This first up-to-date textbook for machine vision software provides all the details on the theory and practical use of the relevant algorithms.
The first part covers image acquisition, including illumination, lenses, cameras, frame grabbers, and bus systems, while the second deals with the algorithms themselves. This includes data structures, image enhancement and transformations, segmentation, feature extraction, morphology, template matching, stereo reconstruction, and camera calibration. The final part concentrates on applications, and features real-world examples, example code with HALCON, and further exercises.
Uniting the latest research results with an industrial approach, this textbook is ideal for students of electrical engineering, physics and informatics, electrical and mechanical engineers, as well as those working in the sensor, automation and optical industries.
Free software available with registration code
Cited By
- Steger C and Ulrich M (2020). A Camera Model for Line-Scan Cameras with Telecentric Lenses, International Journal of Computer Vision, 129:1, (80-99), Online publication date: 1-Jan-2021.
Zhang Z, Zhang B and Akiduki T Specular reflection Surface Defects Detection by using Deep Learning Proceedings of the 2019 3rd International Conference on Information System and Data Mining, (6-10)- Ashish N and Brusniak M Automated Mouse Organ Segmentation Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics, (236-243)
- Steger C (2018). Algorithms for the Orthographic-n-Point Problem, Journal of Mathematical Imaging and Vision, 60:2, (246-266), Online publication date: 1-Feb-2018.
- Liu Z, Wang W, Zhang X and Jia W Inspection of rail surface defects based on image processing Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1, (472-475)
- Liang Z and Jian-hui L Obtain the depth of field based on two-view Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1, (508-510)
- Xie J Optical character recognition based on least square support vector machine Proceedings of the 3rd international conference on Intelligent information technology application, (626-629)
- Ulrich M, Wiedemann C and Steger C CAD-based recognition of 3D objects in monocular images Proceedings of the 2009 IEEE international conference on Robotics and Automation, (2090-2097)
Index Terms
- Machine Vision Algorithms and Applications
Reviews
Fernando Santos Osorio
This book-a very good reference for people interested in machine vision applications- presents a well-balanced mix between theory and practical applications related to the machine vision domain. The authors have much experience in this field, accumulated in their academic-at Technische Universität München (TUM)-and business-as engineers and researchers at MVTec, the company responsible for the HALCON software-careers. In this book, they succeed in writing a text that clearly presents their thoughts about the development of machine vision applications, ranging from image acquisition problems to image processing and vision algorithms, including several interesting practical examples of applications, with the related code used along with HALCON. The book includes a registration code to be used with the student version of the HALCON machine vision software that can be downloaded and used free of charge. The book's strongest point is that it covers basic topics in image acquisition-illumination, light sources, lenses, distortions, sensors, and interfaces-as well as a set of complete applications in machine vision, including detailed examples of an optical character recognition (OCR) device, quality inspection applications (for example, inspection of saw blades, solder balls and junctions, and printed surfaces), measurement applications, and even three-dimensional plane reconstruction using stereo vision. The authors present some foundations and basic concepts of machine vision, followed by practical problems that demonstrate how to use the theoretical concepts previously described. The practical solutions of different machine vision problems or applications are the main aspect that differentiates this book from other well-known introductory books available in this domain. Although the authors state that the book is accessible to students and practitioners, if you do not have previous knowledge of the main concepts related to image processing, this book should be considered as a complement to a more introductory book on image processing and machine vision. Since this book is focused more on applications, the reader should start to learn about the main concepts of this domain before using this book as a guide. I suggest readers new to the topic start by reading some of the classic books in the field; then, they should read this book to help them understand how a practical machine vision system can be implemented. To conclude, this is a very interesting, complete, and up-to-date book about various aspects of solving real-world machine vision problems. The opportunity to use and test the machine vision software HALCON is also an important aspect of this book, allowing the reader to practice and develop machine vision solutions by using a very professional and complete software package. Online Computing Reviews Service
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