Table Of ContentStructured Document
Image Analysis
H. S. Baird H. Bunke K. Yamamoto (Eds.)
Structured Document
Image Analysis
With 230 Figures and 34 Tables
Springer-Verlag
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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
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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
