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Bradski, Gary R.

Learning OpenCV : computer vision with the OpenCV library / Gary Bradski and Adrian Kaehler - Beijing (China) : O'Reilly Media, 2008. - xvii, 555 p. : il., gráficas y tablas ; 24 cm.

Incluye indices y bibliografía


Chapter 1 Overview
What Is OpenCV?
Who Uses OpenCV?
What Is Computer Vision?
The Origin of OpenCV
Downloading and Installing OpenCV
Getting the Latest OpenCV via CVS
More OpenCV Documentation
OpenCV Structure and Content
Portability
Exercises
Chapter 2 Introduction to OpenCV
Getting Started
First Program—Display a Picture
Second Program—AVI Video
Moving Around
A Simple Transformation
A Not-So-Simple Transformation
Input from a Camera
Writing to an AVI File
Onward
Exercises
Chapter 3 Getting to Know OpenCV
OpenCV Primitive Data Types
CvMat Matrix Structure
IplImage Data Structure
Matrix and Image Operators
Drawing Things
Data Persistence
Integrated Performance Primitives
Summary
Exercises
Chapter 4 HighGUI
A Portable Graphics Toolkit
Creating a Window
Loading an Image
Displaying Images
Working with Video
ConvertImage
Exercises
Chapter 5 Image Processing
Overview
Smoothing
Image Morphology
Flood Fill
Resize
Image Pyramids
Threshold
Exercises
Chapter 6 Image Transforms
Overview
Convolution
Gradients and Sobel Derivatives
Laplace
Canny
Hough Transforms
Remap
Stretch, Shrink, Warp, and Rotate
CartToPolar and PolarToCart
LogPolar
Discrete Fourier Transform (DFT)
Discrete Cosine Transform (DCT)
Integral Images
Distance Transform
Histogram Equalization
Exercises
Chapter 7 Histograms and Matching
Basic Histogram Data Structure
Accessing Histograms
Basic Manipulations with Histograms
Some More Complicated Stuff
Exercises
Chapter 8 Contours
Memory Storage
Sequences
Contour Finding
Another Contour Example
More to Do with Contours
Matching Contours
Exercises
Chapter 9 Image Parts and Segmentation
Parts and Segments
Background Subtraction
Watershed Algorithm
Image Repair by Inpainting
Mean-Shift Segmentation
Delaunay Triangulation, Voronoi Tesselation
Exercises
Chapter 10 Tracking and Motion
The Basics of Tracking
Corner Finding
Subpixel Corners
Invariant Features
Optical Flow
Mean-Shift and Camshift Tracking
Motion Templates
Estimators
The Condensation Algorithm
Exercises
Chapter 11 Camera Models and Calibration
Camera Model
Calibration
Undistortion
Putting Calibration All Together
Rodrigues Transform
Exercises
Chapter 12 Projection and 3D Vision
Projections
Affine and Perspective Transformations
POSIT: 3D Pose Estimation
Stereo Imaging
Structure from Motion
Fitting Lines in Two and Three Dimensions
Exercises
Chapter 13 Machine Learning
What Is Machine Learning
Common Routines in the ML Library
Mahalanobis Distance
K-Means
Naïve/Normal Bayes Classifier
Binary Decision Trees
Boosting
Random Trees
Face Detection or Haar Classifier
Other Machine Learning Algorithms
Exercises
Chapter 14 OpenCV's Future
Past and Future
Directions
OpenCV for Artists
Afterword
Chapter 15 Bibliography
Colophon

prender OpenCV se pone en el centro del campo en rápida expansión de la visión por ordenador. Escrito por los creadores de la biblioteca OpenCV de código abierto, este libro es una introducción a la visión por ordenador y muestra cómo se puede construir rápidamente aplicaciones que permiten a las computadoras de "ver" y tomar decisiones basadas en esos datos. la visión por ordenador está en todas partes, en los sistemas de seguridad, sistemas de inspección de fabricación, análisis de imágenes médicas, vehículos aéreos no tripulados, y mucho más. Se cose los mapas de Google y Google Earth juntos, comprueba los píxeles en pantallas LCD, y se asegura de los puntos de sutura en su camisa se cosen correctamente. OpenCV proporciona un marco fácil de usar la visión por ordenador y una amplia biblioteca con más de 500 funciones que se pueden ejecutar código de la visión en tiempo real.

ISBN: 0596516134 9780596516130

Subjects--Topical Terms:
VISIÓN POR COMPUTADOR

Dewey Class. No.: 006.37 / B812o