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Author: Jürgen Beyerer Publisher: Springer ISBN: 3662477947 Category : Technology & Engineering Languages : en Pages : 798
Book Description
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.
Author: Jürgen Beyerer Publisher: Springer ISBN: 3662477947 Category : Technology & Engineering Languages : en Pages : 798
Book Description
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.
Author: Muthukumaran Malarvel Publisher: John Wiley & Sons ISBN: 1119786118 Category : Computers Languages : en Pages : 352
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: Zheng Liu Publisher: Springer ISBN: 1447167414 Category : Computers Languages : en Pages : 541
Book Description
This pioneering text/reference presents a detailed focus on the use of machine vision techniques in industrial inspection applications. An internationally renowned selection of experts provide insights on a range of inspection tasks, drawn from their cutting-edge work in academia and industry, covering practical issues of vision system integration for real-world applications. Topics and features: presents a comprehensive review of state-of-the-art hardware and software tools for machine vision, and the evolution of algorithms for industrial inspection; includes in-depth descriptions of advanced inspection methodologies and machine vision technologies for specific needs; discusses the latest developments and future trends in imaging and vision techniques for industrial inspection tasks; provides a focus on imaging and vision system integration, implementation, and optimization; describes the pitfalls and barriers to developing successful inspection systems for smooth and efficient manufacturing process.
Author: Benjamin M. Dawson Publisher: SPIE-International Society for Optical Engineering ISBN: 9780819414786 Category : Computer vision Languages : en Pages : 336
Author: Jürgen Beyerer
Author: Jürgen Beyerer
Author: 
Author: Muthukumaran Malarvel
Author: Zheng Liu
Author: A. Ravishankar Rao
Author: Martin Anthony Hunt
Author: Frederick Y. Wu
Author: Benjamin M. Dawson
Author: 
Author: Frederick Y. Wu