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This book provides a modern, algorithmic introduction to digital
image p- cessing, designed to be used both by learners desiring a
?rm foundation on which to build and practitioners in search of
critical analysis and modern - plementations of the most important
techniques. This updated and enhanced paperbackedition
ofourcomprehensivetextbookDigital Image Processing: An Algorithmic
Approach Using Java packages the original material into a series of
compactvolumes, therebysupporting a
?exiblesequenceofcoursesindigital image processing. Tailoring the
contents to the scope of individual semester courses is also an
attempt to provide a?ordable (and "backpack-compatible") textbooks
without comprimising the quality and depth of content.
Oneapproachtolearninganewlanguageistobecomeconversantinthecore
vocabulary and to start using it right away. At ?rst, you may only
know how to ask for directions, order co?ee, and so on, but once
you become con?dent with the core, you will start engaging others
in "conversations" and rapidly learn how to get things done. This
step-by-step approach works equally well in many areas of science
and engineering. In this ?rst volume, ostentatiously titled
Fundamental Techniques,wehave attemptedtocompilethecore"vocabulary"
ofdigitalimageprocessing,starting from the basic concepts and
elementary properties of digital images through simple statistics
and point operations, fundamental ? ltering techniques, loc-
ization of edges and contours, and basic operations on color
images. Mastering these most commonly used techniques and
algorithms will enable you to start being productive right away.
This authoritative collection introduces the reader to the state of
the art in iris recognition technology. Topics and features: with a
Foreword by the "father of iris recognition," Professor John
Daugman of Cambridge University; presents work from an
international selection of preeminent researchers, reflecting the
uses of iris recognition in many different social contexts;
provides viewpoints from researchers in government, industry and
academia, highlighting how iris recognition is both a thriving
industry and an active research area; surveys previous developments
in the field, and covers topics ranging from the low-level (e.g.,
physics of iris image acquisition) to the high level (e.g.,
alternative non-Daugman approaches to iris matching); introduces
many active and open areas of research in iris recognition,
including cross-wavelength matching and iris template aging. This
book is an essential resource for anyone wishing to improve their
understanding of iris recognition technology.
This is the second volume of a book series that provides a modern,
algori- mic introduction to digital image processing. It is
designed to be used both by learners desiring a ?rm foundation on
which to build and practitioners in search of critical analysis and
modern implementations of the most important techniques. This
updated and enhanced paperback edition of our compreh- sive
textbook Digital Image Processing: An Algorithmic Approach Using
Java packages the original material into a series of compact
volumes, thereby s- porting a ?exible sequence of courses in
digital image processing. Tailoring the contents to the scope of
individual semester courses is also an attempt to p- vide a?ordable
(and "backpack-compatible") textbooks without comprimising the
quality and depth of content. This second volume, titled Core
Algorithms, extends the introductory - terial presented in the ?rst
volume (Fundamental Techniques) with additional techniques that
are, nevertheless, part of the standard image processing to- box. A
forthcomingthird volume(Advanced Techniques) will extendthis series
and add important material beyond the elementary level, suitable
for an - vanced undergraduate or even graduate course.
This modern, self-contained textbook provides an accessible
introduction to the field from the perspective of a
practicing programmer, supporting a detailed presentation of
the fundamental concepts and techniques with practical
exercises and fully worked out implementation examples. This
much-anticipated 3rd edition of the definitive textbook
on Digital Image Processing has been completely revised and
expanded with new content, improved illustrations and
teaching material. Topics and features: Contains new chapters on
fitting of geometric primitives, randomized feature detection
(RANSAC), and maximally stable extremal regions (MSER). Includes
exercises for most chapters and provides additional supplementary
materials and software implementations at an associated website.
Uses ImageJ for all examples, a widely used open source imaging
environment that can run on all major platforms. Describes each
solution in a stepwise manner in mathematical form, as
abstract pseudocode algorithms, and as complete Java programs
that can be easily ported to other programming languages.
Presents suggested outlines for a one- or two-semester course in
the preface. Advanced undergraduate and graduate students will find
this comprehensive and example-rich textbook will serve as the
ideal introduction to digital image processing. It will also
prove invaluable to researchers and professionals seeking a
practically focused self-study primer.
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