Intelligent Visual Inspection

Rosandich, R.; Dagli, Cihan H.

ISBN 10: 0412708000 / ISBN 13: 9780412708008

Editore: Chapman and Hall, 1996

Explains the application of technology in the areas of artificial vision and neural networks to automated visual inspection. This book includes coverage of various aspects of the automated visual inspection problem, details of the HAVENET neural network and the CAMERA vision model, and descriptions of applications of intelligent visual inspection. Series: Intelligent Engineering Systems Series (Closed). Num Pages: 306 pages, biography. BIC Classification: TBMM; TD. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 156 x 19. Weight in Grams: 1390. . 1996. Hardback. . . . . Codice articolo V9780412708008

Riassunto:

A great deal of research is being done in the areas of artificial vision and neural networks. Although much of this research has been theoretical in nature, many of the techniques developed through these efforts are now mature enough for use in practical applications. This work explains the application of recently emerging technology in the areas of artificial vision and neural networks to automated visual inspection, aiming to to bridge the gap between theoretical research and practical application. Including broad coverage of all aspects of the automated visual inspection problem; details of the HAVENET neural network and the CAMERA vision model; and detailed descriptions of practical applications of intelligent visual inspection, the text should serve as a reference book for researchers and graduate students interested in the areas of artificial vision, neural networks, automated visual inspection and quality control.

Contenuti: One: Introduction.- 1. Intelligent manufacturing.- 1.1 Introduction.- 1.2 Definition of intelligence.- 1.3 Role of vision in intelligence.- 1.4 Modem manufacturing systems.- 1.5 Considerations in intelligent manufacturing systems design.- 2. Intelligent visual inspection.- 2.1 Vision systems for intelligent manufacturing.- 2.2 Definition of visual inspection.- 2.3 Objectives of visual inspection.- 2.4 Inspection errors.- 2.5 Categories of inspection.- 2.6 Areas of application for visual inspection.- 2.7 Benefits of automated inspection.- 2.8 Commercially applied inspection systems.- 2.9 Limitations of automated visual inspection.- 2.10 Research goals.- Two: Fundamentals of Artificial Vision Systems.- 3. Biological vision systems.- 3.1 Introduction.- 3.2 Basic physiology of vision systems.- 3.3 Human visual cognition.- 3.4 Object recognition.- 3.5 Summary.- 4. Artificial neural networks for pattern recognition.- 4.1 Introduction.- 4.2 Early artificial neural networks.- 4.3 Backpropagation neural networks.- 4.4 Self-organizing maps.- 4.5 Adaptive resonance theory and its derivatives.- 4.6 Neocognitron neural network.- 4.7 HAVNET neural network.- 4.8 Summary.- Three: Artificial Vision Systems Design.- 5. Image acquisition and storage.- 5.1 Introduction.- 5.2 Cameras.- 5.3 Object lighting and presentation.- 5.4 Image acquisition cards.- 5.5 Image processing hardware.- 5.6 Image formats.- 6.6 Low-level image processing.- 6.1 Introduction.- 6.2 Image size reduction.- 6.3 Noise removal and filtering.- 6.4 Thresholding and histograms.- 6.5 Region growing and hole filling.- 6.6 Edge detection.- 6.7 Primitive image features.- 6.8 Summary.- 7. Intermediate image processing.- 7.1 Introduction.- 7.2 Color representation and processing.- 7.3 Shape from shading.- 7.4 Stereo vision.- 7.5 Analysis of visual motion.- 7.6 Grouping primitive features into complex features.- 7.7 Summary.- 8. Computational approach to artificial vision.- 8.1 Introduction.- 8.2 The work of David Marr.- 8.3 ACRONYM vision system.- 8.4 SCERPO vision system.- 8.5 Recognition by components theory and the PARVO vision system.- 8.6 Summary.- 9. Connectionist approach to artificial vision.- 9.1 Introduction.- 9.2 Grossberg vision model.- 9.3 Seibert-Waxman vision model.- 9.4 CAMERA vision model.- 10. Experimental evaluation of the CAMERA vision model.- 10.1 Introduction.- 10.2 Experimental apparatus and conditions.- 10.3 Recognition of simple two-dimensional objects.- 10.4 Recognition of complex two-dimensional objects.- 10.5 Recognition of three-dimensional objects.- 10.6 Recognition accuracy.- 10.7 Recognition time.- 10.8 Summary of CAMERA evaluation.- Four: Case Studies.- 11. Automated visual inspection systems.- 11.1 Introduction.- 11.2 Inspection of polished silicon wafers.- 11.3 Inspection of pharmaceutical blister packages.- 11.4 Summary.- 12. Future of automated visual inspection.- 12.1 Introduction.- 12.2 Proposed flexible manufacturing system.- 12.3 Challenging visual inspection problem.- 12.4 Summary.- Appendix A.- Appendix B.- References.

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Titolo: Intelligent Visual Inspection
Casa editrice: Chapman and Hall
Data di pubblicazione: 1996
Legatura: Rilegato
Condizione: New