Page 4 -

Preface

Pattern recognition currently comprises a vast body of methods supporting the
development of numerous applications in many different areas of activity. The
generally recognized relevance of pattern recognition methods and techniques lies,
for the most part, in the general trend or "intelligent" task emulation, which has
definitely pervaded our daily life. Robot assisted manufacture, medical diagnostic
systems, forecast of economic variables, exploration of Earth's resources, and
analysis of satellite data are just a few examples of activity fields where this trend
applies. The pervasiveness of pattern recognition has boosted the number of task-
specific methodologies and enriched the number of links with other disciplines. As
counterbalance to this dispersive tendency there have been, more recently, new
theoretical developments that are bridging together many of the classical pattern
recognition methods and presenting a new perspective of their links and inner
workings.
This book has its origin in an introductory course on pattern recognition taught
at the Electrical and Computer Engineering Department, Oporto University. From
the initial core of this course, the book grew with the intent of presenting a
comprehensive and articulated view of pattern recognition methods combined with
the intent of clarifying practical issucs with the aid ofexarnples and applications to
real-life data. The book is primarily addressed to undergraduate and graduate
students attending pattern recognition courses of engineering and computer science
curricula. In addition to engineers or applied mathematicians, it is also common for
professionals and researchers from other areas of activity to apply pattern
recognition methods, e.g. physicians, biologists, geologists and economists. The
book includes real-life applications and presents matters in a way that reflects a
concern for making them interesting to a large audience, namely to non-engineers
who need to apply pattern recognition techniques in their own work, or who
happen to be involved in interdisciplinary projects employing such techniques.
Pattern recognition involves mathematical models of objects described by their
features or attributes. It also involves operations on abstract representations of what
is meant by our common sense idea of similarity or proximity among objects. The
mathematical formalisms, models and operations used, depend on the type of
problem we need to solve. In this sense, pattern recognition is "mathematics put
into action". Teaching pattern recognition without getting the feedback and insight
provided by practical examples and applications is a quite limited experience, to
say the least. We have, therefore, provided a CD with the book, including real-life
data that the reader can use to practice the taught methods or simply to follow the
explained examples. The software tools used in the book are quite popular, in thc
academic environment and elsewhere, so closely following the examples and