| 摘要 | 第5-8页 |
| ABSTRACT | 第8-10页 |
| 1 THESIS INTRODUCTION | 第17-28页 |
| 1.1 Research Background & Problem Statement | 第17-19页 |
| 1.1.1 Research Background | 第17-18页 |
| 1.1.2 Problem Statement | 第18-19页 |
| 1.2 Importance of the Problem | 第19-21页 |
| 1.3 Literature Review | 第21-25页 |
| 1.3.1 Biological Vision Systems | 第21页 |
| 1.3.2 Biologically Inspired Artificial Vision Systems | 第21-25页 |
| 1.4 Shortcomings of Existing Models and Research Objectives | 第25-27页 |
| 1.4.1 Shortcomings of Existing Models | 第25-26页 |
| 1.4.2 Motivation,Research Objectives and Innovation | 第26-27页 |
| 1.5 Thesis Outline | 第27-28页 |
| 2 BIO-INSPIRED MACHINE VISION SYSTEM-A PRE-REQUISITE | 第28-37页 |
| 2.1 Introduction | 第28页 |
| 2.2 Information Processing across the Visual Cortex | 第28-30页 |
| 2.3 Biologically Inspired Color Vision Models | 第30-33页 |
| 2.3.1 Trichromatic Vision | 第30-32页 |
| 2.3.2 Theory of Opponent-Color | 第32页 |
| 2.3.3 Color Opponency and Ganlion Cells | 第32-33页 |
| 2.4 Bologically Inspired Feature Extraction-HMAX Model | 第33-34页 |
| 2.5 Biologically Inspired Feature Classifier-Extreme Learning Machine | 第34-35页 |
| 2.6 Summary | 第35-37页 |
| 3 DEVELOPMENT OF A BIOLOGICALLY INSPIRED MODEL OF COLOR MACHINEVISION | 第37-48页 |
| 3.1 Introduction | 第37页 |
| 3.2 Proposed Color Machine Vision Model | 第37-47页 |
| 3.2.1 RGB Color Descriptor | 第39-42页 |
| 3.2.2 Integration with HMAX model | 第42页 |
| 3.2.3 SVM Classifier | 第42页 |
| 3.2.4 Experimental Setup | 第42-43页 |
| 3.2.5 Classification: | 第43页 |
| 3.2.6 Performance Evaluation: | 第43页 |
| 3.2.7 Results and Discussions | 第43-46页 |
| 3.2.8 Conclusions | 第46-47页 |
| 3.3 ummary | 第47-48页 |
| 4 IMPROVEMENT OF THE DEVELOPED BIO-INSPIRED COLOR MACHINE VISIONBASED ON DEEP LEARNING | 第48-59页 |
| 4.1 Introduction | 第48页 |
| 4.2 Deep Learning Classifier based on the Extreme Learning Machine | 第48-49页 |
| 4.3 Proposed Method | 第49-54页 |
| 4.3.1 Biologically inspired Deep ELM-based pattern recognition network design (D-ELM) | 第50-54页 |
| 4.4 Experiments | 第54-58页 |
| 4.4.1 Results and Discussion | 第55-57页 |
| 4.4.2 Conclusions | 第57-58页 |
| 4.5 Summary | 第58-59页 |
| 5 APPLICATIONS OF THE DEVELOPED ALGORITHM IN THE AUTOMATION | 第59-77页 |
| 5.1 Introduction | 第59页 |
| 5.2 Experimental Setup to Validate the Developed Model | 第59-60页 |
| 5.3 The Development of the Visual Inspection System for the Baked Food | 第60-68页 |
| 5.3.1 Experimental Setup for Baked Food Inspection | 第61-63页 |
| 5.3.2 Results & Discussions of Baked Food Inspection | 第63-68页 |
| 5.3.3 Conclusions of Baked Food Inspection | 第68页 |
| 5.4 The Identification System for the Traffic Signs to Assist Self-Driving Cars | 第68-70页 |
| 5.4.1 Experimental Setup of Traffic Sign Recognition | 第69页 |
| 5.4.2 Results of Traffic Sign Recognition | 第69-70页 |
| 5.4.3 Conclusion of Traffic Sign Recognition | 第70页 |
| 5.5 Macro-Level Visual Assessment of the Fabric Weave Pattern and Yarn Color | 第70-76页 |
| 5.5.1 Experimental Setup of Fabric Inspection | 第71-73页 |
| 5.5.2 Results and Discussions of Fabric Inspection | 第73-75页 |
| 5.5.3 Performance Evaluation of Fabric Inspection | 第75页 |
| 5.5.4 Conclusion of Fabric Inspection | 第75-76页 |
| 5.6 Chapter Summary | 第76-77页 |
| 6 SUMMARY AND FUTURE RECOMMENDATION | 第77-81页 |
| 6.1 Summary | 第77-80页 |
| 6.2 Future Recommendations | 第80-81页 |
| References | 第81-93页 |
| List of Publications | 第93-94页 |
| Acknowledgements | 第94页 |
