A methodology for constructing compact Chinese font libraries by radical composition.

by Wai-Yip Tung.Thesis (M.Phil.)--Chinese University of Hong Kong, 1993.Includes bibliographical references (leaves 55-56).Chapter 1. --- Introduction --- p.1Chapter 1.1. --- Previous work --- p.2Chapter 1.1.1. --- A Chinese METAFONT --- p.2Chapter 1.1.2. --- Chinese character generator --- p.2Chapter 1.1.3. --- Chinese Character Design System CCDS --- p.2Chapter 1.2. --- Goals of the thesis --- p.3Chapter 1.3. --- Overview of the thesis --- p.3Chapter 2. --- Construction of Chinese Characters --- p.5Chapter 2.1 --- Introduction --- p.5Chapter 2.2. --- liu shu(六書）Six Principles of Chinese Character Construction --- p.5Chapter 2.3. --- Structural Analysis of Chinese Characters --- p.7Chapter 2.3.1. --- Left-Right Structure --- p.8Chapter 2.3.2. --- Top-Bottom Structure --- p.9Chapter 2.3.3. --- Inside-Outside Structure --- p.10Chapter 2.3.4. --- Singleton Structure --- p.10Chapter 2.4. --- Usage frequency of radicals --- p.11Chapter 2.5. --- Usage frequency of Bushou --- p.11Chapter 2.6. --- Usage frequency of Shengpang --- p.13Chapter 2.7. --- Summary --- p.15Chapter 3. --- Composition by Radicals --- p.17Chapter 3.1. --- Introduction --- p.17Chapter 3.2. --- Transforming radicals --- p.18Chapter 3.3. --- Quality of transformed radicals --- p.19Chapter 3.4. --- Lower level components --- p.20Chapter 3.5. --- Summary --- p.23Chapter 4. --- Automatic Hinting for Chinese Font --- p.24Chapter 4.1 --- Introduction --- p.24Chapter 4.2. --- Automatic hinting for Chinese font --- p.26Chapter 4.3. --- Stroke recognition --- p.30Chapter 4.3.1. --- Identify horizontal lines --- p.31Chapter 4.3.2. --- Identify stroke segments --- p.31Chapter 4.3.3. --- Stroke recognition --- p.32Chapter 4.4. --- Regularize stroke width --- p.33Chapter 4.5. --- Grid-fitting horizontal and vertical strokes --- p.33Chapter 4.6. --- Grid-fitting radicals --- p.37Chapter 4.7. --- Summary --- p.39Chapter 5. --- RADIT - A Chinese Font Editor --- p.41Chapter 5.1. --- Introduction --- p.41Chapter 5.2. --- RADIT basics --- p.41Chapter 5.2.1. --- Character selection window --- p.42Chapter 5.2.2. --- Character window --- p.42Chapter 5.2.3. --- Tools Palette --- p.43Chapter 5.2.4. --- Toolbar --- p.43Chapter 5.2.5. --- Zooming the character window --- p.44Chapter 5.3. --- Editing a character --- p.44Chapter 5.3.1. --- Selecting handles --- p.44Chapter 5.3.2. --- Adding lines and curves --- p.45Chapter 5.3.3. --- Delete control points --- p.45Chapter 5.3.4. --- Moving control points --- p.45Chapter 5.3.5. --- Cut and paste --- p.46Chapter 5.3.6. --- Undo --- p.46Chapter 5.4. --- Adding radicals to a character --- p.46Chapter 5.5. --- Rasterizing and grid-fitting a character --- p.47Chapter 5.5.1. --- Rasterizing a character --- p.48Chapter 5.5.2. --- Stroke detection and regularization --- p.48Chapter 5.5.3. --- Grid-fitting and rasterizing a character --- p.49Chapter 6. --- Conclusions --- p.50Appendix A: Sample Fonts --- p.52References --- p.5

A new approach to the generation of Gray scale Chinese fonts.

by Poon Chi-cheung.Thesis (M.Phil.)--Chinese University of Hong Kong, 1993.Includes bibliographical references (leaves 82-84).AbstractAcknowledgmentsPrefaceChapter Chapter 1: --- Font Systems --- p.1Representations of Character Images --- p.1Characteristics of Chinese Font System --- p.3Large Character Set --- p.3Condensed Strokes --- p.4Low Repetition Rate --- p.5WYSIWYG (What You See Is What You Get) --- p.6Chapter Chapter 2: --- Human Visual System and Gray Scale Font --- p.9Human Visual System --- p.9Physiology --- p.9Spatial Frequencies --- p.10How much resolution is enough --- p.11Screen and Printer --- p.12Raster Display Devices --- p.13Printer --- p.14Resolution --- p.15Gray Scale Font --- p.15Generation of Gray Scale Font --- p.18Chapter Chapter 3: --- Digital Filtering Method for Gray Scale Font --- p.19Filtering Process --- p.19Weighted Functions --- p.21Generation of Gray Scale Character --- p.23Results --- p.24More Experiments --- p.24Problems --- p.26Speed and Storage --- p.26Impression of Strokes --- p.27Thin strokes in the small-size character --- p.30New Approach to Generate Gray Scale Font --- p.30Chapter Chapter 4: --- Rasterization Algorithms --- p.32Outline Font --- p.32TrueType Font --- p.33Scan Conversion --- p.35Basic Outline-to-Bitmap Conversion --- p.35Scan-converting Polygon --- p.36Rasterization of a character --- p.36Intersecting Points and Ranges --- p.37Straight Lines --- p.37Quadratic Bezier Curves --- p.38Implementation Techniques --- p.39Approximation of quadratic Bezier curve by straight lines --- p.39Simplification of the Filling Process --- p.41The Rasterization Algorithm --- p.45Chapter Chapter 5: --- Direct Rasterization with Gray Scale --- p.46Rasterization with Gray Scale --- p.46Determination of Gray Value of Boundary-pixel --- p.50Preliminary Results --- p.54Hinting --- p.56Rasterization with Hinting --- p.56Strokes Migration --- p.57Hints Finding --- p.59Chapter Chapter 6: --- Results and Conclusion --- p.62Quality --- p.66Comparison with Black-and-White Character --- p.66Hinted Against Unhinted --- p.71Generation Speeds --- p.75Discussion and Comments --- p.78Practical Font System --- p.79Conclusion --- p.80Bibliography --- p.8

StrokeStyles: Stroke-based Segmentation and Stylization of Fonts

We develop a method to automatically segment a font’s glyphs into a set of overlapping and intersecting strokes with the aim of generating artistic stylizations. The segmentation method relies on a geometric analysis of the glyph’s outline, its interior, and the surrounding areas and is grounded in perceptually informed principles and measures. Our method does not require training data or templates and applies to glyphs in a large variety of input languages, writing systems, and styles. It uses the medial axis, curvilinear shape features that specify convex and concave outline parts, links that connect concavities, and seven junction types. We show that the resulting decomposition in strokes can be used to create variations, stylizations, and animations in different artistic or design-oriented styles while remaining recognizably similar to the input font

Oriental fonts auto boldness.

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

Knowledge Expansion of a Statistical Machine Translation System using Morphological Resources

Translation capability of a Phrase-Based Statistical Machine Translation (PBSMT) system mostly depends on parallel data and phrases that are not present in the training data are not correctly translated. This paper describes a method that efficiently expands the existing knowledge of a PBSMT system without adding more parallel data but using external morphological resources. A set of new phrase associations is added to translation and reordering models; each of them corresponds to a morphological variation of the source/target/both phrases of an existing association. New associations are generated using a string similarity score based on morphosyntactic information. We tested our approach on En-Fr and Fr-En translations and results showed improvements of the performance in terms of automatic scores (BLEU and Meteor) and reduction of out-of-vocabulary (OOV) words. We believe that our knowledge expansion framework is generic and could be used to add different types of information to the model.JRC.G.2-Global security and crisis managemen

AutoGraff: towards a computational understanding of graffiti writing and related art forms.

The aim of this thesis is to develop a system that generates letters and pictures with a style that is immediately recognizable as graffiti art or calligraphy. The proposed system can be used similarly to, and in tight integration with, conventional computer-aided geometric design tools and can be used to generate synthetic graffiti content for urban environments in games and in movies, and to guide robotic or fabrication systems that can materialise the output of the system with physical drawing media. The thesis is divided into two main parts. The first part describes a set of stroke primitives, building blocks that can be combined to generate different designs that resemble graffiti or calligraphy. These primitives mimic the process typically used to design graffiti letters and exploit well known principles of motor control to model the way in which an artist moves when incrementally tracing stylised letter forms. The second part demonstrates how these stroke primitives can be automatically recovered from input geometry defined in vector form, such as the digitised traces of writing made by a user, or the glyph outlines in a font. This procedure converts the input geometry into a seed that can be transformed into a variety of calligraphic and graffiti stylisations, which depend on parametric variations of the strokes

Phraseology in Corpus-based transaltion studies : stylistic study of two contempoarary Chinese translation of Cervantes's Don Quijote

The present work sets out to investigate the stylistic profiles of two modern Chinese versions of Cervantes???s Don Quijote (I): by Yang Jiang (1978), the first direct translation from Castilian to Chinese, and by Liu Jingsheng (1995), which is one of the most commercially successful versions of the Castilian literary classic. This thesis focuses on a detailed linguistic analysis carried out with the help of the latest textual analytical tools, natural language processing applications and statistical packages. The type of linguistic phenomenon singled out for study is four-character expressions (FCEXs), which are a very typical category of Chinese phraseology. The work opens with the creation of a descriptive framework for the annotation of linguistic data extracted from the parallel corpus of Don Quijote. Subsequently, the classified and extracted data are put through several statistical tests. The results of these tests prove to be very revealing regarding the different use of FCEXs in the two Chinese translations. The computational modelling of the linguistic data would seem to indicate that among other findings, while Liu???s use of archaic idioms has followed the general patterns of the original and also of Yang???s work in the first half of Don Quijote I, noticeable variations begin to emerge in the second half of Liu???s more recent version. Such an idiosyncratic use of archaisms by Liu, which may be defined as style shifting or style variation, is then analyzed in quantitative terms through the application of the proposed context-motivated theory (CMT). The results of applying the CMT-derived statistical models show that the detected stylistic variation may well point to the internal consistency of the translator in rendering the second half of Part I of the novel, which reflects his freer, more creative and experimental style of translation. Through the introduction and testing of quantitative research methods adapted from corpus linguistics and textual statistics, this thesis has made a major contribution to methodological innovation in the study of style within the context of corpus-based translation studies.Imperial Users onl

Phraseology in Corpus-Based Translation Studies: A Stylistic Study of Two Contemporary Chinese Translations of Cervantes's Don Quijote

The present work sets out to investigate the stylistic profiles of two modern Chinese versions of Cervantes’s Don Quijote (I): by Yang Jiang (1978), the first direct translation from Castilian to Chinese, and by Liu Jingsheng (1995), which is one of the most commercially successful versions of the Castilian literary classic. This thesis focuses on a detailed linguistic analysis carried out with the help of the latest textual analytical tools, natural language processing applications and statistical packages. The type of linguistic phenomenon singled out for study is four-character expressions (FCEXs), which are a very typical category of Chinese phraseology. The work opens with the creation of a descriptive framework for the annotation of linguistic data extracted from the parallel corpus of Don Quijote. Subsequently, the classified and extracted data are put through several statistical tests. The results of these tests prove to be very revealing regarding the different use of FCEXs in the two Chinese translations. The computational modelling of the linguistic data would seem to indicate that among other findings, while Liu’s use of archaic idioms has followed the general patterns of the original and also of Yang’s work in the first half of Don Quijote I, noticeable variations begin to emerge in the second half of Liu’s more recent version. Such an idiosyncratic use of archaisms by Liu, which may be defined as style shifting or style variation, is then analyzed in quantitative terms through the application of the proposed context-motivated theory (CMT). The results of applying the CMT-derived statistical models show that the detected stylistic variation may well point to the internal consistency of the translator in rendering the second half of Part I of the novel, which reflects his freer, more creative and experimental style of translation. Through the introduction and testing of quantitative research methods adapted from corpus linguistics and textual statistics, this thesis has made a major contribution to methodological innovation in the study of style within the context of corpus-based translation studies