Computer and Machine Vision
Theory, Algorithms, Practicalities
- E. R. Davies, Royal Holloway, University of London, U.K.
Key features include:
- Practical examples and case studies give the âins and outsâ of developing real-world vision systems, giving engineers the realities of implementing the principles in practice.
- New chapters containing case studies on surveillance and driver assistance systems give practical methods on these cutting-edge applications in computer vision.
- Necessary mathematics and essential theory are made approachable by careful explanations and well-illustrated examples.
- Updated content and new sections cover topics such as human iris location, image stitching, line detection using RANSAC, performance measures, and hyperspectral imaging.
- The ârecent developmentsâ section now included in each chapter will be useful in bringing students and practitioners up to date with the subject.
AudienceEmbedded, electronic systems, signal/image processing and computer engineering R&D engineers; post graduates and PhD researchers in machine and computer vision.
- Published: March 2012
- Imprint: ACADEMIC PRESS
- ISBN: 978-0-12-386908-1
Table of Contents
1 Vision, the Challenge
2 Images and Imaging Operations
3 Basic Image Filtering Operations
4 Thresholding Techniques
5 Edge Detection
6 Corner and Interest Point Detection
7 Mathematical Morphology
9 Binary Shape Analysis
10 Boundary Pattern Analysis
11 Line Detection
12 Circle and Ellipse Detection
13 The Hough Transform and Its Nature
14 Abstract Pattern Matching Techniques
15 The Three-Dimensional World
16 Tackling the perspective n-point problem
17 Invariants and perspective
18 Image transformations and camera calibration
20 Automated Visual Inspection
21 Inspection of Cereal Grains
23 In-Vehicle Vision Systems24 Statistical Pattern Recognition
25 Image Acquisition
26 Real-Time Hardware and Systems Design Considerations
27 Epilogue-Perspectives in Vision
Appendix Robust statistics