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Numerical Geometry of Images: Theory, Algorithms, and Applications, by Ron Kimmel
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Numerical Geometry of Images examines computational methods and algorithms in image processing. It explores applications like shape from shading, color-image enhancement and segmentation, edge integration, offset curve computation, symmetry axis computation, path planning, minimal geodesic computation, and invariant signature calculation. In addition, it describes and utilizes tools from mathematical morphology, differential geometry, numerical analysis, and calculus of variations. Graduate students, professionals, and researchers with interests in computational geometry, image processing, computer graphics, and algorithms will find this new text / reference an indispensable source of insight of instruction.
- Sales Rank: #10741512 in Books
- Published on: 2012-08-31
- Released on: 2012-08-31
- Original language: English
- Number of items: 1
- Dimensions: 10.00" h x .51" w x 7.01" l, .87 pounds
- Binding: Paperback
- 209 pages
Review
From the reviews:
"After a brief introduction to differential geometry the book covers computational methods and algorithms in image processing and image analysis. … The author presents classic approaches as well as new solutions … . It would certainly be beneficial for the presumptive reader to be able to rely on a sound background in geometry, linear algebra and calculus." (Anton Gfrerrer, Zentralblatt MATH, Vol. 1049, 2004)
From the Back Cover
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With the ever-rising volume worldwide of visual content on computers and communication networks, it becomes increasingly important to understand visual processing, to model and evaluate image formation, and to attempt to interpret image content.
Numerical Geometry of Images presents an authoritative examination of new computational methods and algorithms in image processing and analysis. In addition to providing the requisite vocabulary for formulating problems, the book describes and utilizes tools from mathematical morphology, differential geometry, numerical analysis, and calculus of variations. Many applications, such as shape reconstruction, color-image enhancement and segmentation, edge integration, path planning, and calculation invariant signatures are explored.
Topics and features:
* Introduces new concepts in geometric image modeling and image interpretation (computer vision)
* Provides the requisite theoretical basis and progresses to using key tools
* Offers a solution to the face-recognition problem by generalizing principles from texture-mapping methods in computer graphics
* Contains numerous helpful exercises and solutions to facilitate learning
* Presents a new perspective on solving classic problems, as well as classic approaches to solving new problems
* Uses industry-proven variational geometric methods and numerical schemes
With its well-organized structure, clarity of presentation, and intuitive style, this new text/reference expedites a solid grasp of the technical material. Only a good background in geometry, linear algebra, and basic calculus is required. Graduate students and professionals with interests in computational geometry, computer vision, image processing, computer graphics, and algorithms will find the book an invaluable and highly practical learning resource.
Most helpful customer reviews
8 of 8 people found the following review helpful.
CS Grad
By Tal Friedman
I was searching for an introduction to this field, and hesitated after reading the two stars review. I found the book at a university bookstore and browsed through it. It is exactly what I was looking for.
A simple yet comprehensive introduction to the field, clear examples, sample code, and some solutions to exercises that helped me go through the chapters.
I like to learn by reading, and searched for an introduction to computer vision and image processing with PDE as tools (I took a classical course that did not cover these aspects). This book was great for the task. It does not pretend to push you into pure theoretical domains as most of the related books seem to enjoy doing, yet it keeps you on the edge when it deals with geometry of moving curves and the interesting model of color image as a surface. If you like geometry like me, you would like the book.
I already experimented with and used some of the tools I picked up from this book. I think it's a great asset to anyone who would like a direct access to a set of geometric tools for manipulating images.
I hesitated weather to give it only 4 stars as the last chapter breaks the flow. However, I saw the author made a whole new book out of it so I kept it 5. Worth the buck.
8 of 11 people found the following review helpful.
Numerical Geometry of Images
By Cinaed
If there's one topic this books is not about, it's the numerical geometry of images
despite its title.
This book should have been titled "Introduction to Geometry of Curves on Surfaces."
The closest the author gets to anything resembling the study of the numerical
geometry of images is the Taylor series expansion of derivatives taught in most
undergraduate calculus courses - and two simple MATLAB program of questionable
value at the end the book.
There are a handful of simple algorithms in the chapter 7 but they only address
fast marching methods applied to two silly boundary value problems. The author
completely ignores the corresponding initial value problem.
I'm giving it 2 stars since the title of the book was completely misleading.
And after reading it, I was left wondering how would someone apply the information
presented in this book to a simple 2 dimensional image since there are absolutely
no examples of any practical value.
9 of 14 people found the following review helpful.
Numerical Geometry of Images
By Michael
A very well-written, interesting and useful book covering a wide range of topics in image processing and computer vision and beyond. A good balance between theory and implementation issues that make the things work. A 100% recommendation to students and specialists in the field.
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