Practical Computer Vision with SimpleCV: The Simple Way to Make Technology See

by Kurt Demaagd, Anthony Oliver, Nathan Oostendorp, Katherine Scott

Overview

Learn how to build your own computer vision (CV) applications quickly and easily with SimpleCV, an open source framework written in Python. Through examples of real-world applications, this hands-on guide introduces you to basic CV techniques for collecting, processing, and analyzing streaming digital images. You’ll then learn how to apply these methods with SimpleCV, using sample Python code. All you need to get started is a Windows, Mac, or Linux system, and a willingness to put CV to work in a variety of ways. Programming experience is optional.

• Capture images from several sources, including webcams, smartphones, and Kinect
• Filter image input so your application processes only necessary information
• Manipulate images by performing basic arithmetic on pixel values
• Use feature detection techniques to focus on interesting parts of an image
• Work with several features in a single image, using the NumPy and SciPy Python libraries
• Learn about optical flow to identify objects that change between two image frames
• Use SimpleCV’s command line and code editor to run examples and test techniques

Product Details

ISBN-13:	9781449343835
Publisher:	O'Reilly Media, Incorporated
Publication date:	07/26/2012
Sold by:	Barnes & Noble
Format:	eBook
Pages:	254
File size:	14 MB
Note:	This product may take a few minutes to download.

About the Author

Kurt is VP of Operations at Ingenuitas, and was a co-founder of Slashdot.

Anthony Oliver has worked in machine vision and robotics for 5 years with Big 3 automakers and other large manufacturers. He has written articles for Vision and Sensor Magazine, The online magazine H+, and given talks at Ignite Automotive and machine vision conferences.

Nathan Oostendorp has 15 of experience on running open source communities, being one of the founders of the website “Slashdot”, the site director for SourceForge and the creator of online communities PerlMonks and Everything2.

Katherine Scott is a graduate student at Columbia University specializing in the field of computer vision, has several peer reviewed papers published in the field of Augmented Reality, and several years of work related history in vision systems.

Table of Contents

Preface; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Chapter 1: Introduction; 1.1 Why Learn Computer Vision; 1.2 What Is the SimpleCV Framework?; 1.3 What Is Computer Vision?; 1.4 Easy Versus Hard Problems; 1.5 What Is a Vision System?; Chapter 2: Getting to Know the SimpleCV Framework; 2.1 Installation; 2.2 Hello World; 2.3 The SimpleCV Shell; 2.4 Introduction to the Camera; 2.5 The Display; 2.6 Examples; Chapter 3: Image Sources; 3.1 Overview; 3.2 Images, Image Sets, and Video; 3.3 The Local Camera Revisited; 3.4 The XBox Kinect; 3.5 Networked Cameras; 3.6 Using Existing Images; 3.7 Examples; Chapter 4: Pixels and Images; 4.1 Pixels; 4.2 Images; 4.3 Transforming Perspectives: Rotate, Warp, and Shear; 4.4 Image Morphology; 4.5 Examples; Chapter 5: The Impact of Light; 5.1 Introduction; 5.2 Light and the Environment; 5.3 Color; 5.4 Color and Segmentation; 5.5 Example; Chapter 6: Image Arithmetic; 6.1 Basic Arithmetic; 6.2 Histograms; 6.3 Using Hue Peaks; 6.4 Binary Masking; 6.5 Examples; Chapter 7: Drawing on Images; 7.1 The Display; 7.2 Working with Layers; 7.3 Drawing; 7.4 Text and Fonts; 7.5 Examples; Chapter 8: Basic Feature Detection; 8.1 Blobs; 8.2 Lines and Circles; 8.3 Corners; 8.4 Examples; Chapter 9: FeatureSet Manipulation; 9.1 Actions on Features; 9.2 FeatureSet Properties; 9.3 FeatureSet Sorting and Filtering; 9.4 Cropping FeatureSets; 9.5 Measuring Features; 9.6 Blobs and Convex Hulls; 9.7 Inside a Blob; 9.8 Rotating Blobs; 9.9 Example: Tracking a Circle (Ball); Chapter 10: Advanced Features; 10.1 Bitmap Template Matching; 10.2 Keypoint Template Matching; 10.3 Optical Flow; 10.4 Haar-like Features; 10.5 Barcode; 10.6 Examples; Advanced Shell Tips; Macro Magic; Run and Edit Python Scripts; Timing; Cameras and Lenses; Cameras and Digital Sensors; Lenses; Advanced Features; Foreground/Background Segmentation; Feature Extractors; Examples;