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Typesetting Classical Greek Philology Could Not find Anything Really Suitable for Her
276 TUGboat, Volume 23 (2002), No. 3/4 professor of classical Greek in a nearby classical high Philology school, was complaining that she could not typeset her class tests in Greek, as she could do in Latin. I stated that with LATEX she should not have any The teubner LATEX package: difficulty, but when I started searching on CTAN,I Typesetting classical Greek philology could not find anything really suitable for her. At Claudio Beccari that time I found only the excellent Greek fonts de- signed by Silvio Levy [1] in 1987 but for a variety of Abstract reasons I did not find them satisfactory for the New The teubner package provides support for typeset- Font Selection Scheme that had been introduced in LAT X in 1994. ting classical Greek philological texts with LATEX, E including textual and rhythmic verse. The special Thus, starting from Levy’s fonts, I designed signs and glyphs made available by this package may many other different families, series, and shapes, also be useful for typesetting philological texts with and added new glyphs. This eventually resulted in other alphabets. my CB Greek fonts that now have been available on CTAN for some years. Many Greek users and schol- 1 Introduction ars began to use them, giving me valuable feedback In this paper a relatively large package is described regarding corrections some shapes, and, even more that allows the setting into type of philological texts, important, making them more useful for the com- particularly those written about Greek literature or munity of people who typeset in Greek — both in poetry. -
Advanced OCR with Omnipage and Finereader
AAddvvHighaa Technn Centerccee Trainingdd UnitOO CCRR 21050 McClellan Rd. Cupertino, CA 95014 www.htctu.net Foothill – De Anza Community College District California Community Colleges Advanced OCR with OmniPage and FineReader 10:00 A.M. Introductions and Expectations FineReader in Kurzweil Basic differences: cost Abbyy $300, OmniPage Pro $150/Pro Office $600; automating; crashing; graphic vs. text 10:30 A.M. OCR program: Abbyy FineReader www.abbyy.com Looking at options Working with TIFF files Opening the file Zoom window Running OCR layout preview modifying spell check looks for barcodes Blocks Block types Adding to blocks Subtracting from blocks Reordering blocks Customize toolbars Adding reordering shortcut to the tool bar Save and load blocks Eraser Saving Types of documents Save to file Formats settings Optional hyphen in Word remove optional hyphen (Tools > Format Settings) Tables manipulating Languages Training 11:45 A.M. Lunch 1:00 P.M. OCR program: ScanSoft OmniPage www.scansoft.com Looking at options Languages Working with TIFF files SET Tools (see handout) www.htctu.net rev. 9/27/2011 Opening the file View toolbar with shortcut keys (View > Toolbar) Running OCR On-the-fly zoning modifying spell check Zone type Resizing zones Reordering zones Enlargement tool Ungroup Templates Saving Save individual pages Save all files in one document One image, one document Training Format types Use true page for PDF, not Word Use flowing page or retain fronts and paragraphs for Word Optional hyphen in Word Tables manipulating Scheduler/Batch manager: Workflow Speech Saving speech files (WAV) Creating a Workflow 2:30 P.M. Break 2:45 P.M. -
OCR Pwds and Assistive Qatari Using OCR Issue No
Arabic Optical State of the Smart Character Art in Arabic Apps for Recognition OCR PWDs and Assistive Qatari using OCR Issue no. 15 Technology Research Nafath Efforts Page 04 Page 07 Page 27 Machine Learning, Deep Learning and OCR Revitalizing Technology Arabic Optical Character Recognition (OCR) Technology at Qatar National Library Overview of Arabic OCR and Related Applications www.mada.org.qa Nafath About AboutIssue 15 Content Mada Nafath3 Page Nafath aims to be a key information 04 Arabic Optical Character resource for disseminating the facts about Recognition and Assistive Mada Center is a private institution for public benefit, which latest trends and innovation in the field of Technology was founded in 2010 as an initiative that aims at promoting ICT Accessibility. It is published in English digital inclusion and building a technology-based community and Arabic languages on a quarterly basis 07 State of the Art in Arabic OCR that meets the needs of persons with functional limitations and intends to be a window of information Qatari Research Efforts (PFLs) – persons with disabilities (PWDs) and the elderly in to the world, highlighting the pioneering Qatar. Mada today is the world’s Center of Excellence in digital work done in our field to meet the growing access in Arabic. Overview of Arabic demands of ICT Accessibility and Assistive 11 OCR and Related Through strategic partnerships, the center works to Technology products and services in Qatar Applications enable the education, culture and community sectors and the Arab region. through ICT to achieve an inclusive community and educational system. The Center achieves its goals 14 Examples of Optical by building partners’ capabilities and supporting the Character Recognition Tools development and accreditation of digital platforms in accordance with international standards of digital access. -
Reconocimiento De Escritura Lecture 4/5 --- Layout Analysis
Reconocimiento de Escritura Lecture 4/5 | Layout Analysis Daniel Keysers Jan/Feb-2008 Keysers: RES-08 1 Jan/Feb-2008 Outline Detection of Geometric Primitives The Hough-Transform RAST Document Layout Analysis Introduction Algorithms for Layout Analysis A `New' Algorithm: Whitespace Cuts Evaluation of Layout Analyis Statistical Layout Analysis OCR OCR - Introduction OCR fonts Tesseract Sources of OCR Errors Keysers: RES-08 2 Jan/Feb-2008 Outline Detection of Geometric Primitives The Hough-Transform RAST Document Layout Analysis Introduction Algorithms for Layout Analysis A `New' Algorithm: Whitespace Cuts Evaluation of Layout Analyis Statistical Layout Analysis OCR OCR - Introduction OCR fonts Tesseract Sources of OCR Errors Keysers: RES-08 3 Jan/Feb-2008 Detection of Geometric Primitives some geometric entities important for DIA: I text lines I whitespace rectangles (background in documents) Keysers: RES-08 4 Jan/Feb-2008 Outline Detection of Geometric Primitives The Hough-Transform RAST Document Layout Analysis Introduction Algorithms for Layout Analysis A `New' Algorithm: Whitespace Cuts Evaluation of Layout Analyis Statistical Layout Analysis OCR OCR - Introduction OCR fonts Tesseract Sources of OCR Errors Keysers: RES-08 5 Jan/Feb-2008 Hough-Transform for Line Detection Assume we are given a set of points (xn; yn) in the image plane. For all points on a line we must have yn = a0 + a1xn If we want to determine the line, each point implies a constraint yn 1 a1 = − a0 xn xn Keysers: RES-08 6 Jan/Feb-2008 Hough-Transform for Line Detection The space spanned by the model parameters a0 and a1 is called model space, parameter space, or Hough space. -
ABBYY Finereader Engine OCR
ABBYY FineReader Engine Performance Guide Integrating optical character recognition (OCR) technology will effectively extend the functionality of your application. Excellent performance of the OCR component is one of the key factors for high customer satisfaction. This document provides information on general OCR performance factors and the possibilities to optimize them in the Software Development Kit ABBYY FineReader Engine. By utilizing its advanced capabilities and options, the high OCR performance can be improved even further for optimal customer experience. When measuring OCR performance, there are two major parameters to consider: RECOGNITION ACCURACY PROCESSING SPEED Which Factors Influence the OCR Accuracy and Processing Speed? Image type and Image image source quality OCR accuracy and Processing System settings processing resources speed Document Application languages architecture Recognition speed and recognition accuracy can be significantly improved by using the right parameters in ABBYY FineReader Engine. Image Type and Image Quality Images can come from different sources. Digitally created PDFs, screenshots of computer and tablet devices, image Key factor files created by scanners, fax servers, digital cameras Image for OCR or smartphones – various image sources will lead to quality = different image types with different level of image quality. performance For example, using the wrong scanner settings can cause “noise” on the image, like random black dots or speckles, blurred and uneven letters, or skewed lines and shifted On the other hand, processing ‘high-quality images’ with- table borders. In terms of OCR, this is a ‘low-quality out distortions reduces the processing time. Additionally, image’. reading high-quality images leads to higher accuracy results. Processing low-quality images requires high computing power, increases the overall processing time and deterio- Therefore, it is recommended to use high-quality images rates the recognition results. -
The File Cmfonts.Fdd for Use with Latex2ε
The file cmfonts.fdd for use with LATEX 2".∗ Frank Mittelbach Rainer Sch¨opf 2019/12/16 This file is maintained byA theLTEX Project team. Bug reports can be opened (category latex) at https://latex-project.org/bugs.html. 1 Introduction This file contains the external font information needed to load the Computer Modern fonts designed by Don Knuth and distributed with TEX. From this file all .fd files (font definition files) for the Computer Modern fonts, both with old encoding (OT1) and Cork encoding (T1) are generated. The Cork encoded fonts are known under the name ec fonts. 2 Customization If you plan to install the AMS font package or if you have it already installed, please note that within this package there are additional sizes of the Computer Modern symbol and math italic fonts. With the release of LATEX 2", these AMS `extracm' fonts have been included in the LATEX font set. Therefore, the math .fd files produced here assume the presence of these AMS extensions. For text fonts in T1 encoding, the directive new selects the new (version 1.2) DC fonts. For the text fonts in OT1 and U encoding, the optional docstrip directive ori selects a conservatively generated set of font definition files, which means that only the basic font sizes coming with an old LATEX 2.09 installation are included into the \DeclareFontShape commands. However, on many installations, people have added missing sizes by scaling up or down available Metafont sources. For example, the Computer Modern Roman italic font cmti is only available in the sizes 7, 8, 9, and 10pt. -
Surviving the TEX Font Encoding Mess Understanding The
Surviving the TEX font encoding mess Understanding the world of TEX fonts and mastering the basics of fontinst Ulrik Vieth Taco Hoekwater · EuroT X ’99 Heidelberg E · FAMOUS QUOTE: English is useful because it is a mess. Since English is a mess, it maps well onto the problem space, which is also a mess, which we call reality. Similary, Perl was designed to be a mess, though in the nicests of all possible ways. | LARRY WALL COROLLARY: TEX fonts are mess, as they are a product of reality. Similary, fontinst is a mess, not necessarily by design, but because it has to cope with the mess we call reality. Contents I Overview of TEX font technology II Installation TEX fonts with fontinst III Overview of math fonts EuroT X ’99 Heidelberg 24. September 1999 3 E · · I Overview of TEX font technology What is a font? What is a virtual font? • Font file formats and conversion utilities • Font attributes and classifications • Font selection schemes • Font naming schemes • Font encodings • What’s in a standard font? What’s in an expert font? • Font installation considerations • Why the need for reencoding? • Which raw font encoding to use? • What’s needed to set up fonts for use with T X? • E EuroT X ’99 Heidelberg 24. September 1999 4 E · · What is a font? in technical terms: • – fonts have many different representations depending on the point of view – TEX typesetter: fonts metrics (TFM) and nothing else – DVI driver: virtual fonts (VF), bitmaps fonts(PK), outline fonts (PFA/PFB or TTF) – PostScript: Type 1 (outlines), Type 3 (anything), Type 42 fonts (embedded TTF) in general terms: • – fonts are collections of glyphs (characters, symbols) of a particular design – fonts are organized into families, series and individual shapes – glyphs may be accessed either by character code or by symbolic names – encoding of glyphs may be fixed or controllable by encoding vectors font information consists of: • – metric information (glyph metrics and global parameters) – some representation of glyph shapes (bitmaps or outlines) EuroT X ’99 Heidelberg 24. -
An Accuracy Examination of OCR Tools
International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8, Issue-9S4, July 2019 An Accuracy Examination of OCR Tools Jayesh Majumdar, Richa Gupta texts, pen computing, developing technologies for assisting Abstract—In this research paper, the authors have aimed to do a the visually impaired, making electronic images searchable comparative study of optical character recognition using of hard copies, defeating or evaluating the robustness of different open source OCR tools. Optical character recognition CAPTCHA. (OCR) method has been used in extracting the text from images. OCR has various applications which include extracting text from any document or image or involves just for reading and processing the text available in digital form. The accuracy of OCR can be dependent on text segmentation and pre-processing algorithms. Sometimes it is difficult to retrieve text from the image because of different size, style, orientation, a complex background of image etc. From vehicle number plate the authors tried to extract vehicle number by using various OCR tools like Tesseract, GOCR, Ocrad and Tensor flow. The authors in this research paper have tried to diagnose the best possible method for optical character recognition and have provided with a comparative analysis of their accuracy. Keywords— OCR tools; Orcad; GOCR; Tensorflow; Tesseract; I. INTRODUCTION Optical character recognition is a method with which text in images of handwritten documents, scripts, passport documents, invoices, vehicle number plate, bank statements, Fig.1: Functioning of OCR [2] computerized receipts, business cards, mail, printouts of static-data, any appropriate documentation or any II. OCR PROCDURE AND PROCESSING computerized receipts, business cards, mail, printouts of To improve the probability of successful processing of an static-data, any appropriate documentation or any picture image, the input image is often ‘pre-processed’; it may be with text in it gets processed and the text in the picture is de-skewed or despeckled. -
Ocr: a Statistical Model of Multi-Engine Ocr Systems
University of Central Florida STARS Electronic Theses and Dissertations, 2004-2019 2004 Ocr: A Statistical Model Of Multi-engine Ocr Systems Mercedes Terre McDonald University of Central Florida Part of the Electrical and Computer Engineering Commons Find similar works at: https://stars.library.ucf.edu/etd University of Central Florida Libraries http://library.ucf.edu This Masters Thesis (Open Access) is brought to you for free and open access by STARS. It has been accepted for inclusion in Electronic Theses and Dissertations, 2004-2019 by an authorized administrator of STARS. For more information, please contact [email protected]. STARS Citation McDonald, Mercedes Terre, "Ocr: A Statistical Model Of Multi-engine Ocr Systems" (2004). Electronic Theses and Dissertations, 2004-2019. 38. https://stars.library.ucf.edu/etd/38 OCR: A STATISTICAL MODEL OF MULTI-ENGINE OCR SYSTEMS by MERCEDES TERRE ROGERS B.S. University of Central Florida, 2000 A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in the Department of Electrical and Computer Engineering in the College of Engineering and Computer Science at the University of Central Florida Orlando, Florida Summer Term 2004 ABSTRACT This thesis is a benchmark performed on three commercial Optical Character Recognition (OCR) engines. The purpose of this benchmark is to characterize the performance of the OCR engines with emphasis on the correlation of errors between each engine. The benchmarks are performed for the evaluation of the effect of a multi-OCR system employing a voting scheme to increase overall recognition accuracy. This is desirable since currently OCR systems are still unable to recognize characters with 100% accuracy. -
P Font-Change Q UV 3
p font•change q UV Version 2015.2 Macros to Change Text & Math fonts in TEX 45 Beautiful Variants 3 Amit Raj Dhawan [email protected] September 2, 2015 This work had been released under Creative Commons Attribution-Share Alike 3.0 Unported License on July 19, 2010. You are free to Share (to copy, distribute and transmit the work) and to Remix (to adapt the work) provided you follow the Attribution and Share Alike guidelines of the licence. For the full licence text, please visit: http://creativecommons.org/licenses/by-sa/3.0/legalcode. 4 When I reach the destination, more than I realize that I have realized the goal, I am occupied with the reminiscences of the journey. It strikes to me again and again, ‘‘Isn’t the journey to the goal the real attainment of the goal?’’ In this way even if I miss goal, I still have attained goal. Contents Introduction .................................................................................. 1 Usage .................................................................................. 1 Example ............................................................................... 3 AMS Symbols .......................................................................... 3 Available Weights ...................................................................... 5 Warning ............................................................................... 5 Charter ....................................................................................... 6 Utopia ....................................................................................... -
Gradu04243.Pdf
Paperilomakkeesta tietomalliin Kalle Malin Tampereen yliopisto Tietojenkäsittelytieteiden laitos Tietojenkäsittelyoppi Pro gradu -tutkielma Ohjaaja: Erkki Mäkinen Toukokuu 2010 i Tampereen yliopisto Tietojenkäsittelytieteiden laitos Tietojenkäsittelyoppi Kalle Malin: Paperilomakkeesta tietomalliin Pro gradu -tutkielma, 61 sivua, 3 liitesivua Toukokuu 2010 Tässä tutkimuksessa käsitellään paperilomakkeiden digitalisointiin liittyvää kokonaisprosessia yleisellä tasolla. Prosessiin tutustutaan tarkastelemalla eri osa-alueiden toimintoja ja laitteita kokonaisjärjestelmän vaatimusten näkökul- masta. Tarkastelu aloitetaan paperilomakkeiden skannaamisesta ja lopetetaan kerättyjen tietojen tallentamiseen tietomalliin. Lisäksi luodaan silmäys markki- noilla oleviin valmisratkaisuihin, jotka sisältävät prosessin kannalta oleelliset toiminnot. Avainsanat ja -sanonnat: lomake, skannaus, lomakerakenne, lomakemalli, OCR, OFR, tietomalli. ii Lyhenteet ADRT = Adaptive Document Recoginition Technology API = Application Programming Interface BAG = Block Adjacency Graph DIR = Document Image Recognition dpi= Dots Per Inch ICR = Intelligent Character Recognition IFPS = Intelligent Forms Processing System IR = Information Retrieval IRM = Image and Records Management IWR = Intelligent Word Recognition NAS = Network Attached Storage OCR = Optical Character Recognition OFR = Optical Form Recognition OHR = Optical Handwriting Recognition OMR = Optical Mark Recognition PDF = Portable Document Format SAN = Storage Area Networks SDK = Software Development Kit SLM -
Formal Aspects of Computing: Latex2ε Guide for Authors
Under consideration for publication in Formal Aspects of Computing Formal Aspects of Computing: LATEX 2ε Guide for Authors Mark Reed1 and Christiane Notarmarco2 1Electronic Products and Composition Group, Cambridge University Press, Cambridge, 2Springer-Verlag London Limited, Godalming, Surrey, UK Abstract. This guide is for authors who are preparing papers for the Formal Aspects of Computing journal using the LATEX 2ε document-preparation system and the Formal Aspects of Computing class file (fac.cls). Keywords: LATEX 2ε; Class file; fac.cls; User guide 1. Introduction In addition to the standard submission of hardcopy from authors, Formal Aspects of Computing now accepts machine-readable forms of papers in LATEX 2ε. The layout design for the Formal Aspects of Computing journal has been implemented as a LATEX 2ε class file, based on the article class as discussed in the LATEX manual (2nd edition) [Lam94]. Commands which differ from the standard LATEX interface, or which are provided in addition to the standard interface, are explained in this guide (which is not a substitute for the LATEX manual itself). Note that the final printed version of papers will use the Monotype Times typeface rather than the Computer Modern available to authors. For this reason line and page breaks will change and authors should not insert hard breaks in their text. Authors planning to submit their papers in LATEX 2ε are advised to use fac.cls as early as possible in the creation of their files. 1.1. Introduction to LATEX LATEX is constructed as a series of macros on top of the TEX typesetting program.