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This includes how to use the software, with examples; the applications development process; the software development environment provided with CVIPtools; and programming and tutorial exercises.
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True computer imaging for engineers!
Digital signal processing has long been the domain of electrical engineers, while the manipulation of image data has been handled by computer scientists. The convergence of these two specialties in the field of Computer Vision and Image Processing (CVIP) is the subject of this pragmatic book, written from an applications perspective and accompanied by its own educational and developmentsoftware environment, CVIPtools. Illustrated with hundreds of examples, Computer Vision and Image Processing brings together the theory of computer imaging with the tools needed for practical research and development.
The first part of Computer Vision and Image Processing presents a system model for each of the major application areas of CVIP, relating each specific algorithm to the overall process of applications development.
The areas covered are:
Computer Vision and Image Processing's second half focuses on the use of the CVIPtools environment, the software developed especially by the author and included on the accompanying CD-ROM. These advanced chapters discuss:
CVIPtools is a GUI-based application, which includes an extended Tcl shell, that is ANSI-C compatible and runs on most flavors of UNIX and Windows NT/95.
To get the most out of Computer Vision and Image Processing, a basic background in mathematics and computers is necessary. Knowledge of the C programming language will enhance the usefulness of the algorithms used in programming, and an understanding of signal and system theory is helpful in mastering transforms and compression.
Engineers, programmers, graphics specialists, multimedia developers, and medical imaging professionals will all appreciate Computer Vision and Image Processing's solid introduction for anyone who uses computer imaging.
I. COMPUTER VISION AND IMAGE PROCESSING FUNDAMENTALS.
1. Introduction to Computer Vision and Image Processing.Overview: Computer Imaging. Computer Vision. Image Processing. Computer Imaging Systems. The CVIPtools Software. Human Visual Perception. Image Representation. Digital Image File Formats. References.
2. Image Analysis.Introduction. Preprocessing. Edge/Line Detection. Segmentation. Discrete Transforms. Feature Extraction and Analysis. References.
3. Image Restoration.Introduction. Noise. Noise Removal Using Spatial Filters. Frequency Domain Filters. Geometric Transforms. References.
4. Image Enhancement.Introduction. Gray-Scale Modification. Image Sharpening. Image Smoothing. References.
5. Image Compression.Introduction. Lossless Compression Methods. Lossy Compression Methods. References.
II. CVIPtools.
6. Using CVIPtools.Introduction and Overview. The Graphical User Interface. Examples.
7. CVIPtools Applications.Introduction. Automatic Skin Tumor Border Identification. Helicopter Image Enhancement and Analysis. Wavelet/Vector Quantization Compression. Image Segmentation Using a Deformable Template Algorithm. Visual Acuity/Night Vision Simulation.
8. Programming with CVIPtools.Introduction to CVIPlab. CVIP Laboratory Exercises. The CVIPtcl and CVIPwish Shells.
9. CVIPtools Library Functions.Introduction. Arithmetic and Logic Library_libarithlogic. Band Image Library_libband. Color Image Library_libcolor. Compression Library_libcompress. Conversion Library_libconverter. Display Library_libdisplay. Feature Extraction Library_libfeature. Geometry Library_libgeometry. Histogram Library_libhisto. Image Library_libimage. Data Mapping Library_libmap. Morphological Library_libmorph. Noise Library_libnoise. Segmentation Library_libsegment. Spatial Filter Library_libspatialfilter. Transform Library_libtransform.
III. APPENDICES.
A. The CVIPtools CD-ROM.Getting CVIPtools software updates. To get via the WWW.
C. CVIPtools Functions.Toolkit Libraries. Toolbox Libraries.
D. CVIPtcl Command List and Corresponding CVIPtools Functions.Preface
Computer vision deals with the processing of image data for use by a computer. The automatic classification of blood cells in medical images and the robotic control of an unmanned lunar rover are examples of computer vision applications. Image processing involves the manipulation of image data for viewing by people. Examples include special effects imaging for motion pictures and the restoration of satellite images distorted by a faulty lens. Computer imaging blends the techniques of both computer vision and image processing; consequently, it is a rapidly growing and exciting field to be involved in today. This book presents a unique approach to the practice of computer imaging and will be of interest both to those who want to learn more about the subject and to those who just want to use computer imaging techniques.
Why Write This Book?
This book takes an applications-oriented approach to computer vision and image processing (CVIP) and brings together these two separate but related fields with an engineering perspective. Although a number of good theory-based textbooks are available, they are primarily of two types: those that were developed from an electrical engineering, specifically a digital signal processing perspective (image processing) and those that have evolved from a computer science perspective (computer vision). In recent years a few books have been written that combined these fields, but they, too, have been primarily theoretical in nature. I felt that there was a need for an application-oriented book that would bring these two perspectives together, and this book fills that gap. The book's development was initiated by my research experience while working toward a PhD in electrical engineering. I encountered two problems then. First, the research and development information available in the professional journals was often incomplete, too specific, or too esoteric. Second, I found that I spent a major portion of my time developing software, severely limiting time available for research and development. The first problem I hope to solve by writing this book_I have organized and clearly presented paradigms and methods for the development of CVIP applications. I attacked the second problem by developing a set of reusable software tools for CVIP applications and research and, in the process, developed a valuable environment for learning about computer imaging.
Who Will Use This Book?
Computer Vision and Image Processing: A Practical Approach Using CVIPtools is intended for use by working professionals in research and development, the commercial sectors, and the academic community. This includes practicing engineers, consultants, and programmers, as well as graphics artists, medical imaging professionals, and multimedia specialists, among others. The book can be used for self study and is of interest to anyone involved with developing computer imaging applications, whether they are engineers, geographers, biologists, oceanographers, or astronomers. At the university it can be used in any computer imaging applications-oriented course, typically in senior-level or graduate courses, or as a laboratory text in a standard computer vision and/or image processing course. It is essentially conceptual in nature, with only as much theory as is necessary to understand the use of the algorithms. The prerequisites for the book are an interest in the field, a basic background in computers, and a basic math background (algebra/trigonometry). Knowledge of the C programming language will be necessary for those intending to develop algorithms at the pro gramming level. Some background in signal and system theory is required for those intending to gain a deep understanding of the sections on transforms and compression. However, the book is written so that those individuals who do not have this background can learn to use the tools and achieve a conceptual understanding of the material.
Approach
Throughout the book I have opted to use what I call a just-in-time approach to learning. Instead of presenting techniques or mathematical tools when they fit into a nice, neat theoretical framework, topics are presented as they become necessary for practical applications. For example, the mathematical process of convolution is introduced when it is needed for an image zoom algorithm, and morphological operations are introduced when morphological filtering operations are needed after image segmentation. This approach provides you with the motivation to learn and use the tools and topics because you will see an immediate need for them. It also makes the book more useful to working professionals who may not work through the book sequentially but will refer to a specific section as the need arises.
Organization of the Book
The book is divided into two major parts: I. Computer Vision and Image Processing Fundamentals, and II. CVIPtools. The first part of the book contains all the basic concepts, definitions, models, and algorithms necessary to understand computer imaging. Each chapter includes numerous references and examples for the material presented. The material is presented in a conceptual and application-oriented manner, so that you will immediately understand how each topic fits into the overall framework of CVIP applications development.