Machine Vision Algorithms and Applications

INTRODUCTION

IMAGE ACQUISITION
Illumination
Lenses
Cameras
Camera-Computer Interfaces

MACHINE VISION ALGORITHMS
Fundamental Data Structures
Image Enhancement
Geometric Transformations
Image Segmentation
Feature Extraction
Morphology
Edge Extraction
Segmentation and Fitting of Geometric Primitives
Camera Calibration
Stereo Reconstruction
Template Matching
Optical Character Recognition

MACHINE VISION APPLICATIONS
Wafer Dicing
Reading of Serial Numbers
Inspection of Saw Blades
Print Inspection
Inspection of Ball Grid Arrays
Surface Inspection
Measuring of Spark Plugs
Molding Flash Detection
Inspection of Punched Sheets
3D Plane Reconstruction with Stereo
Pose Verification and Resistors
Classification of Non-Woven Fabrics

The second edition of this successful machine vision textbook is completely updated, revised and expanded by 15% to reflect the developments of recent years in the fields of image acquisition, machine vision algorithms and applications. The new content includes, but is not limited to, a discussion of new cameras and image acquisition interfaces, 3D sensors and technologies, 3D object recognition and 3D image reconstruction. The authors retain their balanced approach with sufficient coverage of the theory and a strong focus on applications. All examples are based on the latest version of the machine vision software HALCON 13, a trial version of which is available from the authors' website.

Author Information

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.