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Programming Computer Vision with Python Tools and Algorithms for Analyzing Images

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ISBN-10: 1449316549

ISBN-13: 9781449316549

Edition: 2012

Authors: Jan Erik Solem

List price: $79.99
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Description:

If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. As a student, researcher, hacker, or enthusiast, you’ll learn as you follow examples written in Python—the easy-to-learn language that has modules for handling images and mathematical computing and data mining on a par with commercial alternatives.Programming Computer Vision with Pythonteaches computer vision in broad terms that won’t bog you down in theory. Instead, you’ll find this book to be inspiring and motivating. You’ll get all the code you need, with clear explanations on how to reproduce the book’s examples and build upon them directly.
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Book details

List price: $79.99
Copyright year: 2012
Publisher: O'Reilly Media, Incorporated
Publication date: 6/29/2012
Binding: Paperback
Pages: 264
Size: 7.00" wide x 9.25" long x 0.50" tall
Weight: 1.188
Language: English

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Preface
Basic Image Handling and Processing
PIL-The Python Imaging Library
Matplotlib
NumPy
SciPy
Advanced Example: Image De-Noising
Exercises
Conventions for the Code Examples
Local Image Descriptors
Harris Corner Detector
SIFT-Scale-Invariant Feature Transform
Matching Geotagged Images
Exercises
Image to Image Mappings
Homographies
Warping Images
Creating Panoramas
Exercises
Camera Models and Augmented Reality
The Pin-Hole Camera Model
Camera Calibration
Pose Estimation from Planes and Markers
Augmented Reality
Exercises
Multiple View Geometry
Epipolar Geometry
Computing with Cameras and 3D Structure
Multiple View Reconstruction
Stereo Images
Exercises
Clustering Images
K-Means Clustering
Hierarchical Clustering
Spectral Clustering
Exercises
Searching Images
Content-Based Image Retrieval
Visual Words
Indexing Images
Searching the Database for Images
Ranking Results Using Geometry
Building Demos and Web Applications
Exercises
Classifying Image Content
K-Nearest Neighbors
Bayes Classifier
Support Vector Machines
Optical Character Recognition
Exercises
Image Segmentation
Graph Cuts
Segmentation Using Clustering
Variational Methods
Exercises
OpenCV
The OpenCV Python Interface
OpenCV Basics
Processing Video
Tracking
More Examples
Exercises
Installing Packages
NumPy and SciPy
Matplodib
PIL
LibSVM
OpenCV
VLFeat
PyGame
PyOpenGL
Pydot
Python-graph
Simplejson
PySQLite
CherryPy
Image Datasets
Flickr
Panoramio
Oxford Visual Geometry Group
University of Kentucky Recognition Benchmark Images
Other
Image Credits
Images from Flickr
Other Images
Illustrations
References
Index