An Object-oriented expert system shell with image diagnosis.

by Chan Wai Kwong Samual.Thesis (M.Phil.)--Chinese University of Hong Kong.Bibliography: leaves R. 1-6.ACKNOWLEDGEMENTSABSTRACTTABLE OF CONTENTSChapter CHAPTER 1. --- OVERVIEWS --- p.1.1Chapter 1.1 --- Introduction --- p.1.1Chapter 1.2 --- Image Understanding and Artificial Intelligence --- p.1.3Chapter 1.3 --- Object-Oriented Programming and Artificial Intelligence --- p.1.6Chapter 1.4 --- Related Works --- p.1.8Chapter 1.5 --- Discussions and Outlines --- p.1.9Chapter CHAPTER 2. --- OBJECT-ORIENTED SOFTWARE SYSTEMS --- p.2.1Chapter 2.1 --- Introduction --- p.2.1Chapter 2.2 --- Traditional Software Systems --- p.2.1Chapter 2.3 --- Object-Oriented Software Systems --- p.2.2Chapter 2.4 --- Characteristics of an Object-Oriented Systems --- p.2.4Chapter 2.5 --- Knowledge Representation in Image Recognition --- p.2.9Chapter 2.5.1 --- Rule-Based System --- p.2.10Chapter 2.5.2 --- Structured Objects --- p.2.12Chapter 2.5.3 --- Object-Oriented Knowledge Management --- p.2.13Chapter 2.5.4 --- Object-Oriented Expert System Building Tools --- p.2.14Chapter 2.6 --- Concluding Remarks --- p.2.16Chapter CHAPTER 3. --- SYSTEM DESIGN AND ARCHITECTURE --- p.3.1Chapter 3.1 --- Introduction --- p.3.1Chapter 3.2 --- Inheritance and Recognition --- p.3.2Chapter 3.3 --- System Design --- p.3.9Chapter 3.4 --- System Architecture --- p.3.11Chapter 3.4.1 --- The Low Level Vision Kernel --- p.3.14Chapter 3.4.2 --- The High Level Vision Kernel --- p.3.15Chapter 3.4.3 --- User Consultation Kernel --- p.3.17Chapter 3.5 --- Structure of the Image Object Model --- p.3.17Chapter 3.5.1 --- Image Object Model in Object-Oriented Form --- p.3.19Chapter 3.5.2 --- Image Objects Hierarchy --- p.3.23Chapter 3.6 --- Reasoning in OOI --- p.3.26Chapter 3.7 --- Concluding Remarks --- p.3.27Chapter CHAPTER 4. --- CONTROL AND STRATEGIES --- p.4.1Chapter 4.1 --- Introduction --- p.4.1Chapter 4.2 --- Consultation Class Objects --- p.4.4Chapter 4.2.1 --- Audience --- p.4.5Chapter 4.2.2 --- Intrinsic Hypothesis (IH_object) --- p.4.5Chapter 4.2.3 --- Priority Table (PT_object) --- p.4.6Chapter 4.3 --- Operation Objects --- p.4.7Chapter 4.3.1 --- Scheme Scheduler (SS一object) --- p.4.7Chapter 4.3.2 --- Task Scheduler (TS_object) --- p.4.7Chapter 4.4 --- Taxonomy of Image Objects in OOI --- p.4.8Chapter 4.4.1 --- Object Template --- p.4.8Chapter 4.4.2 --- Attributes --- p.4.9Chapter 4.4.3 --- Tasks and Life Cycles --- p.4.9Chapter 4.4.4 --- Object Security --- p.4.10Chapter 4.5 --- Message Passing --- p.4.11Chapter 4.6 --- Strategies --- p.4.12Chapter 4.6.1 --- The Bottom-Up Approach --- p.4.15Chapter 4.6.2 --- The Top-Down Approach --- p.4.18Chapter 4.7 --- Concluding Remarks --- p.4.19Chapter CHAPTER 5. --- IMAGE PROCESSING ALGORITHMS --- p.5.1Chapter 5.1 --- Introduction --- p.5.1Chapter 5.2 --- Image Enhancement --- p.5.2Chapter 5.2.1 --- Spatial Filtering --- p.5.2Chapter 5.2.2 --- Feature Enhancement --- p.5.5Chapter 5.3 --- Pixel Classification --- p.5-7Chapter 5.4 --- Edge Detection Methods --- p.5.9Chapter 5.4.1 --- Local Gradient Operators --- p.5.9Chapter 5.4.2 --- Zero Crossing Method --- p.5.12Chapter 5.5 --- Regional Approaches in Segmentation --- p.5.13Chapter 5.5.1 --- Multi-level Threshold Method --- p.5.13Chapter 5.5.2 --- Region Growing --- p.5.15Chapter 5.6 --- Image Processing Techniques in Medical Domain --- p.5.17Chapter 5.7 --- Concluding Remarks --- p.5.18Chapter CHAPTER 6. --- PICTORIAL DATA MANAGEMENT IN OOI --- p.6.1Chapter 6.1 --- Introduction --- p.6.1Chapter 6.2 --- Description of Basic Properties --- p.6.1Chapter 6.3 --- Description of Relations --- p.6.7Chapter 6.3.1 --- Relational Database of Pictorial Data --- p.6.7Chapter 6.3.2 --- Relational Graphs and Relational Databases --- p.6.10Chapter 6.4 --- Access Functions in Image Objects --- p.6.14Chapter 6.4.1 --- Basic Access Functions --- p.6.14Chapter 6.4.2 --- User Accessible Functions in Objects --- p.6.15Chapter 6.5 --- Image Functions --- p.6.16Chapter 6.5.1 --- Unary Image operations --- p.6.16Chapter 6.5.2 --- Binary Relation Operations --- p.6.19Chapter 6.5.3 --- Update Operations --- p.6.20Chapter 6.6 --- Concluding Remarks --- p.6.21Chapter CHAPTER 7. --- KNOWLEDGE MANAGEMENT --- p.7.1Chapter 7.1 --- Introduction --- p.7.1Chapter 7.2 --- Knowledge in A Domain Knowledge Base --- p.7.1Chapter 7.2.1 --- Structure of Rules --- p.7.2Chapter 7.2.2 --- Hypothesis Generation --- p.7.6Chapter 7.2.3 --- Inference Engine --- p.7.8Chapter 7.3 --- Model Based Reasoning in OOI --- p.7.9Chapter 7.3.1 --- Merging and Labelling --- p.7.9Chapter 7.3.2 --- Vision Model --- p.7.11Chapter 7.4 --- Fuzzy Reasoning --- p.7.12Chapter 7.5 --- Concluding Remarks --- p.7.15Chapter CHAPTER 8. --- KNOWLEDGE ACQUISITION AND USER INTERFACES --- p.8.1Chapter 8.1 --- Introduction --- p.8.1Chapter 8.2 --- Knowledge Acquisition Subsystem --- p.8.3Chapter 8.2.1 --- Rule Management Module --- p.8.3Chapter 8.2.2 --- Attribute Management Module --- p.8.4Chapter 8.2.3 --- Model Management Module --- p.8.8Chapter 8.2.4 --- Methods of Knowledge Encoding and Acquisition --- p.8.9Chapter 8.3 --- User Interface in OOI --- p.8.11Chapter 8.3.1 --- Screen Layout --- p.8.13Chapter 8.3.2 --- Menus and Options --- p.8.15Chapter 8.4 --- Concluding Remarks --- p.8.20Chapter CHAPTER 9. --- IMPLEMENTATION AND RESULTS --- p.9.1Chapter 9.1 --- Introduction --- p.9.1Chapter 9.2 --- Using Expanded Memory --- p.9.2Chapter 9.3 --- ESCUM --- p.9.3Chapter 9.3.1 --- General Description --- p.9.3Chapter 9.3.2 --- Cervical Intraepithelial Neoplasia (CIN) --- p.9.4Chapter 9.3.3 --- Development of ESCUM --- p.9.5Chapter 9.4 --- Results --- p.9.12Chapter 9.5 --- Concluding Remarks --- p.9.13Chapter CHAPTER 10. --- CONCLUSION --- p.10.1Chapter 10.1 --- Summary --- p.10.1Chapter 10.2 --- Areas of Future Work --- p.10.5Chapter APPENDIX A. --- Rule Base of ESCUM --- p.A1Chapter APPENDIX B. --- Glossary for Objected-Oriented Programming --- p.B1REFERENCES --- p.R

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Cascaded Segmentation-Detection Networks for Word-Level Text Spotting

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IMPLEMENTATION OF A LOCALIZATION-ORIENTED HRI FOR WALKING ROBOTS IN THE ROBOCUP ENVIRONMENT

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A Neural Network Architecture for Figure-ground Separation of Connected Scenic Figures

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Object-Oriented Dynamics Learning through Multi-Level Abstraction

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