The application of intelligent imaging techniques to industrial vision problems is an evolving aspect of current machine vision research. Machine vision is a relatively new technology, more concerned with systems engineering than with computer science, and with much to offer the manufacturing industry in terms of improving efficiency, safety and product quality. Beginning with an introductory chapter on the basic concepts, the authors develop these ideas to describe intelligent imaging techniques for use in a new generation of industrial imaging systems. Sections cover the application of AI languages such as Prolog, the use of multi-media interfaces and multi-processor systems, external device control, and colour recognition. The text concludes with a discussion of several case studies that illustrate how intelligent machine vision techniques can be used in industrial applications.
Inhaltsverzeichnis
1 Basic Concepts. - 1. 1 Industrial Vision Systems. - 1. 2 Systems Engineering. - 1. 3 Intelligent Vision. - 1. 4 Book Outline. - 2 Basic Machine Vision Techniques. - 2. 1 Representations of Images. - 2. 2 Elementary Image Processing Functions. - 2. 3 Binary Images. - 2. 4 Binary Mathematical Morphology. - 2. 5 Grey Scale Morphology. - 2. 6 Global Image Transforms. - 2. 7 Texture Analysis. - 2. 8 Implementation Considerations. - 2. 9 Commercial Devices. - 2. 10 Further Remarks. - 3 Intelligent Image Processing. - 3. 1 Interactive Image Processing. - 3. 2 Introducing PrologH-. - 3. 3 Review of Prolog. - 3. 4 The Nature of Prolog+. - 3. 5 Prolog+Programs. - 3. 6 Abstract Concepts in Prolog+. - 3. 7 Implementation of Prolog+. - 3. 8 Comments. - 4 Enhanced Intelligent Systems. - 4. 1 Prolog+ Environment: A Tool-box for Machine Vision. - 4. 2 Understanding Simple Spoken Instructions. - 4. 3 Aids for Designing Vision Systems. - 4. 4 Multi-camera Systems. - 4. 5 Comments. - 5 Controlling External Devices. - 5. 1 Devices and Signals. - 5. 2 Protocols and Signals. - 5. 3 Programmable Logic Controller. - 5. 4 General Purpose Interface Unit. - 5. 5 Flexible Inspection Cell, Design Issues. - 5. 6 Prolog+ Predicates for Device Control. - 5. 7 System Calibration. - 5. 8 Picking up a Randomly Placed Object (Overhead Camera). - 5. 9 Grippers. - 5. 10 Summary. - 6 Colour Image Recognition. - 6. 1 Introduction. - 6. 2 Applications of Coarse Colour Discrimination. - 6. 3 Why is a Banana Yellow? . - 6. 4 Machines for Colour Discrimination. - 6. 5 Ways of Thinking about Colour. - 6. 6 Programmable Colour Filter (PCF). - 6. 7 Colour Recognition in Prolog+ Programs. - 6. 8 Discussion and Conclusions. - 7 Applications of Intelligent Vision. - 7. 1 Recognition of Printed Patterns. - 7. 2 Manipulation of Planar Objects. - 7. 3 Packing and Depletion. - Blob Packing. - Polygon Packing. - Predicates. -7. 4 Handedness of Mirror-Image Components. - Relating Chirality and Handedness. - Formal Definition. - Generating Concavity Trees. - Sample Concavity Trees. - Canonical Form of Concavity Trees. - Program to find Chirality. - Instability. - 7. 5 Telling the Time. - 7. 6 Food and Agricultural Products. - 8 Concluding Remarks. - References. - A Proverbs, Opinions and Folklore. - B Factors to be Considered when Designing a Vision System. - C General Reference Material. - D PIP Software Implementation of Prolog+. - E Prolog+ and PIP Commands. - Glossary of Terms. - Index of Predicates, Operators and Grammar Rules.
