Machine Vision Algorithms and Applications

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 (www.machine–vision–book.com)

Spis treści:
Preface.
1. Introduction.
2. Image Acquisition.
3. Machine Vision Algorithms.
4. Machine Vision Applications.
References.
Index.

Nota biograficzna:
Carsten Steger studied computer science at Technische Universität München (TUM) and received his PhD from TUM in 1998. In 1996, he co–founded the company MVTec, where he heads the Research and Development department.
He has authored and co–authored more than 60 scientific publications in the field of machine vision. Carsten Steger is also a guest lecturer at the Technische Universität München, where he teaches machine vision.
Markus Ulrich studied Geodesy and Remote Sensing at Technische Universität München (TUM) and received his PhD from TUM in 2003. Since 2003, he is a software engineer at the Research and Development department of MVTec. He has authored and co–authored scientific publications in the fields of photogrammetry and machine vision.
Markus Ulrich is also a guest lecturer at the Technische Universität München, where he teaches close–range photogrammetry.
Christian Wiedemann studied Geodesy and Remote Sensing at
Technische Universität München (TUM) and received his PhD from TUM in 2001. He has authored and co–authored more than 40 scientific publications in the fields of photogrammetry, remote sensing, and machine vision. Since 2003, he is a software engineer at the Research and Development department of MVTec.

Okładka tylna:
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 (www.machine–vision–book.com)