Book description
"This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised."-William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology
Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on that data.
Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time.
Learning OpenCV will teach any developer or hobbyist to use the framework quickly with the help of hands-on exercises in each chapter. This book includes:
- A thorough introduction to OpenCV
- Getting input from cameras
- Transforming images
- Segmenting images and shape matching
- Pattern recognition, including face detection
- Tracking and motion in 2 and 3 dimensions
- 3D reconstruction from stereo vision
- Machine learning algorithms
Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.
Table of contents
- A Note Regarding Supplemental Files
- Preface
- 1. Overview
- 2. Introduction to OpenCV
-
3. Getting to Know OpenCV
- OpenCV Primitive Data Types
- CvMat Matrix Structure
- IplImage Data Structure
-
Matrix and Image Operators
-
Matrix and Image Operators
- cvAbs, cvAbsDiff, and cvAbsDiffS
- cvAdd, cvAddS, cvAddWeighted, and alpha blending
- cvAnd and cvAndS
- cvAvg
- cvAvgSdv
- cvCalcCovarMatrix
- cvCmp and cvCmpS
- cvConvertScale
- cvConvertScaleAbs
- cvCopy
- cvCountNonZero
- cvCrossProduct
- cvCvtColor
- cvDet
- cvDiv
- cvDotProduct
- cvEigenVV
- cvFlip
- cvGEMM
- cvGetCol and cvGetCols
- cvGetDiag
- cvGetDims and cvGetDimSize
- cvGetRow and cvGetRows
- cvGetSize
- cvGetSubRect
- cvInRange and cvInRangeS
- cvInvert
- cvMahalanobis
- cvMax and cvMaxS
- cvMerge
- cvMin and cvMinS
- cvMinMaxLoc
- cvMul
- cvNot
- cvNorm
- cvNormalize
- cvOr and cvOrS
- cvReduce
- cvRepeat
- cvScale
- cvSet and cvSetZero
- cvSetIdentity
- cvSolve
- cvSplit
- cvSub, cvSubS, and cvSubRS
- cvSum
- cvSVD
- cvSVBkSb
- cvTrace
- cvTranspose and cvT
- cvXor and cvXorS
- cvZero
-
Matrix and Image Operators
- Drawing Things
- Data Persistence
- Integrated Performance Primitives
- Summary
- Exercises
- 4. HighGUI
- 5. Image Processing
- 6. Image Transforms
- 7. Histograms and Matching
- 8. Contours
-
9. Image Parts and Segmentation
- Parts and Segments
- Background Subtraction
- Watershed Algorithm
- Image Repair by Inpainting
- Mean-Shift Segmentation
- Delaunay Triangulation, Voronoi Tesselation
- Exercises
- 10. Tracking and Motion
- 11. Camera Models and Calibration
-
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
- 13. Machine Learning
- 14. OpenCV’s Future
- 15. Bibliography
- Index
- About the Authors
- Colophon
- Copyright
Product information
- Title: Learning OpenCV
- Author(s):
- Release date: September 2008
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9780596516130
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