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Computer Vision

Author: Dana H. Ballard
Publisher: Prentice-Hall 1982
Pages: 544
ISBN:0-13-165316-4


Preface:
The dream of intelligent automata goes back to antiquity; its first major articulation
in the context of digital computers was by Turing around I960. Since then, this
dream has been pursued primarily by workers in the field of artificial intelligence,
whose goal is to endow computers with information-processing capabilities
comparable to those of biological organisms. From the outset, one of the goals of
artificial intelligence has been to equip machines with the capability of dealing with
sensory inputs.
Computer vision is the construction of explicit, meaningful descriptions of
physical objects from images. Image understanding is very different from image
processing, which studies image-to-image transformations, not explicit description
building. Descriptions are a prerequisite for recognizing, manipulating, and
thinking about objects.
We perceive a world of coherent three-dimensional objects with many
invariant properties. Objectively, the incoming visual data do not exhibit
corresponding coherence or invariance; they contain much irrelevant or even
misleading variation. Somehow our visual system, from the retinal to cognitive
levels, understands, or imposes order on, chaotic visual input. It does so by using
intrinsic information that may reliably be extracted from the input, and also through
assumptions and knowledge that are applied at various levels in visual processing.
The challenge of computer vision is one of explicitness. Exactly what
information about scenes can be extracted from an image using only very basic
assumptions about physics and optics? Explicitly, what computations must be
performed? Then, at what stage must domain-dependent, prior knowledge about
the world be incorporated into the understanding process? How are world models
and knowledge represented and used? This book is about the representations and
mechanisms that allow image information and prior knowledge to interact in image
understanding.
Computer vision is a relatively new and fast-growing field. The first
experiments were conducted in the late 1950s, and many of the essential concepts
have been developed during the last five years. With this rapid growth, crucial ideas
have arisen in disparate areas such as artificial intelligence, psychology, computer
graphics, and image processing. Our intent is to assemble a selection of this material
in a form that will serve both as a senior/graduate-level academic text and as a
useful reference to those building vision systems. This book has a strong artificial
intelligence flavor, and we hope this will provoke thought. We believe that both the
intrinsic image information and the internal model of the world are important in
successful vision systems.
The book is organized into four parts, based on descriptions of objects at four
different levels of abstraction.
1. Generalized images¡ªimages and image-likeentities.
2. Segmented images¡ªimages organized into subimagcs that are likely to
correspond to "interesting objects."
3. Geometric structures¡ªquantitative models of imageand world structures.
4. Relational structures¡ªcomplex symbolic descriptions of image and world
structures.
The parts follow a progression of increasing abstractness. Although the four
parts are most naturally studied in succession, they are not tightly interdependent. Part
I is a prerequisite for Part II, but Parts III and IV can be read independently.
Parts of the book assume some mathematical and computing background
(calculus, linear algebra, data structures, numerical methods). However, throughout
the book mathematical rigor takes a backseat to concepts. Our intent is to transmit a set
of ideas about a new field to the widest possible audience.
In one book it is impossible to do justice to the scope and depth of prior work in
computer vision. Further, we realize that in a fast-developing field, the rapid influx of
new ideas will continue. We hope that our readers will be challenged to think, criticize,
read further, and quickly go beyond the confines of this volume.
D. H. Ballard
§³. §®. Brown


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Computer Vision,by Dana H. Ballard,Prentice-Hall 1982.rar
Computer Vision,by Dana H. Ballard,Prentice-Hall 1982.rar
Computer Vision,by Dana H. Ballard,Prentice-Hall 1982.rar
Computer Vision,by Dana H. Ballard,Prentice-Hall 1982.rar
Computer Vision,by Dana H. Ballard,Prentice-Hall 1982.rar
Computer Vision,by Dana H. Ballard,Prentice-Hall 1982.rar
Computer Vision,by Dana H. Ballard,Prentice-Hall 1982.rar
Computer Vision,by Dana H. Ballard,Prentice-Hall 1982.rar
--------------------------------------------------------------------------------------------------------

[ Last edited by conanwj on 2009-6-26 at 09:51 ]
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