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.
What is Automated Optical Inspection Automated optical inspection (AOI) is an automated visual inspection of printed circuit board (PCB) manufacture where a camera autonomously scans the device under test for both catastrophic failure and quality defects. It is commonly used in the manufacturing process because it is a non-contact test method. It is implemented at many stages through the manufacturing process including bare board inspection, solder paste inspection (SPI), pre-reflow and post-re-flow as well as other stages. How you will benefit (I) Insights, and validations about the following topics: Chapter 1: Automated Optical Inspection Chapter 2: Printed Circuit Board Chapter 3: Ball Grid Array Chapter 4: Surface-mount Technology Chapter 5: Gerber Format Chapter 6: Reflow Oven Chapter 7: Reflow Soldering Chapter 8: Rework (Electronics) Chapter 9: Solder Paste Chapter 10: Selective Soldering (II) Answering the public top questions about automated optical inspection. (III) Real world examples for the usage of automated optical inspection in many fields. Who this book is for Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Automated Optical Inspection.
This collection of works on the theory, technology and industrial applications of automated optical inspection contains 117 papers on such subjects as high-speed optical inspection systems and novel inspection algorithms and architectures.
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.
