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.

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.

This edited book brings together leading researchers, academic scientists and research scholars to put forward and share their experiences and research results on all aspects of an inspection system for detection analysis for various machine vision applications. It also provides a premier interdisciplinary platform to present and discuss the most recent innovations, trends, methodology, applications, and concerns as well as practical challenges encountered and solutions adopted in the inspection system in terms of image processing and analytics of machine vision for real and industrial application. Machine vision inspection systems (MVIS) utilized all industrial and non-industrial applications where the execution of their utilities based on the acquisition and processing of images. MVIS can be applicable in industry, governmental, defense, aerospace, remote sensing, medical, and academic/education applications but constraints are different. MVIS entails acceptable accuracy, high reliability, high robustness, and low cost. Image processing is a well-defined transformation between human vision and image digitization, and their techniques are the foremost way to experiment in the MVIS. The digital image technique furnishes improved pictorial information by processing the image data through machine vision perception. Digital image pro­cessing has widely been used 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), barcode reading and traceability, medical diagnosis, weather forecasting, face recognition, defence and space research, 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 image processing techniques.

The book offers a thorough introduction to machine vision. It is organized in two parts. The first part covers the image acquisition, which is the crucial component of most automated visual inspection systems. All important methods are described in great detail and are presented with a reasoned structure. The second part deals with the modeling and processing of image signals and pays particular regard to methods, which are relevant for automated visual inspection.

Machine vision technology has revolutionised the process of automated inspection in manufacturing. The specialist techniques required for inspection of natural products, such as food, leather, textiles and stone is still a challenging area of research. Topological variations make image processing algorithm development, system integration and mechanical handling issues much more complex. The practical issues of making machine vision systems operate robustly in often hostile environments together with the latest technological advancements are reviewed in this volume. Features: - Case studies based on real-world problems to demonstrate the practical application of machine vision systems. - In-depth description of system components including image processing, illumination, real-time hardware, mechanical handling, sensing and on-line testing. - Systems-level integration of constituent technologies for bespoke applications across a variety of industries. - A diverse range of example applications that a system may be required to handle from live fish to ceramic tiles. Machine Vision for the Inspection of Natural Products will be a valuable resource for researchers developing innovative machine vision systems in collaboration with food technology, textile and agriculture sectors. It will also appeal to practising engineers and managers in industries where the application of machine vision can enhance product safety and process efficiency.

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.