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Extraction of Typographic Elements from Outline Representations of Fonts

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Extraction of Typographic Elements from Outline Representations of Fonts Extraction of Typ ographic Elements from Outline Representations of Fonts Ariel Shamir and Ari Rapp op ort Institute of Computer Science The Hebrew University of Jerusalem Jerusalem Israel farikarirgcshujiacil Abstract Digital typefaces for computer graphics and multimedia applications must be capable of supporting operations such as font variations transformations deformations and blending A powerful implementation of such op erations must rely on the inherent typographic attributes of the typeface However even todays most advanced typeface representations support only geometric outline representations and basic font variations In this paper we discuss highlevel typeface representations which we term Parametric Typ ographic Represen tations PTRs We present an algorithm for automatical ly extracting typographic elements of typefaces from their outline representation which is an essential initial step in converting typefaces from outline representa tions to PTRs The extracted typographic elements include serifs bars stems slants bows arcs curve stems and curve bars Most notable is the treatment of serifs which are represented by niteautomata The algorithm only needs to learn a serif type once and is then capable of automatical ly recognizing it in dierent typefaces We show an application of a PTR for automatic highquality hinting of fonts which is one of the most important stages in digital font production Our system was used to generate hints for dozens of thousands of Kanji Roman and Hebrew characters Keywords Digital typ ography outline fonts typ ographic elements hinting parametric typ ographic repre sentations Intro duction Printed pages have constituted a ma jor way of communication b etween literate p eople ever since the invention of print by Guten b erg in the th century The existence of electronic media has mo died this situation Typsetting page layout typ efaces and fonts need to change their nature and b ecome more exible A wide range of applications such as multimedia publishin g computer animation and even mechanical or electronic computeraided design systems must incorp orate a diverse set of text manipulation functions from simple ane transformations to advanced deformations The basic technology which supp orts this functionality is encapsulated in the representation used for digital typ ographic typ efaces or digital fonts Hence the degree of sophisticati on of digital typ eface representations is a crucial factor in the expressive p ower and usability of mo dern visual communication In the design and analysis of typ efaces one uses terms such as stems bars serifs style size weight and width Lawson Rubinstein Bringhurst Bauermeister see the gures in this pap er for examples However even the advanced typ eface representations in use to day eg QuickDrawGX Apple TrueTyp e and TrueTyp e Op en Microsoft Typ e Adob e Adob e concentrate only on representing the geometry of a font and on the provision of relatively simple font variations There is a large gap b etween the highlevel terms used by designers and b etween current representations A representation which supp orts highlevel parameterization based on typ ographic terminology is needed The general term which we use for such a representation is a Parametric Typographic Representation PTR Extraction of typ ographic elements from existing font representations is essential in order to convert to days outline representations into any parametric typ ographic representation Previous Work Some previous work of identifying typ ographic elements has b een done for the sake of automating the pro cess of hinting an outline font hints are needed in order to rasterize scaled fonts correctly whether on a screen or in print Basic hints can b e added to the outline description automatically by recognizing horizontal and vertical bars and curvilinear shap e extrema Andler or even some serif parts Karow Hersch and Betrisey have presented an elab orate automatic hinting metho d Herscha which requires a top ological fontindep endent mo del for the description of each Roman letter shap e These mo dels include sp ecic hints connected to various typ ographic elements In order to add hints to a concrete letter shap e a matching algorithm b etween the real shap e and the mo dels is p erformed After a match has b een found the hints contained in the matched mo del are adapted to the real letter shap e by identifying similar p oints in b oth the mo del and the actual letter shap e This scheme involves the denition of a mo del for each top ology of a letter shap e a pro cess which is b oth dicult and time and space consuming for example in ideographic Chinese Japanese and Korean scripts Several other techniques for automatic hinting of outlined characters exist inside the font development systems of commercial companies such as Bitstream Adob e and Apple These systems are considered a commercial secret but by examining their output eg TrueTyp e or Typ e fonts one can see that a large amount of typ ographic information is still not identied by the automatic hinting pro cess and therefore a lot of manual pro ong and hinting is taking place in order to achieve the desired quality Some research has b een done on the extraction of strokes from the outline description for applications such as display of Kanji characters Chialing conversion to a dierent representation Dursta Durstb and optical character recognition Feng The general spirit of these pap ers is opp osite to ours since they are interested in removing the subtle typ ographic details of typ efaces in order to create a skeleton representation of characters which is simpler and easier to recognize A font represented in metafont Knuth is in principle parametric since metafont is a pro cedural programming language However all the parameterization is done manually by the programmer Conversion of PostScript fonts to metafont has b een describ ed in Haralamb ous but the metho d is sp ecic to these two representations and it do es not treat automatic extraction of typ ographic elements Contribution In this pap er we present an algorithm to extract typ ographic elements of typ efaces from an outline repre sentation of a font and show how to use its results for automatic hinting The conversion algorithm extracts basic typ ographic elements from the outline description of a character Figure and can gather information regarding the relationshi ps b etween them b oth inside each character and across the font This information can then b e used to assign parametric attributes to the typ ographic elements With this capability the algo rithm can b e viewed as an essential initial step in converting a typ eface from an outline representation into a parametric typ ographic representation Our conversion metho d involves two main stages The rst stage is the designation and classication of characteristic p oints along the glyph outline which is similar in spirit to some previous work Herscha but is given here in a more detailed manner The second stage uses data from the rst stage for the actual extraction of the typ ographic features from the outline Among the basic features recognized are stems and bars b ows and arcs curve stems and curve bars slants extrema and most notably serifs of all typ es These typ ographic features are in turn gathered to create higher degree elements such as groups of bars inside a glyph or a Kanji strokelike element Zhang Sp ecial treatment has b een given to the extraction of serifs Serifs play a crucially imp ortant role in the design of a typ eface and there is an enormous diversity of serif designs We create a niteautomaton Lewis that denes the sequence or sequences of p oints which characterize each typ e of serif Once this automaton has b een dened serifs of this typ e can b e extracted and recognized in any outlined font input to the system If a new typ eface containing new typ es of serifs is intro duced to the system only a few new niteautomata need to b e dened in order to extract the new typ eface features Along with a rastertooutline mo dule our system can convert a typ eface in any lowerlevel description technique to a higher level parametric typ ographic representation We do not require a mo del for each glyph since the information regarding typ ographic elements is stored in a higher representational level that applies to any glyph The algorithm is time and space ecient if n is the numb er of p oints dening the outline of a glyph and k is the numb er of features extracted from it where k n the pro cess for recognizing basic 2 elements for one glyph takes O n log n k time and O n k space Our metho d needs much less manual manipulati on and pro ong than previous work it is multiling ual in nature not using languagedep endent letter mo dels and it pro duces higher level typ ographic details suitable to mo dern visual communication applications The problem dealt with in this pap er is very similar to the problem of feature recognition extensively researched in geometric and solid mo deling Wo o dwark In b oth cases we desire to convert a b oundary representation Brep which is a relatively lowlevel representation to a higherlevel one supp orting terms taken from the applicatio n domain In Section we describ e the state of the art in digital typ ography to day and the hierarchy of digital typ eface representations Section describ es the classication of the p oints describing the outline Section describ es the actual extraction of the typ ographic elements Finally in Section we discuss an imp
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