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Off-line recognition system for printed Chinese characters.

Sin Ka Wai. / Thesis (M.Sc.)--Chinese University of Hong Kong, 1992. / Includes bibliographical references (leaves [81]-[82]). / 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 / Chapter §2.1 --- Idea --- p.15 / Chapter §2.2 --- Feature Extraction / Chapter §2.2.1 --- Feature selection criteria --- p.15 / Chapter §2.2.2 --- 4C code --- p.20 / Chapter §2.2.3 --- Regional code --- p.22 / Chapter §2.2.4 --- Walsh Transform --- p.24 / Chapter §2.2.5 --- Black dot density projection profile --- p.26 / Chapter §2.2.6 --- Corner features --- p.28 / Chapter §2.3 --- Clustering Method -K-MEANS & Other Algorithms --- p.32 / Chapter §2.4 --- Pros & Cons --- p.35 / Chapter §2.5 --- Decision Table --- p.37 / Chapter §2.6 --- The Optimum Classifier & its Implemen- tation difficulties --- p.39 / Chapter §3. --- APPROACH 2 - SUPERVISED LEARNING --- p.43 / Chapter §4. --- POSSIBLE IMPROVEMENT / Chapter §4.1 --- Training and Test Sample Reduction --- p.46 / Chapter §4.2 --- Noise Filtering --- p.46 / Chapter §4.3 --- Decision with Overlapping --- p.52 / Chapter §4.4 --- Back Tracking for Holes --- p.56 / Chapter §4.5 --- Fuzzy Decision with Tolerance Limit --- p.59 / Chapter §4.6 --- Different Tree Architecture --- p.63 / Chapter §4.7 --- Building Decision Tree by Entropy Reduction Method --- p.65 / Chapter §5. --- EXPERIMENTAL RESULTS & THE IMPROVED MULTISTAGE CLASSIFIER / Chapter §5.1 --- Experimental Results --- p.70 / Chapter §5.2 --- Conclusion --- p.81 / Chapter §6. --- IMPROVED MULTISTAGE TREE CLASSIFIER / Chapter §6.1 --- The Optimal Multistage Tree Classifier --- p.83 / Chapter §6.2 --- Performance Analysis --- p.84 / Chapter §7. --- FURTHER DISCRIMINATION BY CONTEXT CONSIDERATION --- p.87 / Chapter §8. --- CONCLUSION / Chapter §8.1 --- Advantage of the Classifier --- p.89 / Chapter §8.2 --- Limitation of the Classifier --- p.90 / Chapter §9. --- AREA OF FUTURE RESEARCH AND IMPROVEMENT / Chapter §9.1 --- Detailed Analysis at Each Terminal Node --- p.91 / Chapter §9.2 --- Improving the Noise Filtering Technique --- p.92 / Chapter §9.3 --- The Use of 4 Corner Code --- p.93 / Chapter §9.4 --- Increase in the Dimension of the Feature Space --- p.95 / Chapter §9.5 --- 1-Tree Protocol with Entropy Reduction --- p.96 / Chapter §9.6 --- The Use of Human Intelligence --- p.97 / APPENDICES / Chapter A.1 --- K-MEANS / Chapter A.2 --- Maximum Distance Algorithm & ISODATA Algorithm / Chapter A.3 --- Approach Two - Supervised Learning / Chapter A.4 --- Theories on Statistical Discriminant Analysis / Chapter A.5 --- An Example of Misclassification Table / Chapter A.6 --- "Listing of the Program ""CHDIS.C""" / Chapter A.7 --- Further Discrimination by Context Consideration / Chapter A.8 --- Passage used in Testing the Performance of the Classifier with Context Consideration / Chapter A.9 --- A Partial List of Semantically Related Chinese Characters / REFERENCE

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_318967
Date January 1992
ContributorsSin, Ka Wai., Chinese University of Hong Kong Graduate School. Division of Information Engineering.
PublisherChinese University of Hong Kong
Source SetsThe Chinese University of Hong Kong
LanguageEnglish
Detected LanguageEnglish
TypeText, bibliography
Formatprint, 97, 79 leaves : ill. ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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