Thesis (M. Sc.)--University of Hong Kong, 2006. / Also available in print.

published_or_final_version / Computer Science / Master / Master of Philosophy

Thesis (M.A.)--Guo li Taiwan gong ye ji shu xue yuan, 1983. / Includes bibliographical references.

Thesis (M. Ed.)--University of Hong Kong, 1999. / Includes bibliographical references (leaves 93-98).

Thesis (M. Phil.)--University of Hong Kong, 1997. / Includes bibliographical references (leaf 75-79).

Thesis (M.Ed.)--University of Hong Kong, 1999. / Includes bibliographical references (leaves 93-98). Also available in print.

by Lo I Fan. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references. / Chapter Chapter 1: --- Introduction / Chapter 1.1 --- The Evolution of Fonts --- p.1 / Chapter 1.2 --- Bitmap Fonts --- p.2 / Chapter 1.3 --- Outline Fonts / Chapter 1.3.1 --- Arc and Vector Form --- p.4 / Chapter 1.3.2 --- Spline Form --- p.4 / Chapter 1.3.3 --- Pros and Cons of Outline Fonts --- p.8 / Chapter 1.4 --- Examples of Outline Fonts / Chapter 1.4.1 --- Adobe's PostScript --- p.9 / Chapter 1.4.2 --- Apple's and Microsoft TrueType / Chapter 1.4.2.1 --- Outline Representation --- p.10 / Chapter 1.4.2.2 --- Rasterisation --- p.12 / Chapter 1.4.2.3 --- Hinting --- p.13 / Chapter 1.5 --- Bold Fonts / Chapter 1.5.1 --- Definition of Bold --- p.15 / Chapter 1.5.2 --- Definition of Auto B oldness --- p.16 / Chapter 1.5.3 --- Auto Boldness by Double Printing --- p.17 / Chapter 1.5.4 --- Auto Boldness by Multi-Master Technique --- p.18 / Chapter 1.6 --- Chinese Fonts / Chapter 1.6.1 --- Chinese Character Sets --- p.19 / Chapter 1.6.2 --- The Subtleties of Chinese Fonts Auto Boldness --- p.21 / Chapter 1.7 --- Project Objective --- p.23 / Chapter 1.8 --- Goals --- p.23 / Chapter Chapter 2: --- Main Ideas of Chinese Font Auto Boldness / Chapter 2.1 --- Prototype of Auto Boldness Driver --- p.24 / Chapter 2.2 --- Design Features of the Prototype Auto Boldness Driver --- p.25 / Chapter 2.3 --- Data Structure and Algorithm of Auto Boldness / Chapter 2.3.1 --- Data Structure of TrueType Character Outline --- p.27 / Chapter 2.3.2 --- Algorithm of Auto Boldness --- p.28 / Chapter 2.3.3 --- Algorithm Description --- p.29 / Chapter 2.4 --- Component Font Auto Boldness --- p.35 / Chapter Chapter 3: --- Language of Auto Boldness / Chapter 3.1 --- Enhancements of TrueType Engine to support Auto Boldness --- p.36 / Chapter 3.2 --- Symmetric Bold Instruction --- p.38 / Chapter 3.3 --- Rotate Bold Instruction --- p.47 / Chapter 3.4 --- Asymmetric B old Instruction --- p.50 / Chapter 3.5 --- Comparison of Bold Instructions --- p.54 / Chapter 3.6 --- Serif Accommodation Instruction --- p.55 / Chapter Chapter 4: --- Shape Parsing and Auto Bold Code Generation / Chapter 4.1 --- Compilation Process and Auto Boldness --- p.62 / Chapter 4.2 --- Shape Lexical Analyzer --- p.64 / Chapter 4.3 --- Shape Token Attributes Evaluation / Chapter 4.3.1 --- line Token --- p.66 / Chapter 4.3.2 --- bezier2 Token --- p.67 / Chapter 4.3.3 --- sharp Token --- p.70 / Chapter 4.3.4 --- concave Token --- p.75 / Chapter 4.3.5 --- convex Token --- p.75 / Chapter 4.4 --- Scope of Shape Parsing --- p.76 / Chapter 4.5 --- Shape Parsing Mechanism --- p.77 / Chapter 4.6 --- Model Grammar Rules / Chapter 4.6.1 --- Grammar Rule Format --- p.81 / Chapter 4.6.2 --- Grammar Rule Item --- p.82 / Chapter 4.6.3 --- Grammar Rule Assignment --- p.83 / Chapter 4.6.4 --- Grammar Rule Condition --- p.83 / Chapter 4.7 --- Auto Boldness Code Generation --- p.84 / Chapter 4.8 --- Program Methodology of Prototype Auto Boldness Driver --- p.86 / Chapter Chapter 5: --- Conclusions / Chapter 5.1 --- Work Achieved --- p.87 / Chapter 5.2 --- The Pros and Cons of Auto Boldness Algorithm --- p.88 / Chapter 5.3 --- Bold Quality Assessments --- p.91 / Chapter 5.3 --- Future Directions --- p.93 / References / Appendix One / Appendix Two

by Wong Tsz Kin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 45-47). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Characteristics of Chinese Character --- p.2 / Chapter 1.1.1 --- The Nature of Chinese Language --- p.2 / Chapter 1.1.2 --- The Structure of Chinese Characters --- p.3 / Chapter 1.1.3 --- Basic Writing Strokes --- p.3 / Chapter 1.1.4 --- Writing Stroke Sequencing --- p.3 / Chapter 1.1.5 --- Geographic Structure of Components --- p.4 / Chapter 1.2 --- Stroke Distribution of Chinese Characters --- p.5 / Chapter 1.3 --- Radical --- p.5 / Chapter 1.4 --- Overview --- p.6 / Chapter 1.5 --- Objective --- p.10 / Chapter 2 --- Preprocessing --- p.12 / Chapter 2.1 --- Smoothing and Sampling --- p.12 / Chapter 2.2 --- Interpolation --- p.13 / Chapter 2.3 --- Dehooking --- p.13 / Chapter 2.4 --- Normalization --- p.14 / Chapter 2.5 --- Stroke Segmentation --- p.15 / Chapter 3 --- Preclassification --- p.18 / Chapter 3.1 --- Feature Analysis --- p.18 / Chapter 3.2 --- Radical Detection --- p.20 / Chapter 3.3 --- Description of The Preclassification Component --- p.22 / Chapter 3.4 --- Results and Conclusions --- p.23 / Chapter 4 --- The Recognition Stage --- p.25 / Chapter 4.1 --- Introduction --- p.25 / Chapter 4.2 --- Stroke Match Algorithm --- p.26 / Chapter 4.3 --- Relation Match Stage --- p.30 / Chapter 4.3.1 --- Introduction --- p.30 / Chapter 4.4 --- Final Classification --- p.35 / Chapter 5 --- Results and Conclusions --- p.39 / Chapter 5.1 --- Experiment Results --- p.39 / Chapter 5.2 --- Analysis --- p.39 / Chapter 5.3 --- Conclusions

Yeung Lap Kei. / Thesis (M.Sc.)--Chinese University of Hong Kong, 1992. / Includes bibliographical references (leaves [14-15]). / PREFACE / ABSTRACT / CONTENT / Chapter §1. --- INTRODUCTION / Chapter §1.1 --- The Chinese language --- p.1 / Chapter §1.2 --- Chinese information processing system --- p.2 / Chapter §1.3 --- Chinese character recognition --- p.4 / Chapter §1.4 --- Multi-stage tree classifier Vs Single-stage tree classifier in Chinese character recognition --- p.6 / Chapter §1.5 --- Decision Tree / Chapter §1.5.1 --- Basic Terminology of a decision tree --- p.7 / Chapter §1.5.2 --- Structure design of a decision tree --- p.10 / Chapter §1.6 --- Motivation of the project --- p.12 / Chapter §1.7 --- Objects of the project --- p.14 / Chapter §1.8 --- Development environment --- p.14 / Chapter §2. --- APPROACH 1 - UNSUPERVISED LEARNING --- p.15 / Chapter §3. --- APPROACH 2 - SUPERVISED LEARNING / Chapter §3.1 --- Idea --- p.17 / Chapter §3.2 --- The 3 Corner Code --- p.20 / Chapter §3.3 --- Feature Extraction & Selection --- p.22 / Chapter §3.4 --- Decision at Each Node / Chapter §3.4.1 --- Statistical Linear Discriminant Analysis --- p.22 / Chapter §3.4.2 --- Optimization of the Number of Misclassification --- p.24 / Chapter §3.5 --- Implementation / Chapter §3.5.1 --- Training Data --- p.36 / Chapter §3.5.2 --- Clustering with the Use of SAS --- p.38 / Chapter §3.5.3 --- Building the Decision Trees --- p.42 / Chapter §3.5.4 --- Description of the Classifier --- p.45 / Chapter §3.6 --- Experiments and Testing Result / Chapter §3.6.1 --- Performance Parameters being Measured --- p.47 / Chapter §3.6.2 --- Testing by Resubstitution Method --- p.50 / Chapter §3.6.3 --- Noise Model --- p.52 / Chapter §4. --- POSSIBLE IMPROVEMENT --- p.55 / Chapter §5. --- EXPERIMENTAL RESULTS & THE IMPROVED MULTISTAGE CLASSIFIER / Chapter §5.1 --- Experimental Results --- p.59 / Chapter §5.2 --- Conclusion --- p.70 / Chapter §6. --- IMPROVED MULTISTAGE TREE CLASSIFIER / Chapter §6.1 --- The Optimal Multistage Tree Classifier --- p.72 / Chapter §6.2 --- Performance Analysis --- p.73 / Chapter §7. --- FURTHER DISCRIMINATION BY CONTEXT CONSIDERATION / Chapter §7.1 --- Idea --- p.76 / Chapter §7.2 --- Description of Algorithm --- p.78 / Chapter §7.3 --- Performance Analysis --- p.81 / Chapter §8. --- CONCLUSION / Chapter §8.1 --- Advantage of the Classifier --- p.84 / Chapter §8.2 --- Limitation of the Classifier --- p.85 / Chapter §9. --- AREA OF FUTURE RESEARCH AND IMPROVEMENT / Chapter §9.1 --- Detailed Analysis at Each Terminal Node --- p.86 / Chapter §9.2 --- Improving the Noise Filtering Technique --- p.87 / Chapter §9.3 --- The Use of 4 Corner Code --- p.88 / Chapter §9.4 --- Increase in the Dimension of the Feature Space --- p.90 / Chapter §9.5 --- 1-Tree Protocol with Entropy Reduction --- p.91 / Chapter §9.6 --- The Use of Human Intelligence --- p.92 / APPENDICES / Chapter A.1 --- K-MEANS / Chapter A.2 --- Unsupervised Learning Approach / Chapter A.3 --- Other Algorithms (Maximum Distance & ISODATA) / Chapter A.4 --- Possible Improvement / Chapter A.5 --- Theories on Statistical Discriminant Analysis / Chapter A.6 --- Passage used in Testing the Performance of the Classifier with Context Consideration / Chapter A.7 --- A Partial List of Semantically Related Chinese Characters / Chapter A.8 --- An Example of Misclassification Table / Chapter A.9 --- "Listing of the Program ""CHDIS.C""" / REFERENCE

by Poon Chi-cheung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 82-84). / Abstract / Acknowledgments / Preface / Chapter Chapter 1: --- Font Systems --- p.1 / Representations of Character Images --- p.1 / Characteristics of Chinese Font System --- p.3 / Large Character Set --- p.3 / Condensed Strokes --- p.4 / Low Repetition Rate --- p.5 / WYSIWYG (What You See Is What You Get) --- p.6 / Chapter Chapter 2: --- Human Visual System and Gray Scale Font --- p.9 / Human Visual System --- p.9 / Physiology --- p.9 / Spatial Frequencies --- p.10 / How much resolution is enough --- p.11 / Screen and Printer --- p.12 / Raster Display Devices --- p.13 / Printer --- p.14 / Resolution --- p.15 / Gray Scale Font --- p.15 / Generation of Gray Scale Font --- p.18 / Chapter Chapter 3: --- Digital Filtering Method for Gray Scale Font --- p.19 / Filtering Process --- p.19 / Weighted Functions --- p.21 / Generation of Gray Scale Character --- p.23 / Results --- p.24 / More Experiments --- p.24 / Problems --- p.26 / Speed and Storage --- p.26 / Impression of Strokes --- p.27 / Thin strokes in the small-size character --- p.30 / New Approach to Generate Gray Scale Font --- p.30 / Chapter Chapter 4: --- Rasterization Algorithms --- p.32 / Outline Font --- p.32 / TrueType Font --- p.33 / Scan Conversion --- p.35 / Basic Outline-to-Bitmap Conversion --- p.35 / Scan-converting Polygon --- p.36 / Rasterization of a character --- p.36 / Intersecting Points and Ranges --- p.37 / Straight Lines --- p.37 / Quadratic Bezier Curves --- p.38 / Implementation Techniques --- p.39 / Approximation of quadratic Bezier curve by straight lines --- p.39 / Simplification of the Filling Process --- p.41 / The Rasterization Algorithm --- p.45 / Chapter Chapter 5: --- Direct Rasterization with Gray Scale --- p.46 / Rasterization with Gray Scale --- p.46 / Determination of Gray Value of Boundary-pixel --- p.50 / Preliminary Results --- p.54 / Hinting --- p.56 / Rasterization with Hinting --- p.56 / Strokes Migration --- p.57 / Hints Finding --- p.59 / Chapter Chapter 6: --- Results and Conclusion --- p.62 / Quality --- p.66 / Comparison with Black-and-White Character --- p.66 / Hinted Against Unhinted --- p.71 / Generation Speeds --- p.75 / Discussion and Comments --- p.78 / Practical Font System --- p.79 / Conclusion --- p.80 / Bibliography --- p.82