Measurements and Instrumentation for Machine Vision
- 466 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Measurements and Instrumentation for Machine Vision
About this book
A comprehensive reference book that addresses the field of machine vision and its significance in cyber-physical systems. It explores the multidisciplinary nature of machine vision, involving electronic and mechatronic devices, artificial intelligence algorithms, embedded systems, control systems, robotics, interconnectivity, data science, and cloud computing. The book aims to provide advanced students, early career researchers, and established scholars with state-of-the-art knowledge and novel content related to the implementation of machine vision in engineering, scientific knowledge, and technological innovation.
The chapters of the book delve into various topics and applications within the realm of machine vision. They cover areas such as camera and inertial measurement unit calibration, technical vision systems for human detection, design and evaluation of support systems using neural networks, UV sensing in contemporary applications, fiber Bragg grating arrays for medical diagnosis, color model creation for terrain recognition by robots, navigation systems for aircraft, object classification in infrared images, feature selection for vehicle/non-vehicle classification, visualization of sedimentation in extreme conditions, quality estimation of tea using machine vision, image dataset augmentation techniques, machine vision for astronomical images, agricultural automation, occlusion-aware disparity-based visual servoing, machine learning approaches for single-photon imaging, and augmented visual inertial wheel odometry.
Each chapter is a result of expert research and collaboration, reviewed by peers and consulted by the book's editorial board. The authors provide in-depth reviews of the state of the art and present novel proposals, contributing to the development and futurist trends in the field of machine vision.
"Measurements and Instrumentation for Machine Vision" serves as a valuable resource for researchers, students, and professionals seeking to explore and implement machine vision technologies in various domains, promoting sustainability, human-centered solutions, and global problem-solving.
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Information
Table of contents
- Cover Page
- Title Page
- Copyright Page
- Preface
- Acknowledgement
- Contents
- List of Contributors
- 1 Machine Learning Approaches for Single Photon Direct Time of Flight Imaging
- 2 Experimental Evaluation of Depth Measurements Accuracy in Indoor Environments
- 3 Design and Evaluation Support System for Convolutional Neural Network, Support Vector Machine and Convolutional Autoencoder
- 4 Classification of Objects in IR Images using Wavelet Filters based on Lifting Scheme
- 5 Image Dataset Augmentation A Survey and Taxonomy
- 6 A Filter-based Feature Selection Methodology for Vehicle/Non-Vehicle Classification
- 7 Augmented Visual Inertial Wheel Odometry Through Slip Compensation
- 8 Methodology for Developing Models of Image Color of Terrain with Landmarks for Their Detection and Recognition by Autonomous Mobile Robots
- 9 Machine Vision: A Measurement Tool for Agricultural Automation
- 10 Occlusion-Aware Disparity-based Direct Visual Servoing of Mobile Robots
- 11 Development of a Software and Hardware Complex for the Visualization of Sedimentation Inside a Vortex Chamber
- 12 Machine Vision for Astronomical Images using The Modern Image Processing Algorithms Implemented in the CoLiTec Software
- 13 Gallium Oxide UV Sensing in Contemporary Applications
- 14 Technical Vision System for Alive Human Detection in an Optically Opaque Environment
- 15 The Best Linear Solution for a Camera and an Inertial Measurement Unit Calibration
- 16 Methods of Forming and Selecting a Reference Image to Provide High-Speed Navigation for Maneuvering Aircraft
- 17 Application of Fibre Bragg Grating Arrays for Medical Diagnosis and Rehabilitation Purposes
- Index