A 2004 introduction to machine vision that includes many programming exercises.

Aimed at manufacturing managers and engineers looking for an introduction to computer vision and its potential, this book discusses the areas in which machine vision is being used, explains different types of machine vision hardware and software and summarizes research at several universities.

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 first edition of conference Proceedings reflects the expansion of the field of Mechatronics, which has now taken its place in the world of newer transdisciplinary fields of Adaptronics, Integronics, and Cyber-Mix Mechatronics. It presents state-of-the art advances in Mechatronics, Adaptronics, Integronics and Cyber-Mix-Mechatronics. The 1st International Conference of Mechatronics and Cyber-MixMechatronics/ICOMECYME was organized by the National Institute of R&D in Mechatronics and Measurement Technique in Bucharest (Romania), on September 7th–8th, 2017 and attracted specialists from all over the world—including North America, South America, and Asia. In addition to presenting research results, ICOMECYME also offered a forum for exchange between R&D experts.

Industrial Internet of Things: Technologies, Design, and Applications addresses the complete functional framework workflow in IoT technology. It explores basic and high-level concepts, thus serving as a manual for those in the industry while also helping beginners. The book incorporates the working methodology of Industrial IoT works, is based on the latest technologies, and will cover the major challenges, issues, and advances while exploring data-based intelligent and automated systems and their implications to the real world. The book discusses data acquisition, security, learning, intelligent data analysis, and case studies related to Industrial IoT-based applications.

For both students and engineers in R&D, this book explains machine vision in a concise, hands-on way, using the Vision Development Module of the LabView software by National Instruments. Following a short introduction to the basics of machine vision and the technical procedures of image acquisition, the book goes on to guide readers in the use of the various software functions of LabView's machine vision module. It covers typical machine vision tasks, including particle analysis, edge detection, pattern and shape matching, dimension measurements as well as optical character recognition, enabling readers to quickly and efficiently use these functions for their own machine vision applications. A discussion of the concepts involved in programming the Vision Development Module rounds off the book, while example problems and exercises are included for training purposes as well as to further explain the concept of machine vision. With its step-by-step guide and clear structure, this is an essential reference for beginners and experienced researchers alike.