1st Edition
Measurements and Instrumentation for Machine Vision
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.
Chapter 1: Machine Learning Approaches for Single Photon Direct Time of Flight Imaging
Jack Iain MacLean, Brian Stewart, and Istvan Gyongy
Chapter 2: Experimental Evaluation of Depth Measurements Accuracy in Indoor Environments
Wendy García-Gonzalez, Wendy Flores-Fuentes, Oleg Sergiyenko, Julio C. Rodríguez-Quiñonez, Jesús E. Miranda-Vega, Arnoldo Díaz-Ramirez, and Marina Kolendovska
Chapter 3: Design and Evaluation Support System for Convolutional Neural Network, Support Vector Machine and Convolutional Autoencoder
Fusaomi Nagata, Kento Nakashima, Kohei Miki, Koki Arima, Tatsuki Shimizu, Keigo Watanabe, and Maki K. Habib
Chapter 4: Classification of Objects in IR Images Using Wavelet Filters Based on Lifting Scheme
Daniel Trevino-Sanchez and Vicente Alarcon-Aquino
Chapter 5: Image Dataset Augmentation: A Survey and Taxonomy
Sergey Nesteruk, Svetlana Illarionova, and Andrey Somov
Chapter 6: A Filter-based Feature Selection Methodology for Vehicle/Non-Vehicle Classification
Atikul Islam, Saurav Mallik, Arup Roy, Maroi Agrebi, and Pawan Kumar Singh
Chapter 7: Augmented Visual Inertial Wheel Odometry Through Slip Compensation
Niraj Reginald, Omar Al-Buraiki, Baris Fidan, and Ehsan Hashemi
Chapter 8: Methodology for Developing Models of Image Color of Terrain with Landmarks for Their Detection and Recognition by Autonomous Mobile Robots
Oleksandr Poliarus and Yevhen Poliakov
Chapter 9: Machine Vision: A Measurement Tool for Agricultural Automation
Duke M. Bulanon, Isaac Compher, Garrisen Cizmich, Joseph Ichiro Bulanon, and Brice Allen
Chapter 10: Occlusion-Aware Disparity-based Direct Visual Servoing of Mobile Robots
Xiule Fan, Baris Fidan, and Soo Jeon
Chapter 11: Development of Software and Hardware Complex for the Visualization of Sediments Inside a Vortex Chamber
DO Semenov, SV Dvoinishnikov, VG Meledin, VV Rakhmanov, GV Bakakin, VA Pavlov, and IK Kabardin
Chapter 12: Machine Vision for Astronomical Images using the Modern Image Processing Algorithms Implemented in the CoLiTec Software
Sergii Khlamov, Vadym Savanevych, Iryna Tabakova, Vladimir Kartashov, Tetiana Trunova, and Marina Kolendovska
Chapter 13: Gallium Oxide UV Sensing in Contemporary Applications
Naif H. Al-Hardan, Muhammad Azmi Abdul Hamid, Chaker Tlili, Azman Jalar, Mohd Firdaus Raih, and Naser M Ahmed
Chapter 14: Technical Vision System for Alive Human Detection in an Optically Opaque Environment
Oleg Sytnik and Vladimir Kartashov
Chapter 15: The Best Linear Solution for a Camera and an Inertial Measurement Unit Calibration
Miti Ruchanurucks, Ratchakorn Srihera, and Surangrak Sutiworwan
Chapter 16: Methods of Forming and Selecting a Reference Image to Provide High-Speed Navigation for Maneuvering Aircraft
Sotnikov Oleksandr, Tymochko Oleksandr, Tiurina Valeriia, Trystan Andrii, Dmitriev Oleg, Olizarenko Serhii, Afanasiev Volodymyr, Fustii Vadim, and Stepanenko Dmitryo
Chapter 17: Application of Fibre Bragg Grating Arrays for Medical Diagnosis and Rehabilitation Purposes
Manish Mishra and Prasant Kumar Sahu
Biography
Oleg Sergiyenko is a Researcher in the Engineering Institute of Baja California. His research interests are in automated metrology, machien vision, robot navigation, fast electric measurements and control theory.
Wendy Flores-Fuentes is a Researcher-Professor of the Faculty of Engineering of the Autonomous University of Baja California. Her area of interest is the study, analysis and experimentation of optoelectronics and automatic measuremetns for the instrumentation of machine vision systems.
Julio C. Rodríguez-Quiñonez is a Researcher-Professor of the Faculty of Engineering of the Autonomous University of Baja California. His current research interests encompass automated metrology, machine vision, stereo vision systems, intertial navigation systems and robot navigation.
Jesús E. Miranda-Vega is a Professor in the National Technological Institute of Mexico/Mexicali Institute of Technology. His current research interests are machine vision, stereo vision, laser systems, artificial intelligence and signal processing.
