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.

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 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 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.