handbook of computer vision and applications. vol. 3. systems and applications

HANDBOOK OF
COMPUTER VISION AND
APPLICATIONS
Volume 3
Systems and Applications
ACADEMIC
PRESS
Bernd Jähne
Horst Haußecker
Peter Geißler
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1
2
2
2
24
11
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Handbook of
Computer Vision
and Applications
Volume 3
Systems and Applications

Handbook of

Computer Vision
and Applications
Volume 3
Systems and Applications
Editors
Bernd Jähne
Interdisciplinary Center for Scientific Computing
University of Heidelberg, Heidelberg, Germany
and
Scripps Institution of Oceanography
University of California, San Diego
Horst Haußecker
Peter Geißler
Interdisciplinary Center for Scientific Computing
University of Heidelberg, Heidelberg, Germany
ACADEMIC PRESS
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ACADEMIC PRESS
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ACADEMIC PRESS
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/>Library of Congress Cataloging-In-Publication Data
Handbook of computer vision and applications / edited by Bernd Jähne,
Horst Haussecker, Peter Geissler.
p. cm.
Includes bibliographical references and indexes.
Contents: v. 1. Sensors and imaging — v. 2. Signal processing and
pattern recognition—v. 3. Systems and applications.
ISBN 0–12–379770–5 (set). — ISBN 0–12–379771-3 (v. 1)
ISBN 0–12–379772–1 (v. 2). — ISBN 0–12–379773-X (v. 3)
1. Computer vision — Handbooks, manuals. etc. I. Jähne, Bernd
1953– . II. Haussecker, Horst, 1968– . III. Geissler, Peter, 1966– .
TA1634.H36 1999
006.3

7 — dc21 98–42541
CIP
Printed in the United States of America
9900010203DS987654321

Contents
Preface xv
Contributors xvii
1 Introduction 1
B. Jähne
1.1 Computer vision architecture 2
1.2 Classes of tasks 4
I Architecture of Computer Vision Systems
2 Field Programmable Gate Array Image Processing 9
K H. Noffz, R. Lay, R. Männer, and B. Jähne
2.1 Introduction 10
2.2 Field programmable gate arrays (FPGAs) 11
2.3 FPGA-based image processing systems 15
2.4 Programming software for FPGA image processing 21
2.5 Application examples 26
2.6 Conclusions 29
2.7 References 30
3 Multimedia Architectures 31
B. Jähne and H. Herrmann
3.1 Introduction 32
3.2 Signal processing performance of microprocessors 33
3.3 Principles of SIMD signal processing 36
3.4 Comparative analysis of instruction sets 38
3.5 SIMD algorithms for signal processing 45
3.6 Conclusions and outlook 50
3.7 References 52
4 Customizable Medical Image Processing Systems 53
A. M. Demiris, C. E. Cardenas S., and H. P. Meinzer
4.1 Introduction 53
4.2 State of the art 57

4.3 Identifying development phases 58
4.4 Components of the architecture 60
4.5 Implementation of the architecture 70
4.6 Conclusions 74
v
vi Contents
4.7 Future work 74
4.8 References 75
5 Software Engineering for Image Processing and Analysis 77
D. Paulus, J. Hornegger, and H. Niemann
5.1 Introduction 78
5.2 Object-oriented software engineering 79
5.3 Programming languages for image processing 84
5.4 Image understanding 88
5.5 Class hierarchy for data and algorithms 91
5.6 Conclusion 99
5.7 References 100
6 Reusable Software in Computer Vision 103
U. Köthe
6.1 Introduction 104
6.2 Generic programming 107
6.3 Two-dimensional iterators 114
6.4 Image data accessors 118
6.5 Generic algorithms on images 120
6.6 Performance 127
6.7 Image iterator adapters 127
6.8 Conclusions 131
6.9 References 132
7 Application-oriented Assessment of CV Algorithms 133
P. Klausmann, S. Fries, D. Willersinn, U. Stilla, and U. Thönnessen

7.1 Introduction 133
7.2 Analytical versus empirical performance analysis 134
7.3 Application-oriented empirical algorithm assessment 136
7.4 The assessment system 143
7.5 Example: Assessment of a detection algorithm 145
7.6 Conclusion 149
7.7 References 149
8 A Hybrid Neuro-AI-Architecture 153
G. Hartmann, U. Büker, and S. Drüe
8.1 Introduction 153
8.2 Holistic recognition of segmented 2-D objects 156
8.3 Holistic recognition of 3-D objects in real scenes 171
8.4 The hybrid neuro-artificial intelligence (AI) system 182
8.5 Conclusion 194
8.6 References 195
9 Active Vision Systems 197
B. Mertsching and S. Schmalz
9.1 Introduction 197
9.2 Marr’s theory and its drawbacks 198
9.3 Basic concepts of active vision 202
9.4 Examples for active vision environments 209
9.5 Applications for active vision devices 213
Contents vii
9.6 Conclusion 215
9.7 References 215
10 The Global Algebraic Frame of the Perception-Action Cycle 221
G. Sommer
10.1 Introduction 222
10.2 Design of behavior-based systems 223
10.3 Algebraic frames of higher-order entities 230

10.4 Applications of the algebraic framework 249
10.5 Summary and conclusions 259
10.6 References 260
II Industrial and Technical Applications
11 Market and Future Needs of Industrial Imaging 267
K. Singer
11.1 Introduction 267
11.2 Historical roots 268
11.3 Market overview 271
11.4 Economical situation 271
11.5 Mainstream technology used today 276
11.6 Future trends 277
11.7 Conclusions 279
11.8 References 282
12 Applications of Morphological Operators 283
P. Soille
12.1 Introduction 283
12.2 Geosciences 284
12.3 Material sciences 284
12.4 Biological and medical imaging 286
12.5 Industrial applications 287
12.6 Identification and security control 288
12.7 Document processing 289
12.8 Image coding 290
12.9 Other applications 290
12.10 References 291
13 Industrial Object Recognition 297
T. Wagner and P. Plankensteiner
13.1 Problem, market and solutions 297
13.2 Compact solution: intelligent cameras 300

13.3 Object recognition for many object types 305
13.4 Discussion and outlook 311
13.5 References 313
14 Character Recognition in Industrial Production 315
R. Koy-Oberthür, T. Münsterer, and S. Sun
14.1 Introduction 315
14.2 Codings 316
14.3 Code generation and code control 317
viii Contents
14.4 Functional principle and system setup 317
14.5 Examples of applications 321
14.6 References 328
15 Motion Tracking 329
R. Frischholz
15.1 Introduction 329
15.2 Flexible automatic motion tracking 333
15.3 Sample applications 340
15.4 Conclusion and remarks 343
15.5 References 344
16 3-D Image Metrology for Industrial Production 345
H. A. Beyer
16.1 Introduction 345
16.2 Geometry check of wing roots 347
16.3 Three-dimensional image metrology in shipbuilding 349
16.4 Machine control and TI
2
technology 351
16.5 Developments 354
16.6 Conclusions 357
16.7 References 357

17 Reverse Engineering Using Optical Range Sensors 359
S. Karbacher, G. Häusler, and H. Schönfeld
17.1 Introduction 360
17.2 Related work 362
17.3 Three-dimensional sensors 364
17.4 Calibration 364
17.5 Registration 365
17.6 Surface reconstruction 368
17.7 Surface modeling and smoothing 369
17.8 Examples 376
17.9 Conclusions 379
17.10 References 379
18 Topographical Maps of Microstructures 381
T. Scheuermann, G. Wiora and M. Graf
18.1 Introduction 382
18.2 Depth-from-focus approaches 382
18.3 System description 384
18.4 Optical theory 387
18.5 Reconstruction of topography 392
18.6 Systematic errors 397
18.7 Measurement of layer thickness 401
18.8 Applications 406
18.9 Conclusions 407
18.10 References 409
Contents ix
19 Processing of Digital Elevation Maps 411
P. Soille
19.1 Introduction 411
19.2 Geodesic interpolation of contour data 412
19.3 Drainage network detection 418

19.4 Watershed detection 424
19.5 Concluding remarks 425
19.6 References 426
20 3-D Modeling of Objects from Image Sequences 429
R. Koch
20.1 Introduction 429
20.2 System overview 431
20.3 Image acquisition and calibration 432
20.4 Stereoscopic depth estimation 434
20.5 Three-dimensional model building 440
20.6 Uncalibrated monocular sequences 445
20.7 Conclusions 448
20.8 References 448
21 Three-Dimensional Fast Full-Body Scanning 451
N. Stein and B. Minge
21.1 Introduction 451
21.2 Evaluation hardware and software 454
21.3 Mechanical design 455
21.4 Measuring process 456
21.5 Ranges of application 456
21.6 References 466
22 3-D Model-Driven Person Detection 467
B. Radig, O. Munkelt, C. Ridder, D. Hansel, and W. Hafner
22.1 Introduction 467
22.2 The object model 468
22.3 Appearance and its representation 471
22.4 Matching 475
22.5 Implementation 477
22.6 Applications 480
22.7 References 482

23 Single-Perspective 3-D Object Recognition 485
S. Lanser, C. Zierl, and B. Radig
23.1 Introduction 485
23.2 The MORAL object-recognition system 487
23.3 Applications 495
23.4 Conclusion 498
23.5 References 499
x Contents
24 Flexible Models of Human Faces 501
T. Vetter
24.1 Introduction 501
24.2 Automated learning of flexible face models 504
24.3 View synthesis 510
24.4 Conclusions 512
24.5 References 513
25 Knowledge-Based Image Retrieval 515
Th. Hermes, C. Klauck, and O. Herzog
25.1 Introduction 515
25.2 Overview 520
25.3 Object recognition 522
25.4 Examples 525
25.5 Conclusion 527
25.6 References 527
26 A Tactile Vision-Substitution System 531
M. Loose, T. Macher, J. Schemmel, K. Meier, and M. Keller
26.1 Introduction 531
26.2 Concept and realization 532
26.3 Results and prospects 540
26.4 References 541
27 The Neural Active Vision System NAVIS 543

B. Mertsching, M. Bollmann, R. Hoischen, and S. Schmalz
27.1 Introduction 544
27.2 Experimental platforms 545
27.3 Image preprocessing 547
27.4 Depth estimation 549
27.5 Visual attention 551
27.6 Object recognition 554
27.7 Motion estimation and object tracking 561
27.8 Conclusion 566
27.9 References 566
28 Dynamic Vision for Perception and Control of Motion 569
E. D. Dickmanns and H J. Wünsche
28.1 Introduction 570
28.2 Application areas discussed 577
28.3 Sensory information used 578
28.4 Dynamic perception with spatiotemporal models 580
28.5 Multiple loops in dynamic scene understanding 606
28.6 Experimental results 609
28.7 Conclusions and outlook 617
28.8 References 617
Contents xi
III Scientific Applications
29 Size Distributions of Small Particles 623
P. Geißler and T. Scholz
29.1 Introduction 623
29.2 Depth-from-focus based measurements 624
29.3 Size distribution of air bubbles 626
29.4 In situ microscopy 639
29.5 Acknowledgments 645
29.6 References 645

30 Fluorescence Imaging of Air-Water Gas Exchange 647
S. Eichkorn, T. Münsterer, U. Lode, and B. Jähne
30.1 Introduction 647
30.2 Historical review 649
30.3 LIF measurements of concentration fields 650
30.4 Critical discussion and outlook 660
30.5 References 661
31 Particle-Tracking Velocimetry 663
D. Engelmann, M. Stöhr, C. Garbe, and F. Hering
31.1 Introduction 664
31.2 Visualization 665
31.3 Image processing for particle-tracking velocimetry 671
31.4 Stereo particle-tracking velocimetry 684
31.5 Conclusions 694
31.6 References 696
32 Analyzing Particle Movements at Soil Interfaces 699
H. Spies, O. Beringer, H. Gröning, and H. Haußecker
32.1 Introduction 700
32.2 Previous investigations 700
32.3 Experimental setup 701
32.4 Image analysis 704
32.5 Results 713
32.6 Conclusions and future activities 717
32.7 References 718
33 Plant-Leaf Growth 719
D. Schmundt and U. Schurr
33.1 Introduction 719
33.2 Previous investigations 720
33.3 Experimental setup 722
33.4 Image analysis 725

33.5 Stability and validation 730
33.6 Applications 732
33.7 Outlook 733
33.8 References 734
xii Contents
34 Mathematical Modeling of Ca
2+
-Fluorescence Images 737
D. Uttenweiler and R. H. A. Fink
34.1 Introduction 737
34.2 The necessity of modeling fluorescence images 738
34.3 The complex structure of muscle cells 740
34.4 Ca
2+
-measurements 741
34.5 Mathematical modeling 743
34.6 Simulated Ca
2+
-transients 746
34.7 Conclusions 748
34.8 References 749
35 Thermography for Small-Scale Air-Sea Interaction 751
U. Schimpf, H. Haußecker, and B. Jähne
35.1 Introduction 751
35.2 The controlled flux technique 752
35.3 Experimental setup 756
35.4 Calibration 757
35.5 Results and conclusions 759
35.6 References 761
36 Thermography to Measure Water Relations of Plant Leaves 763

B. Kümmerlen, S. Dauwe, D. Schmundt, and U. Schurr
36.1 Botanical background 763
36.2 Previous measurement techniques 765
36.3 Theoretical background 766
36.4 Measurements 772
36.5 Conclusion and further developments 780
36.6 References 781
37 Retrieval of Atmospheric Trace Gas Concentrations 783
C. Leue, M. Wenig, and U. Platt
37.1 Introduction 783
37.2 The global ozone monitoring experiment (GOME) 785
37.3 Retrieval of trace gas concentrations 787
37.4 Image interpolation 792
37.5 Determination of vertical columns 796
37.6 Results 802
37.7 References 805
38 Tracking “Fuzzy” Storms in Doppler Radar Images 807
J. L. Barron, R. E. Mercer, D. Cheng, and P. Joe
38.1 Introduction 807
38.2 Problems of storm tracking 808
38.3 Background: Zhang/Krezeski’s algorithms 809
38.4 Fuzzy storm centers 812
38.5 Incremental relaxation-labeling algorithm 814
38.6 An X-Window-based storm-visualization program 817
38.7 Experimental results 817
38.8 Conclusions 819
38.9 References 820
Contents xiii
39 Detection of Dendritic Spine Synapses 821
R. Watzel, W. Hilberg, H. Scheich, and K. Braun

39.1 Introduction 821
39.2 Data acquisition by confocal microscopy 823
39.3 Image restoration 824
39.4 Differential feature detection for segmentation 826
39.5 Topology preserving three-dimensional thinning 829
39.6 Graph construction and interpretation 831
39.7 Results 833
39.8 Discussion 834
39.9 References 837
40 Spectral Precision Distance Confocal Microscopy 839
C. Cremer, P. Edelmann, H. Bornfleth, G. Kreth, H. Muench, and
M. Hausmann
40.1 The problem 839
40.2 Principles of spectral precision distance microscopy 845
40.3 Determination of the resolution equivalent in situ 852
40.4 Conclusions 855
40.5 References 855
41 Three-dimensional Analysis of Genome Topology 859
H. Bornfleth, P. Edelmann, D. Zink, and C. Cremer
41.1 Introduction 859
41.2 Analysis of large- and small-scale chromatin structure 863
41.3 Discussion and outlook 874
41.4 References 877
Index 879
xiv Contents
Preface
What this handbook is about
This handbook offers a fresh approach to computer vision. The whole
vision process from image formation to measuring, recognition, or re-
acting is regarded as an integral process. Computer vision is under-

stood as the host of techniques to acquire, process, analyze, and un-
derstand complex higher-dimensional data from our environment for
scientific and technical exploration.
In this sense the handbook takes into account the interdisciplinary
nature of computer vision with its links to virtually all natural sciences
and attempts to bridge two important gaps. The first is between mod-
ern physical sciences and the many novel techniques to acquire images.
The second is between basic research and applications. When a reader
with a background in one of the fields related to computer vision feels
he has learned something from one of the many other facets of com-
puter vision, the handbook will have fulfilled its purpose.
The handbook comprises three volumes. The first volume, Sensors
and Imaging, covers image formation and acquisition. The second vol-
ume, Signal Processing and Pattern Recognition , focuses on processing
of the spatial and spatiotemporal signal acquired by imaging sensors.
The third volume, Systems and Applications, describes how computer
vision is integrated into systems and applications.
Prerequisites
It is assumed that the reader is familiar with elementary mathematical
concepts commonly used in computer vision and in many other areas
of natural sciences and technical disciplines. This includes the basics
of set theory, matrix algebra, differential and integral equations, com-
plex numbers, Fourier transform, probability, random variables, and
graphing. Wherever possible, mathematical topics are described intu-
itively. In this respect it is very helpful that complex mathematical
relations can often be visualized intuitively by images. For a more for-
xv
xvi Preface
mal treatment of the corresponding subject including proofs, suitable
references are given.

How to use this handbook
The handbook has been designed to cover the different needs of its
readership. First, it is suitable for sequential reading. In this way the
reader gets an up-to-date account of the state of computer vision. It is
presented in a way that makes it accessible for readers with different
backgrounds. Second, the reader can look up specific topics of inter-
est. The individual chapters are written in a self-consistent way with
extensive cross-referencing to other chapters of the handbook and ex-
ternal references. The CD that accompanies each volume of the hand-
book contains the complete text of the handbook in the Adobe Acrobat
portable document file format (PDF). This format can be read on all
major platforms. Free Acrobat reader version 3.01 for all major com-
puting platforms is included on the CDs. The texts are hyperlinked in
multiple ways. Thus the reader can collect the information of interest
with ease. Third, the reader can delve more deeply into a subject with
the material on the CDs. They contain additional reference material,
interactive software components, code examples, image material, and
references to sources on the Internet. For more details see the readme
file on the CDs.
Acknowledgments
Writing a handbook on computer vision with this breadth of topics is
a major undertaking that can succeed only in a coordinated effort that
involves many co-workers. Thus the editors would like to thank first
all contributors who were willing to participate in this effort. Their
cooperation with the constrained time schedule made it possible that
the three-volume handbook could be published in such a short period
following the call for contributions in December 1997. The editors are
deeply grateful for the dedicated and professional work of the staff at
AEON Verlag & Studio who did most of the editorial work. We also
express our sincere thanks to Academic Press for the opportunity to

write this handbook and for all professional advice.
Last but not least, we encourage the reader to send us any hints
on errors, omissions, typing errors, or any other shortcomings of the
handbook. Actual information about the handbook can be found at the
editors homepage .
Heidelberg, Germany and La Jolla, California, December 1998
Bernd Jähne, Horst Haußecker, Peter Geißler
Contributors
John Barron graduated from the University of Toronto,
Ontario, Canada with an M.Sc. and PhD in Computer Sci-
ence in 1980 and 1988, respectively. He is currently an
associate professor in Computer Science at the Univer-
sity of Western Ontario. His research interests are in
Computer Vision and include the measurement and in-
terpretation of both optical and range flow and tracking
(deformable) objects in long image sequences.
John Barron, Dept. of Computer Science
Middlesex College, The University of Western Ontario,
London, Ontario, N6A 5B7, Canada,
Horst A. Beyer graduated from the Swiss Federal Insti-
tute of Technology, Zurich, Switzerland with a Diploma
and PhD in photogrammetry in 1982 and 1992, respec-
tively and from the Ohio State University, Columbus,
Ohio with a M.Sc. in Geodetic Science in 1985. He is
founder and president of Imetric SA. His interests lie in
vision based high accuracy three-dimensional measure-
ments and camera calibration.
Horst A. Beyer, Imetric SA, Technopole
CH-2900 Porrentry, Switzerland
,

Maik Bollmann received his diploma in electrical engi-
neering from the University of Paderborn in 1994. He
has been a member of the IMA research group at the de-
partment of computer science, University of Hamburg
since 1994. His research interests include attentive vi-
sion, models of visual attention, and color image pro-
cessing. He is supported by the Deutsche Forschungsge-
meinschaft.
Dipl Ing. Maik Bollmann, University of Hamburg
Dept. of Computer Science, AG IMA
Vogt-Kölln-Str. 30, D-22527 Hamburg, Germany

/>xvii
xviii Contributors
Harald Bornfleth studied physics at the Universities of
Mainz and Heidelberg, both in Germany, where he re-
ceived his diploma degree in May 1995. During this
time, he spent a year at Glasgow University, Great Britain,
with an Erasmus grant from the European Union. From
September 1995 to July 1998, he worked on his PhD
thesis at the Institute of Applied Physics and the In-
terdisciplinary Centre of Scientific Computing, Univer-
sity of Heidelberg. The thesis centered on the devel-
opment of algorithms to analyze three-dimensional and
four-dimensional (3D+time) patterns formed by replication-labeled DNA foci
in cell nuclei.
Dr. Harald Bornfleth, Institut für Angewandte Physik, Universität Heidelberg
Albert-Überle-Str. 3-5, D-69120 Heidelberg, Germany
Harald.Bornfl
Katharina Braun received her diploma in biology and

chemistry from Darmstadt University of Technology in
1980. From 1981 to 1987 she was research assistant at
the Institute for Zoology at Darmstadt University, where
she received her PhD in 1986. From 1988 to 1990 she was
a postdoctoral fellow at the University of Washington. In
1991/92 she held a Helmholtz fellowship awarded from
the German Ministry for Science and Technology (BMBF).
She became leader of an independent research group in
1993. In 1994 she received her habilitation for zoology
from Darmstadt University.
Katharina Braun, Leibniz Institute for Neurobiology
Brenneckestr. 6, 39118 Magdeburg, Germany


Ulrich Büker studied computer science and mathematics
at the University of Paderborn and received his diploma
in 1990. He then joined the computer vision group
in Paderborn and got his doctoral degree in electri-
cal engineering in 1995. Currently he holds the posi-
tion of an Oberingenieur in Paderborn. His main re-
search interests are active vision systems, knowledge-
based and neural recognition strategies for hybrid sys-
tems, and the use of parallel and distributed com-
puting for the development of realtime vision sys-
tems.
Dr Ing. Ulrich Büker, Heinz Nixdorf Institute
Department of Electrical Engineering, University of Paderborn
Pohlweg 47-49, D-33098 Paderborn, Germany

/>Contributors xix

Carlos Cárdenas holds a Dipl. Med. Inform. and is a
PhD student in the basic research group. He has been
a member of the medical IP group since 1996. His in-
terests include graphical user interfaces, object-oriented
development, and software ergonomics. He is a member
of the IEEE and the BVMI.
Carlos E. Cárdenas S.
Div. Medical and Biological Informatics
Deutsches Krebsforschungszentrum
Im Neuenheimer Feld 280, D-69120 Heidelberg
/>David Cheng recently completed both his Bachelor and
Master degrees in Computer Science at the University of
Western Ontario. He is currently a research program-
mer for the nuclear medicine department at the London
Health Sciences Centre.
David Cheng, Dept. of Nuclear Medicine
The University of Western Ontario
London, Ontario, N6A 5B7, Canada

Christoph Cremer received degrees in Physics (Uni-
versity of Munich, 1970), Biology (University of Frei-
burg/Breisgau, 1976), and Human Genetics (University
of Freiburg/Breisgau, 1983). Since October 1983 he
has been Professor of Applied Optics and Information
Processing at the University of Heidelberg, Faculty of
Physics (Institute of Applied Physics). From 1970–1979
he worked at the Institute of Human Genetics, University
of Freiburg; from 1980–1983 he worked at Lawrence Liv-
ermore National Laboratory, California as a visiting sci-
entist. His present research interests are concentrated

on the study of the 3-D structure of the human cell nucleus and its dynam-
ics, using advanced methods of multispectral molecular fluorescence labeling,
laser-supported light microscopy including spectral distance precision mea-
surement procedures, and multidimensional image processing tools.
Prof. Dr. Christoph Cremer, Institute of Applied Physics
University of Heidelberg, Albert-Überle-Str. 3-5, D-69120 Heidelberg, Germany

xx Contributors
Stefan Dauwe graduated in 1997 from the University of
Heidelberg with a Master degree in physics. Since 1998
he has been working at the Institute for Solar Energy Re-
search (ISFH), Hameln/Emmerthal, Germany. Now pur-
suing his PhD, he is working on the development of new,
low-priced, crystalline Si solar cells.
Stefan Dauwe
Institut für Solarenergieforschung GmbH
Am Ohrberg 1, 31860 Emmerthal, Germany

Athanasios Demiris holds a Dipl. Med. Inform. and a
PhD in medical informatics. He has been active in the
area of object-oriented modeling since 1989 and a mem-
ber of the medical IP group since 1992. His inter-
ests involve object-oriented information architectures,
image analysis, fuzzy logic, and cognition-based soft-
ware ergonomics. He was involved in the HELIOS II
AIM project and the “Computer-aided Liver Resection
Planning” project (funded by the Tumorzentrum Heidel-
berg/Mannheim). He is a member of the IEEE and the GI.
Athanasios M. Demiris
Div. Medical and Biological Informatics, Deutsches Krebsforschungszentrum

Im Neuenheimer Feld 280, D-69120 Heidelberg, Germany

/>E. D. Dickmanns studied aerospace engineering at the
RWTH Aachen from 1956-1961 and control engineering
at Princeton University, NJ from 1964-1965. From 1961–
1975 he was a researcher with the German Aerospace
Research Organisation DFVLR. He received his PhD in
engineering from RWTH Aachen in 1969 and was a Post-
doctoral Research Associate with NASA at the MSFC in
Huntsville, AL, U.S. Since 1975 he has been full profes-
sor for control engineering at the University of the Fed-
eral Armed Forces of Germany, Munich (UniBwM), De-
partment of Aero-Space Technology. Founder of the In-
stitut für Systemdynamik und Flugmechanik (ISF) He was
visiting professor at the California Institute of Technology in spring 1996 and
at the Massachusetts Institute of Technology in fall 1998. His research sub-
jects include dynamic machine vision; applications to road vehicle guidance,
navigation of autonomously guided vehicles on the factory floor, landing ap-
proach of aircraft, landmark navigation for helicopters, and robotics in space.
Prof. Dr. Ernst Dieter Dickmanns
Universität der Bundeswehr, München, D-85577 Neubibert, Germany

Contributors xxi
Siegbert Drüe received his diploma and doctoral de-
gree in electrical engineering from the University of
Paderborn in 1983 and 1988. Since 1988 he has been
Akademischer Oberrat at the Department of Electrical
Engineering, University of Paderborn. His research in-
terests include computer vision, active vision systems,
and artificial neural networks and their applications.

Dr Ing. Siegbert Drüe, Heinz Nixdorf Institute
Department of Electrical Engineering
University of Paderborn
Pohlweg 47-49, D-33098 Paderborn, Germany

/>Peter Ulrich Edelmann studied physics at the University
of Ulm, Germany from October 1990 to October 1992.
Since then he has studied at the University of Heidel-
berg, specializing in commercial information technology
and digital image processing. He received the diploma
degree in physics from Heidelberg University in Decem-
ber of 1996. During his diploma thesis he worked on 3-D
image analysis and reconstruction of the morphology of
interphase chromosomes. Since January 1, 1997 he has
been working on his PhD dissertation “Spectral Precision
Distance Microscopy” in the Applied Optics and Informa-
tion Processing group of Prof. C. Cremer.
Peter Ulrich Edelmann
Institut für Angewandte Physik, Universität Heidelberg
Albert-Überle-Str. 3-5, D-69120 Heidelberg, Germany

Sven Eichkorn studied physics in Heidelberg, Germany
and Santiago de Compostella, Spain. In 1997 he received
his MSc degree. His thesis dealt with a LIF method to
measure gas exchange. Currently he is doing research to
acquire a PhD degree at the Max-Planck-Institute for Nu-
clear Physics, Heidelberg. His research interests include
atmospheric trace gas physics.
Sven Eichkorn, Atmospheric Physics Division, Max-
Planck-Institute for Nuclear Physics, Saupfercheckweg 1

D-69117 Heidelberg, Germany
Phone: +49 6221 516-0, Fax: +49 6221 516 324

xxii Contributors
Dirk Engelmann studied physics at the Technical Uni-
versity of Darmstadt, Germany. He is currently pursu-
ing his PhD Thesis at the Interdisciplinary Center for
Scientific Computing at Heidelberg University. His re-
search topic is flow dynamics close air/water interface
and his research interests include measurements of the
flow field near the free water surface with the aid of 4-
D Particle Tracking Velocimetry and numerical simula-
tion of flow applying numerical finite element solvers on
Navier Stokes partial differential equations.
Dirk Engelmann
Forschungsgruppe Bildverarbeitung, IWR
Universität Heidelberg, Im Neuenheimer Feld 368
D-69120 Heidelberg, Germany

/>Rainer H.A. Fink is a professor at the II. Institute of Phys-
iology at the University of Heidelberg. His research inter-
ests comprise calcium regulation, activation of contrac-
tile force, membrane electrophysiology, and laser appli-
cations in the biophysics of muscular contraction. He
held research and teaching positions at the University of
Washington, Seattle, WA, U.S., La Trobe University, Mel-
bourne, and the University of Adelaide, Australia, before
taking up his professorship in Heidelberg in 1990. He
received his PhD in 1979 at the University of Bochum,
Germany.

Prof. Dr. Rainer H.A. Fink, II. Physiologisches Institut
Universität Heidelberg, Im Neuenheimer Feld 326
D-69120 Heidelberg, Germany
fi
Stefan Fries studied physics at the Universities of Karls-
ruhe and Augsburg, Germany. He worked at the Max-
Planck-Institute for Plasma Physics in Garching, Germany
on simulations in the field of electromagnetism. In 1996,
he earned a diploma degree in physics from the Univer-
sity of Augsburg. Since 1997 he has been a member
of the research group on algorithm assessment at the
Fraunhofer Institute for Information and Data Process-
ing in Karlsruhe. His interests are the investigation of
algorithm performance characteristics and the develop-
ment of software tools to measure these quantities.
Dipl Phys. Stefan Fries
FhG-Institut für Informations- und Datenverarbeitung
Fraunhoferstr. 1, D-76131 Karlsruhe, Germany,
Contributors xxiii
Robert Frischholz studied computer science in Erlangen.
Since 1991 he was working for the Fraunhofer Institute
IIS in the field of software development for high-speed
cameras and motion analysis systems. From 1996 to
1998, he was the leader of the development department
of Mikromak GmbH. In 1998 he received his doctoral de-
gree from Erlangen University. Since August 1998, he
is the development manager of DCS AG, Berlin-Erlangen,
and is currently involved in research and development
of biometric person identification.
Dr. Robert Frischholz, DCS AG, Wetterkreuz 19a

D-91058 Erlangen, Germany
,
Christoph Sebastian Garbe studied physics at the Uni-
versity of Hamburg, Germany and the University of Hei-
delberg, Germany and is currently pursuing his Diploma
Thesis at the Interdisciplinary Center for Scientific Com-
puting and the Institute for Environmental Physics in Hei-
delberg. His research interests include measurements of
the flow fields near the free water surface with the aid of
4-D Particle Tracking Velocimetry.
Christoph Sebastian Garbe
Forschungsgruppe Bildverarbeitung
Interdisciplinary Center for Scientific Computing
Im Neuenheimer Feld 368, D-69120 Heidelberg, Germany


Peter Geißler studied physics in Heidelberg. He received
his diploma and doctoral degree from Heidelberg Uni-
versity in 1994 and 1998, respectively. His research in-
terests include computer vision, especially depth-from-
focus, adaptive filtering, and flow visualization as well as
the application of image processing in physical sciences
and oceanography.
Dr. Peter Geißler
Forschungsgruppe Bildverarbeitung, IWR
Universität Heidelberg, Im Neuenheimer Feld 368
D-69120 Heidelberg, Germany


xxiv Contributors

Matthias Graf studied physics at the University of Karls-
ruhe from 1991 to 1998. Between 1995 and 1997 he
developed the topographical measurement system for
layer thickness at the Fraunhofer Institut für Chemische
Technologie (ICT) in Pfinztal, Germany. Since 1998 he
has been working on his doctorate in the microwave pro-
cessing group at the Institut für Kunststoffprüfung und
Kunststoffkunde (IKP), University of Stuttgart, Germany.
Matthias Graf
Institut für Kunststoffprüfung und Kunststoffkunde
(IKP), Pfaffenwaldring 32, D-70569 Stuttgart, Germany
,

Hermann Gröning graduated in 1996 from the Univer-
sity of Heidelberg with a master degree in physics and
is now pursuing his PhD at the Interdisciplinary Center
for Scientific Computing. He is concerned mainly with
radiometric and geometric camera calibration.
Hermann Gröning
Forschungsgruppe Bildverarbeitung, IWR
Universität Heidelberg
Im Neuenheimer Feld 368
D-69120 Heidelberg, Germany

Gerd Häusler is adjunct professor, University of Erlan-
gen, Chair for Optics, and director of the Optical Metrol-
ogy Group. He received his diploma in 1970 and a doc-
toral degree in 1974 from the Optical Institute, Techni-
cal University Berlin. In 1974 he moved to the Chair for
Applied Optics (later Chair for Optics), University of Er-

langen. There he received his habilitation in 1982. As a
doctoral fellow he worked with IBM (Sindelfingen), ENST
Telecom (Paris), and RCA (Zürich). At the University of
Munich and the RIKEN Institute in Tokyo he worked on
optical and electronical image processing and nonlinear
optical feedback systems. His current research interests
include the investigation of the physical limits of range sensing and the con-
struction of sensors that work at these limits and cover the nanometer to meter
range, with applications in industry and medicine.
Prof. Dr. Gerd Häusler, Chair for Optics, Universität Erlangen-Nürnberg
Staudtstraße 7/B2, D-91056 Erlangen, Germany