Computer and Machine Vision

Informationen zum Autor Roy Davies was Emeritus Professor of Machine Vision at Royal Holloway, University of London. He worked on many aspects of vision, from feature detection to robust, real-time implementations of practical vision tasks. His interests included automated visual inspection, surveillance, vehicle guidance, crime detection and neural networks. He has published more than 200 papers, and three books. Machine Vision: Theory, Algorithms, Practicalities (1990) has been widely used internationally for more than 25 years, and is now out in this much enhanced fifth edition. Roy held a DSc at the University of London and was awarded Distinguished Fellow of the British Machine Vision Association, and Fellow of the International Association of Pattern Recognition. Zusammenfassung Presents the basic methodology of computer and machine vision! covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This text contains case studies on surveillance and driver assistance systems that give practical methods on these advanced applications in computer vision.

Autorentext
Roy Davies was Emeritus Professor of Machine Vision at Royal Holloway, University of London. He worked on many aspects of vision, from feature detection to robust, real-time implementations of practical vision tasks. His interests included automated visual inspection, surveillance, vehicle guidance, crime detection and neural networks. He has published more than 200 papers, and three books. Machine Vision: Theory, Algorithms, Practicalities (1990) has been widely used internationally for more than 25 years, and is now out in this much enhanced fifth edition. Roy held a DSc at the University of London and was awarded Distinguished Fellow of the British Machine Vision Association, and Fellow of the International Association of Pattern Recognition.

Klappentext

Presents the basic methodology of computer and machine vision, covering the essential elements of the theory while emphasizing algorithmic and practical design constraints. This text contains case studies on surveillance and driver assistance systems that give practical methods on these advanced applications in computer vision.

Inhalt

1. Vision, the Challenge2. Images and Imaging Operations3. Basic Image Filtering Operations4. Thresholding Techniques5. Edge Detection6. Corner and Interest Point Detection7. Mathematical Morphology8. Texture9. Binary Shape Analysis10. Boundary Pattern Analysis11. Line Detection12. Circle and Ellipse Detection13. The Hough Transform and Its Nature14. Abstract Pattern Matching Techniques15. The Three-Dimensional World16. Tackling the perspective n-point problem17. Invariants and perspective18. Image transformations and camera calibration19. Motion20. Automated Visual Inspection21. Inspection of Cereal Grains22. Surveillance23. In-Vehicle Vision Systems24 Statistical Pattern Recognition25. Image Acquisition26. Real-Time Hardware and Systems Design Considerations27. Epilogue - Perspectives in VisionAppendix Robust statistics