Structured Document Image Analysis PDF
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Structured Document Image Analysis H. S. Baird H. Bunke K. Yamamoto (Eds.) Structured Document Image Analysis With 230 Figures and 34 Tables Springer-Verlag Berlin Heidelberg New York London Paris Tokyo Hong Kong Barcelona Budapest Editors Henry S. Baird AT&T Bell Laboratories Computing Science Research Center 600 Mountain Avenue, Room 2C-322 P. O. Box 636 Murray Hill, NJ 07974-0636, USA Horst Bunke Institut flir Informatik und angewandte Mathematik UniversiUit Bern Liinggass-Str. 51, CH-30l2 Bern Kazuhiko Yamamoto Machine Understanding Division Electrotechnical Laboratory 1-1-4, Umezono, Tsukuba Science City Ibaraki 305, Japan ISBN -13: 978-3-642-77283-2 e-ISBN -13: 978-3-642-77281-8 DOl: 10.1007/978-3-642-77281-8 Library of Congress Cataloging-in-Publication Data. Structured document image analysis / H.S. Baird, H. Bunke, K. Yamamoto, eds. p. cm. Includes bibliographical references and index. ISBN-13:978-3-642-77283-2 (alk. paper: U.S.) I. Image processing. 2. Computer vision. I. Baird, Henry S. II. Bunke, Horst. III. Yamamoto,K.(Kazuhiko) TA1632.S852 1992 621.36'7-dc20 92-27386 CIP This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag. Violations are liable for prosecution under the German Copyright Law. © Springer-Verlag Berlin Heidelberg 1992 Softcover reprint of the hardcover 1st edition 1992 The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover Design: H. Lopka, Ilvesheim Typesetting: Camera ready by the editors 45/3140 -5 4 3 2 1 0 -Printed on acid-free paper To H. Clark Maziuk Preface Document image analysis is concerned with the automatic interpretation of im ages of printed and handwritten documents, including text, engineering draw ings, maps, music scores, etc. Research in this field descends in an unbroken tradi tion from the earliest experiments in computer vision, and remains distinguished by close and productive ties between the academic and industrial communities. While the difficulty of its characteristic problems continues to stimulate basic research, general agreement on quantifiable performance standards has encour aged the evolution of sound engineering methods. As a result, research in this area supports a rapidly growing industry. We are pleased to offer a collection of state-of-the-art papers touching on virtually every topic of current research interest: printed documents; character and symbol recognition; handwriting; graphics, maps, and technical drawings; music notation; and methodology. Among these are several authoritative critical surveys of the literature. We have singled out music notation for special emphasis since it offers an ideal vehicle for sharing basic research internationally: identical scores are available, and are unambiguously understood, in every country. Document images offer computer vision researchers unique opportunities. The early stages of processing such as feature extraction are relatively tractable, allowing rapid access to extraordinarily challenging later stages requiring the construction of full interpretations of complex scenes. As a result, a major focus of research is the architecture of complete, integrated vision systems, often ex hibiting extremely high competency. We have included several parallel studies of this kind. All but four of these papers were first presented at the International Asso ciation for Pattern Recognition workshop on Syntactic and Structural Pattern Recognition (SSPR'90), held at Murray Hill, New Jersey USA, June 13-15, 1990. At that time, they were reviewed by three referees, and in many cases revised; since then, most have been expanded or extensively reworked for publication here. For improved balance, we have also invited four new contributions. In the closing section of the book, we report briefly on the SSPR'90 workshop and several of its working groups. These groups, consisting of experts interested in a common topic, drew up lists of open problems and proven methods; their debates provide a fascinating perspective on the field. Murray Hill, New Jersey, USA Henry S. Baird Bern, Switzerland Horst Bunke Tsukuba, Japan Kazuhiko Yamamoto July 1991 Table of Contents Printed Documents Towards the Understanding of Printed Documents .......................... 3 T. Bayer, J. Franke, U. Kressel, E. Mandler, M. Oberlander, J. Schurmann An Experimental Implementation of a Document Recognition System for Papers Containing Mathematical Expressions .......................... 36 M. Okamoto, A. Miyazawa Towards a Structured Document Image Utility ............................. 54 G. Nagy ANASTASIL: A System for Low-Level and High-Level Geometric Analysis of Printed Documents ............................................ 70 A. Dengel A Top-Down Approach to the Analysis of Document Images ............... 99 H. Fujisawa, Y. Nakano Analysis of Scanned Documents - a Syntactic Approach ................. 115 M. Viswanathan Character and Symbol Recognition Structural Analysis and Description of Curves by Quasi-Topological Features and Singular Points .......................... 139 H. Nishida, S. Mori Combination of Decisions by Multiple Classifiers .......................... 188 T. K. Ho, J. J. Hull, S. N. Srihari Resolving Ambiguity in Segmenting Touching Characters ................. 203 S. Tsujimoto, H. Asada x Table of Contents Handwriting Off-line Identification with Handwritten Signature Images: Survey and Perspectives .................................................. 219 R. Sabourin, R. Plamondon, G. Lorette Difficult Cases in Handwritten Numeral Recognition ...................... 235 R. Legault, C. Y. Suen, C. Nadal Recognition of Hand-Printed Chinese Characters and the Japanese Cursive Syllabary ...................................... 250 K. Yamamoto, H. Yamada Regularities and Singularities in Line Pictures ............................ 261 J.-C. Simon, O. Baret Graphics, Maps, and Technical Drawings An Overview of Techniques for Graphics Recognition ..................... 285 R. Kasturi, R. Raman, C. Chennubhotla, L. O'Gorman High Quality Vectorization Based on a Generic Object Model ............. 325 O. Hori, A. Okazaki Recognizing Hand-Drawn Electrical Circuit Symbols with Attributed Graph Matching ......................................... 340 S.-w. Lee Self-Structural Syntax-Directed Pattern Recognition of Dimensioning Components in Engineering Drawings .................... 359 D. Dori Analysis of Technical Documents: The REDRAW System ................. 385 D. Antoine, S. Collin, K. Tombre Music Notation A Critical Survey of Music Image Analysis ............................... 405 D. Blostein, H. S. Baird A Recognition System for Printed Piano Music using Musical Knowledge and Constraints ................................ 435 H. Kato, S. Inokuchi Automatic Recognition of Printed Music ................................. 456 N. P. Carter, R. A. Bacon Automatic Recognition of Several Types of Musical Notation ............. 466 T. Itagaki, M. Isogai, S. Hashimoto, S. Ohteru Table of Contents XI Methodology Syntactic and Structural Methods in Document Image Analysis ........... 479 A. Sanfeliu Syntactic Analysis of Context-Free Plex Languages for Pattern Recognition .................................................. 500 H. Bunke, B. Haller Document Image Analysis Using Logic-Grammar-Based Syntactic Pattern Recognition ............................................ 520 D. B. Searls, S. L. Taylor Document Image Defect Models .......................................... 546 H. S. Baird IAPR 1990 Workshop on SSPR SSPR'90 Workshop Report ............................................... 559 H. S. Baird, L. 0 'Gorman Document Analysis: SSPR'90 Working Group Report .................... 562 J. Kanai, A. Dengel Character Recognition: SSPR'90 Working Group Report ................. 565 T. Bayer, J. Hull, G. Nagy Line Drawings, Feature Extraction, and Symbol Recognition: SSPR'90 Working Group Report ......................................... 568 P. S. P. Wang, D. Dori Technical Drawing Analysis: SSPR'90 Working Group Report ............ 570 E. Saund, S. H. Joseph Recognition of Music Notation: SSPR'90 Working Group Report ......... 573 D. Blostein, N. P. Carter Syntactic Methods: SSPR'90 Working Group Report ..................... 575 R. Siromoney, A. Sanfeliu SSPR'90 Participants List ................................................ 577 Printed Documents Towards the Understanding of Printed Documents Thomas Bayer, Jiirgen Franke, Ulrich Kressel, Eberhard Mandler, Matthias Oberlander, and Jiirgen Schiirmann Daimler-Benz AG, Research Center VIm, Wilhelm-Runge-Str. 11, D-7900 Ulm, Germany 1 Introduction Document analysis aims at the transformation of data presented on paper and addressed to human comprehension into a computer-revisable form. The pixel representation of a scanned document must be converted into a structured set of symbolic entities, which are appropriate for the intended kind of computerized information processing. It can be argued that the achieved symbolic description level resembles the degree of understanding acquired by a document analysis system. This interpretation of the term 'understanding' shall be explained a little more deeply. An attempt shall be made to clarify the important question: "Up to what level can a machine really understand a given document?" Looking at the many problems still unsolved, this is indeed questionable. Is it acceptable to use the term understanding, if the internal data structure merely describes geometric properties? Or is it necessary, at least, to be on the level of word meanings, or even more, to have knowledge about the topics being addressed in a given letter? In answering these questions, it is helpful to consider a particular document model, for example, the Office Document Architecture (ODA, see [Horak 85]). ODA provides a general concept for describing office documents. It allows for standardized access by all kind of text processing programs, like editors or print formatters. It also specifies an interchange format (called ODIF) not only for final, but also for revisable document formats. Though originally conceived for document generation, it gives some insight into the reverse task: document anal ysis. The central idea of ODA is the distinction between layout structure and logical structure of a document. The layout structure deals with the appearance of a document, whereas the logical structure speaks about its logical constituents (e.g. headline, paragraph, captions, references, etc), completely disregarding any geometric properties. Obviously, the logical objects are much closer to semantics, and hence to understanding. But it would be a precipitate conclusion that layout data has nothing to do with understanding. When trying to understand a document, the layout structure, the logical structure, or both, may be considered. A very simple processing scheme for a
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