Programming Computer Vision with Python

Tools and Algorithms for Analyzing Images

By: Jan Erik Solem

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Paperback | 6 July 2012

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260 Pages

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23.5 x 17.5 x 1.5

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If you want a basic understanding of computer vision's underlying theory and algorithms, this hands-on introduction is the ideal place to start. You'll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python.

Programming Computer Vision with Python explains computer vision in broad terms that won't bog you down in theory. You get complete code samples with explanations on how to reproduce and build upon each example, along with exercises to help you apply what you've learned. This book is ideal for students, researchers, and enthusiasts with basic programming and standard mathematical skills.

Learn techniques used in robot navigation, medical image analysis, and other computer vision applications
Work with image mappings and transforms, such as texture warping and panorama creation
Compute 3D reconstructions from several images of the same scene
Organize images based on similarity or content, using clustering methods
Build efficient image retrieval techniques to search for images based on visual content
Use algorithms to classify image content and recognize objects
Access the popular OpenCV library through a Python interface

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Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Computer Vision Computer Programming & Software Development Web Programming Graphical & Digital Media Applications O'Reilly Programming & Scripting Languages

Preface	p. vii
Basic Image Handling and Processing	p. 1
PIL-The Python Imaging Library	p. 1
Matplotlib	p. 3
NumPy	p. 7
SciPy	p. 16
Advanced Example: Image De-Noising	p. 23
Exercises	p. 26
Conventions for the Code Examples	p. 27
Local Image Descriptors	p. 29
Harris Corner Detector	p. 29
SIFT-Scale-Invariant Feature Transform	p. 36
Matching Geotagged Images	p. 44
Exercises	p. 51
Image to Image Mappings	p. 53
Homographies	p. 53
Warping Images	p. 57
Creating Panoramas	p. 70
Exercises	p. 77
Camera Models and Augmented Reality	p. 79
The Pin-Hole Camera Model	p. 79
Camera Calibration	p. 84
Pose Estimation from Planes and Markers	p. 86
Augmented Reality	p. 89
Exercises	p. 98
Multiple View Geometry	p. 99
Epipolar Geometry	p. 99
Computing with Cameras and 3D Structure	p. 107
Multiple View Reconstruction	p. 113
Stereo Images	p. 120
Exercises	p. 125
Clustering Images	p. 127
K-Means Clustering	p. 127
Hierarchical Clustering	p. 133
Spectral Clustering	p. 140
Exercises	p. 145
Searching Images	p. 147
Content-Based Image Retrieval	p. 147
Visual Words	p. 148
Indexing Images	p. 151
Searching the Database for Images	p. 155
Ranking Results Using Geometry	p. 160
Building Demos and Web Applications	p. 162
Exercises	p. 165
Classifying Image Content	p. 167
K-Nearest Neighbors	p. 167
Bayes Classifier	p. 175
Support Vector Machines	p. 179
Optical Character Recognition	p. 183
Exercises	p. 189
Image Segmentation	p. 191
Graph Cuts	p. 191
Segmentation Using Clustering	p. 200
Variational Methods	p. 204
Exercises	p. 206
OpenCV	p. 209
The OpenCV Python Interface	p. 209
OpenCV Basics	p. 210
Processing Video	p. 213
Tracking	p. 216
More Examples	p. 223
Exercises	p. 226
Installing Packages	p. 227
NumPy and SciPy	p. 227
Matplodib	p. 228
PIL	p. 228
LibSVM	p. 228
OpenCV	p. 229
VLFeat	p. 230
PyGame	p. 230
PyOpenGL	p. 230
Pydot	p. 230
Python-graph	p. 231
Simplejson	p. 231
PySQLite	p. 232
CherryPy	p. 232
Image Datasets	p. 233
Flickr	p. 233
Panoramio	p. 234
Oxford Visual Geometry Group	p. 235
University of Kentucky Recognition Benchmark Images	p. 235
Other	p. 235
Image Credits	p. 237
Images from Flickr	p. 237
Other Images	p. 238
Illustrations	p. 238
References	p. 239
Index	p. 243
Table of Contents provided by Ingram. All Rights Reserved.

Programming Computer Vision with Python

Tools and Algorithms for Analyzing Images

At a Glance

Paperback

Shipping

How to return your order

Defective items

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