Practical Computer Vision with SimpleCV
The Simple Way to Make Technology See
Publisher: O'Reilly Media
Release Date: August 2012
Pages: 254
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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
Table of Contents
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Chapter 1 Introduction
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Why Learn Computer Vision
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What Is the SimpleCV Framework?
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What Is Computer Vision?
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Easy Versus Hard Problems
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What Is a Vision System?
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Chapter 2 Getting to Know the SimpleCV Framework
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Installation
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Hello World
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The SimpleCV Shell
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Introduction to the Camera
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The Display
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Examples
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Chapter 3 Image Sources
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Overview
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Images, Image Sets, and Video
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The Local Camera Revisited
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The XBox Kinect
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Networked Cameras
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Using Existing Images
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Examples
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Chapter 4 Pixels and Images
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Pixels
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Images
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Transforming Perspectives: Rotate, Warp, and Shear
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Image Morphology
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Examples
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Chapter 5 The Impact of Light
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Introduction
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Light and the Environment
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Color
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Color and Segmentation
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Example
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Chapter 6 Image Arithmetic
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Basic Arithmetic
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Histograms
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Using Hue Peaks
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Binary Masking
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Examples
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Chapter 7 Drawing on Images
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The Display
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Working with Layers
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Drawing
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Text and Fonts
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Examples
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Chapter 8 Basic Feature Detection
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Blobs
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Lines and Circles
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Corners
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Examples
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Chapter 9 FeatureSet Manipulation
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Actions on Features
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FeatureSet Properties
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FeatureSet Sorting and Filtering
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Cropping FeatureSets
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Measuring Features
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Blobs and Convex Hulls
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Inside a Blob
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Rotating Blobs
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Example: Tracking a Circle (Ball)
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Chapter 10 Advanced Features
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Bitmap Template Matching
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Keypoint Template Matching
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Optical Flow
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Haar-like Features
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Barcode
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Examples
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Appendix Advanced Shell Tips
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Macro Magic
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Run and Edit Python Scripts
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Timing
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Appendix Cameras and Lenses
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Cameras and Digital Sensors
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Lenses
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Appendix Advanced Features
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Foreground/Background Segmentation
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Feature Extractors
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Examples
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