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Machine Vision Algorithms and Applications
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Table of Contents

Image Acquisition (illumination, lenses, cameras, frame grabbers, bus systems) Machine Vision Algorithms (Data structures, Image enhancement, image transformations, segemntation, feature extraction, morphology, template matching, stereo reconstruction, camera calibration, FFT, color, texture, etc.) Machine Vision Applications (application examples, descriptions on how to solve them with the methods discussed in the book, example code with HALCON - MVTec's premier machine vision software, possibly further exercises)

About the Author

Carsten Steger studied computer science at Technische Universitat Munchen (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 Universitat Munchen, where he teaches machine vision. Markus Ulrich studied Geodesy and Remote Sensing at Technische Universitat Munchen (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 Universitat Munchen, where he teaches close-range photogrammetry. Christian Wiedemann studied Geodesy and Remote Sensing at Technische Universitat Munchen (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.

Reviews

"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 HALCOM 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." ( Computing Reviews , January 21, 2009) "This textbook for machine vision software not only covers the relevant algorithms in theory, but also figures out their practical use." ( openPR.com , September 2008)

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