sensors for structural health monitoring This book is the first to fill the gap between scientific research of computer vision and its practical applications for structural health monitoring (SHM). It provides a complete, state-of-the-art review of the collective experience that the SHM community has gained in recent years. It also extensively explores the potentials of the vision sensor as a fast and cost-effective tool for solving SHM problems based on both time and frequency domain analytics, broadening the application of emerging computer vision sensor technology in not only scientific research but also engineering practice. Computer Vision for Structural Dynamics and Health Monitoring presents fundamental knowledge, important issues, and practical techniques critical to successful development of vision-based sensors in detail, including robustness of template matching techniques for tracking targets; coordinate conversion methods for determining calibration factors to convert image pixel displacements to physical displacements; sensing by tracking artificial targets vs. natural targets; measurements in real time vs. by post-processing; and field measurement error sources and mitigation methods. The book also features a wide range of tests conducted in both controlled laboratory and complex field environments in order to evaluate the sensor accuracy and demonstrate the unique features and merits of computer vision-based structural displacement measurement. Offers comprehensive understanding of the principles and applications of computer vision for structural dynamics and health monitoring Helps broaden the application of the emerging computer vision sensor technology from scientific research to engineering practice such as field condition assessment of civil engineering structures and infrastructure systems Includes a wide range of laboratory and field testing examples, as well as practical techniques for field application Provides MATLAB code for most of the issues discussed including that of image processing, structural dynamics, and SHM applications Computer Vision for Structural Dynamics and Health Monitoring is ideal for graduate students, researchers, and practicing engineers who are interested in learning about this emerging sensor technology and advancing their applications in SHM and other engineering problems. It will also benefit those in civil and aerospace engineering, energy, and computer science.
Author: Brunken, Hauke
Publisher: Universitätsverlag der TU Berlin
ISBN: 3798332053
Category : Technology & Engineering
Languages : en
Pages : 188
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Book Description
When planning road construction measures, it is essential to have up-to-date information on road conditions. If this information is not to be obtained manually, it is currently obtained using laser scanners mounted on mobile mapping vehicles, which can measure the 3D road profile. However, a large number of mobile mapping vehicles would be necessary to record an entire road network on a regular basis. Since 2D road damages can be found automatically on monocular camera images, the idea was born to use a stereo camera system to capture the 3D profile of roads. With stereo camera systems, it would be possible to equip a large number of vehicles and regularly collect data from large road networks. In this thesis, the potential applications of a stereo camera system for measuring road profiles, which is mounted behind the windshield of a vehicle, are investigated. Since this requires a calibration of the stereo camera system, but the effort for the user should be kept low, the camera self-calibration for this application is also examined. 3D reconstruction from stereoscopic images is a well-studied topic, but its application on road surfaces with little and repetitive textures requires special algorithms. For this reason, a new stereo method was developed. It is based on the plane-sweep approach in combination with semi-global matching. It was tested with different measures for pixel comparison. Furthermore, the plane-sweep approach was implemented in a neural network that solves the stereo correspondence problem in a single step. It uses the stereoscopic images as input and provides an elevation image as output. A completely new approach was developed for the self-calibration of mono cameras and stereo camera systems. Previous methods search for feature points in several images of the same scene. The points are matched between the images and used for the calibration. In contrast to these methods, the proposed method uses feature maps instead of feature points to compare multiple views of one and the same plane. To estimate the unknown parameters, the backpropagation algorithm is used together with the gradient descent method. The measurements obtained by stereoscopic image processing were compared with those obtained by industrial laser scanners. They show that both measurements are very close to each other and that a stereoscopic camera system is in principle suitable for capturing the surface profile of a road. Experiments show that the proposed self-calibration method is capable of estimating all parameters of a complex camera model, including lens distortion, with high precision. Bei der Planung von Straßenbaumaßnahmen ist es unabdingbar, über aktuelle Informationen über den Straßenzustand zu verfügen. Sollen diese Informationen nicht manuell gewonnen werden, werden derzeit Messfahrzeug mit Laserscannern verwendet, welche das 3D-Straßenprofil vermessen können. Für die regelmäßige Erfassung eines gesamten Straßennetzes wäre jedoch eine große Anzahl von Messfahrzeugen erforderlich. Da 2D-Straßenschäden automatisch auf monokularen Kamerabildern gefunden werden können, entstand die Idee, ein Stereokamerasystem zur Erfassung des 3D-Profils zu verwenden. Eine große Anzahl von Fahrzeugen könnte damit ausgerüstet werden und es könnten regelmäßig Daten von großen Straßennetzen erfasst werden. In dieser Arbeit werden die Einsatzmöglichkeiten eines Stereokamerasystems zur Messung von Straßenprofilen untersucht, dass sich hinter der Windschutzscheibe eines Fahrzeugs befindet. Da hierzu das Stereokamerasystems kalibriert sein muss, der Aufwand für den Anwender aber geringgehalten werden soll, wird außerdem die Selbstkalibrierung für diesen Einsatzzweck untersucht. Die 3D-Rekonstruktion aus stereoskopischen Bildern ist ein viel untersuchtes Thema, aber ihre Anwendung auf Straßenoberflächen mit wenig und sich wiederholenden Texturen erfordert spezielle Algorithmen. Aus diesem Grund wurde ein neues Stereoverfahren entwickelt. Es basiert auf dem Plane-sweep-Ansatz in Kombination mit Semi-global Matching. Es wurde mit verschiedene Maßen für den Vergleich von Pixeln getestet. Darüber hinaus wurde der Plane-sweep-Ansatz in einem neuronalen Netzwerk implementiert, das das Stereo-Korrespondenzproblem in einem einzigen Schritt löst. Es verwendet die stereoskopischen Bilder als Eingabe und liefert als Ausgabe ein Höhenbild. Für die Selbstkalibrierung von Monokameras und Stereokamerasystemen wurde ein völlig neuer Ansatz entwickelt. Bisherige Methoden suchen nach Merkmalspunkten in mehreren Bildern der gleichen Szene. Die Punkte werden zwischen den Bildern zugeordnet und für die Kalibrierung verwendet. Die vorgeschlagene Methode verwendet anstelle von Merkmalspunkten Feature-Maps um mehrere Ansichten derselben Ebene zu vergleichen. Zur Schätzung der unbekannten Parameter wird der Backpropagation-Algorithmus zusammen mit dem Gradientenabstiegsverfahren verwendet. Die durch stereoskopische Bildverarbeitung erhaltenen Messungen wurden mit Messungen von industriellen Laserscannern verglichen. Sie zeigen, dass beide sehr nahe beieinander liegen und dass ein Stereokamerasystem für die Erfassung des Oberflächenprofils einer Straße grundsätzlich geeignet ist. Experimente zeigen, dass die neue Selbstkalibrierungsmethode in der Lage ist, alle Parameter eines komplexen Kameramodells, einschließlich der Linsenverzerrung, mit hoher Präzision abzuschätzen.
Author: Kohei Arai
Publisher: Springer Nature
ISBN: 3031104617
Category : Technology & Engineering
Languages : en
Pages : 930
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Book Description
The book, “Intelligent Computing - Proceedings of the 2022 Computing Conference”, is a comprehensive collection of chapters focusing on the core areas of computing and their further applications in the real world. Each chapter is a paper presented at the Computing Conference 2022 held on July 14-15, 2022. Computing 2022 attracted a total of 498 submissions which underwent a double-blind peer-review process. Of those 498 submissions, 179 submissions have been selected to be included in this book. The goal of this conference is to give a platform to researchers with fundamental contributions and to be a premier venue for academic and industry practitioners to share new ideas and development experiences. We hope that readers find this book interesting and valuable as it provides the state-of-the-art intelligent methods and techniques for solving real-world problems. We also expect that the conference and its publications will be a trigger for further related research and technology improvements in this important subject.
Author: Andreas Loizos
Publisher: CRC Press
ISBN: 1351585797
Category : Technology & Engineering
Languages : en
Pages : 364
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Book Description
Bearing Capacity of Roads, Railways and Airfields includes the contributions to the 10th International Conference on the Bearing Capacity of Roads, Railways and Airfields (BCRRA 2017, 28-30 June 2017, Athens, Greece). The papers cover aspects related to materials, laboratory testing, design, construction, maintenance and management systems of transport infrastructure, and focus on roads, railways and airfields. Additional aspects that concern new materials and characterization, alternative rehabilitation techniques, technological advances as well as pavement and railway track substructure sustainability are included. The contributions discuss new concepts and innovative solutions, and are concentrated but not limited on the following topics: · Unbound aggregate materials and soil properties · Bound materials characteritics, mechanical properties and testing · Effect of traffic loading · In-situ measurements techniques and monitoring · Structural evaluation · Pavement serviceability condition · Rehabilitation and maintenance issues · Geophysical assessment · Stabilization and reinforcement · Performance modeling · Environmental challenges · Life cycle assessment and sustainability Bearing Capacity of Roads, Railways and Airfields is essential reading for academics and professionals involved or interested in transport infrastructure systems, in particular roads, railways and airfields.
Author: Rivas-Lopez, Moises
Publisher: IGI Global
ISBN: 1522557520
Category : Computers
Languages : en
Pages : 459
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Book Description
Sensor technologies play a large part in modern life, as they are present in things like security systems, digital cameras, smartphones, and motion sensors. While these devices are always evolving, research is being done to further develop this technology to help detect and analyze threats, perform in-depth inspections, and perform tracking services. Optoelectronics in Machine Vision-Based Theories and Applications provides innovative insights on theories and applications of optoelectronics in machine vision-based systems. It also covers topics such as applications of unmanned aerial vehicle, autonomous and mobile robots, medical scanning, industrial applications, agriculture, and structural health monitoring. This publication is a vital reference source for engineers, technology developers, academicians, researchers, and advanced-level students seeking emerging research on sensor technologies and machine vision.
Author: Muthukumaran Malarvel
Publisher: John Wiley & Sons
ISBN: 1119786096
Category : Computers
Languages : en
Pages : 354
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Book Description
Machine Vision Inspection Systems (MVIS) is a multidisciplinary research field that emphasizes image processing, machine vision and, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry. Now a day's the current research on machine inspection gained more popularity among various researchers, because the manual assessment of the inspection may fail and turn into false assessment due to a large number of examining while inspection process. This volume 2 covers machine learning-based approaches in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT), presence/absence detection, defect/fault detection (weld, textile, tiles, wood, etc.), automated vision test & measurement, pattern matching, optical character recognition & verification (OCR/OCV), natural language processing, medical diagnosis, etc. This edited book is designed to address various aspects of recent methodologies, concepts, and research plan out to the readers for giving more depth insights for perusing research on machine vision using machine learning-based approaches.
Author: Hamzeh Zakeri
Publisher: John Wiley & Sons
ISBN: 1119800668
Category : Computers
Languages : en
Pages : 548
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Book Description
Automation and Computational Intelligence for Road Maintenance and Management A comprehensive computational intelligence toolbox for solving problems in infrastructure management In Automation and Computational Intelligence for Road Maintenance and Management, a team of accomplished researchers delivers an incisive reference that covers the latest developments in computer technology infrastructure management. The book contains an overview of foundational and emerging technologies and methods in both automation and computational intelligence, as well as detailed presentations of specific methodologies. The distinguished authors emphasize the most recent advances in the maintenance and management of infrastructure robotics, automated inspection, remote sensing, and the applications of new and emerging computing technologies, including artificial intelligence, evolutionary computing, fuzzy logic, genetic algorithms, knowledge discovery and engineering, and more. Automation and Computational Intelligence for Road Maintenance and Management explores a universal synthesis of the cutting edge in parameters and indices to evaluate models. It also includes: Thorough introductions to management science and the latest methods of automation and the structure and framework of automation and computing intelligence Comprehensive explorations of advanced image processing techniques, recent advances in fuzzy, and diagnosis automation Practical discussions of segmentation and fragmentation and different types of features and feature extraction methods In-depth examinations of methods of classification along with various developed methodologies and models of quantification, evaluation, and indexing in automation Perfect for postgraduate students in road and transportation engineering, evaluation, and assessment, Automation and Computational Intelligence for Road Maintenance and Management will also earn a place in the libraries of researchers interested in or working with the evaluation and assessment of infrastructure.
