Image Technology: Advances in Image Processing, Multimedia and Machine Vision

757 Pages·1996·20.968 MB·English

by  S. L. Bartlett, A. Hampapur, M. J. Huber, D. Kortenkamp, S. Moezzi (auth.), Dr. Jorge L. C. Sanz (eds.)

Image Technology
Springer-V erlag Berlin Heidelberg GmbH
Jorge L.C. Sanz
(Ed.)
Image Technology
Advances in Image Processing,
Multimedia and Machine Vis ion
With 344 Figures, Some in Color and 41 rabIes
i
Springer
Dr. Jorge L.e. Sanz
Coordinated Science Laboratory
University of Illinois at Urbana-Champaign
Urbana, IL 61801
USA
IBM Argentina
Ingeniero Enrique Butty 275
1300 Buenos Aires
Argentina
ISBN 978-3-642-63528-1 ISBN 978-3-642-58288-2 (eBook)
DOI 10.1007/978-3-642-58288-2
Library of Congress Cataloging-in-Publication Dat •. Image technology: advances in im.ge process
ing, multimedia and machine vision/Jorge L.C. Sanz, (ed). p. cm. Includes bibliographical refer
ences.1. Image processing. 2. Multimedia systems. 3. Computer vision. 1. Sanz, J.L.C.
(Jorge L.e.), 1955- . TA1637.145 1995 006.4'2-dc20 95-42729
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© Springer-Verlag Berlin Heidelberg 1996
Originally published by Springer-Verlag Berlin Heidelberg New York in 1996
Softcover reprint of the hardcover 1 st edition 1996
The use of general descriptive names, registered names, trademarks, etc. in this publication does not
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To my wife Diana,
to whom lowe all what
I have in my life
June 1994
Introduction
Almost seven years have elapsed since I edited the book Advances in
Machine Vision, published by Springer-Verlag in 1988. In spite of the
tough economic times of the early 1990s, image processing and ma
chine vision continue to be areas of active research and development.
Commercial and industrial applications are widespread, and gaining
more acceptance in different business environments. The advent of
new algorithms and electronics clears the way to larger and more
complex image applications.
In this book, several areas of continued interest and work are
visited, covering some fundamentals as well as technology-oriented
contributions. The book emphasizes concrete applications and prom
ising technologies, although it also includes a few reviews of funda
mental subjects that are relevant to both specialists and newcomers to
this exciting field. The chapters by no means cover all areas in image
processing and machine vision, but hopefully provide a solid start for
a graduate student or the specialist who wants to gain some insight
into the chosen subjects.
The book starts with an in-depth treatment of machine vision and
mobile robots. The chapter "Vision for Mobile Robots" by Bartlett,
Hampapur, Huber, Kortenkamp, Moezzi, and Weymouth presents an
extensive review of work done in this area. The authors describe opti
cal flow algorithms from a critical perspective and propose new ap
proaches for mobile robots that take advantage of constraints unique
to this domain. They go further into depth computation through ego
motion complex logarithmic mapping. The results of the stereo tech
niques are improved by a new computational model in which spatial
information is integrated over time without the direct computation of
camera motion. This idea is tested on stereo image sequences coming
from a mobile robot. The chapter ends with a discussion of collision
avoidance using visual information, and coordination among multiple
mobile robots, with concrete experiences obtained from the CARMEL
project.
As in the case of mobile robots, deriving 3-dimensional informa
tion about a scene from its images is a challenging general problem.
The chapter "3D Constraints on Monocular Image Sequences: Theory
VIII Introduction
and Algorithms" by Sawhney and Anandan presents a critical ap
praisal of the techniques for problems involving geometric constraints
between a scene and its monocular images when the scene is viewed
from various positions and orientations of the camera.
The chapter "Integrating Selective Attention and Space-Variant
Sensing in Machine Vision" by Colombo, Rucci, and Dario describes
the simultaneous use of selective attention mechanisms and retina-like
sensing in a system for machine perception.
The processing and understanding of color images has received a
great deal of attention in recent years. The chapter "Modeling Color
Images for Machine Vision" by Healey presents a review and an evalu
ation of color image models that have been used in machine vision. A
detailed account of recent work on color texture is also shown.
Another subject that has attracted the interest of many image
processing and computer vision researchers is the use of the Minimum
Description Length (MDL) principle for different estimation problems
in the field. MDL is explained in general terms in the chapter by
Kanungo, Dom, Niblack, and Steele. Their chapter "A Fast Algorithm
for MDL-Based Multi-Band Image Segmentation" also deals with the
application of MDL to the segmentation of color images. They intro
duce novel methods to deal with the complexity of the optimization
problems arising from the proposed functional.
With increasing interest in making transportation more efficient,
a number of projects have been launched worldwide. One important
aspect of public transportation is to provide large cities with efficient
schedules for public buses. Counting people flow is an important way
to determine the need for more buses, to measure congestion, and so
on. The chapter "A Vision System for Estimating People Flow" by Del
Bimbo and Nesi deals with new methods for counting people getting
on and off a bus or other mass transportation vehicle.
The chapter "A Bayesian Network for Automatic Visual Crowding
Estimation in Underground Stations" by Regazzoni, Tesei, and
Vernazza also deals with the problem of counting people, this time in
subway stations. The paper presents new techniques for estimating
people congestion by means of multiple cameras and statistical ap
proaches based on visual features. Applications to real data obtained
from the underground system in Genoa, Italy, are given.
Another important aspect of transportation systems relies on the
improvement of highway control, and in particular, on the ability to
automate the job done at toll gates. The ideal system will be one that
can bill a passing car through a toll directly to the owner without
manual intervention and without traffic congestion. An important
technology that may enable this process is the automatic reading of the
license plate of a car passing through a toll gate. The chapter "Recog
nition of Motor Vehicle License Plates in Rear-View Images" by
Introduction IX
Granieri, Stabile, and Comelli describes a system based on customized
optical character recognition, suitably adapted to the varying scene
situations arising from different illumination, weather conditions, and
so on.
Using image processing and image understanding techniques to
automate tasks of industrial inspection has been a research effort for
many years. Its potential for improving quality and reducing costs of
industrial production has been demonstrated by many working sys
tems used in production environments.
The next four chapters cover different aspects of the many issues
involved in inspection. They have been selected from papers submitted
to the 11 th International Conference on Pattern Recognition at the
Hague, The Netherlands. The topics covered are quality control of
hybrid circuits, evaluation of gravure paper quality, underwater in
spection of pipelines, and dimensional inspection of machine parts.
These different topics indicate the breadth of problems and applica
tions for industrial inspection tasks.
The chapter "Automatic System of Quality Control by Vision of
Hybrid Circuits" by Chehdi and Corazza describes a system for check
ing the production of hybrid circuits. The position of the circuit links
and the quality of the solder joints are controlled by using a model of
non-defective circuits. Experimental results show that about 97% of
the flaws can be detected under the imposed time constraints.
The chapter "An Image Analysis Based Method to Evaluate Gra
vure Paper Quality" by Langinmaa describes a method to measure
paper quality on the basis of measuring the quality of gravure printing.
The problem is to measure defects quickly and objectively. Three dif
ferent nonlinear processing methods are evaluated and it is shown that
about 90% of defects can be detected. Also, the approach is reasonably
insensitive to small parameter changes.
The chapter "A Vision System for an Autonomous Underwater
Vehicle" by Hallset describes the vision component for a pipeline
inspection system. Problems involved are light absorption, a non
uniform background on the sea bed, marine materials covering parts
of the pipeline, and more than one pipeline in the field of view. The
system employs a pipeline map to match pipeline segments with model
segments. Experimental results show that the system can find and
analyze moderately complex configurations and is robust against scal
ing and rotation errors.
The chapter "Visual Inspection of Machined Parts" by Modayur,
Shapiro, and Haralick addresses the problem of defining and measur
ing geometric tolerances of machined parts. Presently, tolerances of
industrial parts are usually evaluated by precision measurement de
vices. Ap romising future approach is to use optical precision measure
ment, based on image processing approaches. The paper gives a
x Introduction
thorough definition of tolerances and works out propagation of uncer
tainties from low-level image processing up to tolerance decision. It is
demonstrated experimentally that the error probabilities obtained by
this approach are lower than those obtained without uncertainty
propagation.
In summary, these chapters demonstrate that industrial inspec
tion tasks can be handled successfully by image processing ap
proaches. It is another question whether the approaches are already
economically competitive. However, the cost of labor is steadily in
creasing and the cost of hardware is decreasing. In addition, automatic
inspection is objective, not subject to fatigue, and readily applicable
also in hazardous environments.
Important applications of texture measures include the inspection
of finished surfaces, the assessment of wear of different materials in
textile production, and quality of wood logs for commercial use,
among many others. Finnish industries have a long record in the
exploitation of machine vision technologies in order to better control
production quality. The chapter «Texture Analysis in Industrial
Applications" by Pietikaeinen and Ojala presents a thorough review
of texture measures and their application to different inspection
problems.
Two chapters reviewing and presenting new material relevant to
the practitioner in machine vision are «Methods for Illumination-In
variant Image Processing" by Miller and Shridhar, and «A Comparison
of Algorithms for Subpixel Peak Detection" by Fisher and Naidu.
These chapters have techniques often used in different practical prob
lems arising in 2-dimensional image processing. On a similar track is
the chapter «Splines and Spline Fitting Revisited" by Vargas, E.
Rodriguez, Flickner, and Sanzo Splines are frequently involved in
fitting tasks and shape modeling in image processing, and the close
relationship between them and multi-resolution periodic wavelets will
attract renewed interest in spline fundamentals.
The chapters on visual inspection from ICPR in Holland are com
plemented by the chapter «Algorithms for a Fast Confocal Optical
Inspection System" by Rao, Ramesh, Wu, Mandeville, and Kerstens, in
which the authors present a system for surface topography measure
ment by means of confocal imaging. An image processing module is
designed to detect surfaces in the incoming signal as well as to improve
its resolution.
A long-standing and important 2-dimensional computer vision
problem is the recognition of aircraft on the ground. The chapter
«Qualitative Recognition of Aircraft in Perspective Aerial Images" by
Das, Bhanu, Wu, and Braithwaite gives a summary of existing systems
and presents a new system based on the use of a hierarchical object
model data base using geometric entities.
Introduction XI
Non-conventional imaging presents new challenges to the image
processing and machine vision fields. Conversely, breakthroughs in
robust algorithms for image processing and machine vision may un
leash the power of new sensing methods for sub-micron metrology
problems. The chapter "Scanning Probe Microscopy: Trends and Im
age Processing Issues" by Pingali and Jain demonstrates the impor
tance of image processing techniques in scanning probe microscopy,
and surveys different scanning probe microscopes such as scanning
tunneling microscopy, magnetic force microscopy, atomic force
microscopy, and scanning ion conductance microscopy, all from the
perspective of image processing algorithms.
Images are at the heart of the new information management sys
tems. The diversity of image data is paramount: from typed documents
to color maps, and from detail-sensitive imagery to highly redundant
video sequences. The representation and handling of this diversity,
and its combination with other forms of data such as graphics and text,
bring important new problems to information handling systems. The
storage, modeling, and representation of image information is an
active area of research.
The chapter "Advances in Image Information Modeling" by
Grosky and Mehrotra discusses some of the key issues involved in
image formation modeling, representation, and information repre
sented in image management systems. Some future directions for re
search are discussed. Related material on this important topic can be
found in the summary of the NSF Workshop on Visual Information
Management Systems, published by R. Jain in SIGMOD Record, Vol.
22, Sept. 1993.
An important aspect of image representation is the volume of
storage required in very large applications. Several commercial appli
cations do not tolerate the loss associated with conventional compres
sion algorithms. Such applications include archiving and retrieval
systems for medical images, fingerprint storage systems, and many
others. The massive number of images and high image resolution
necessary in these applications call for judicious image compression
techniques. Aiazzi, Alparone, and Baronti illustrate some of these
issues in the chapter "Lossless Compression of Medical Images by
Content-Driven Laplacian Pyramid Splitting".
A central image processing research and development subject of
the 1990s is video compression. Applications of video storage and
retrieval are commonly referred to as "multimedia". Two last two
chapters of the book are devoted to the subject of video compression.
The chapter "Video Compression for Multimedia Applications"
by A. Rodriguez, Fogg, and Delp describes algorithms and techniques
commonly used in both software-only and hardware-assisted com
pression categories. A practical description of the technology is given