- Preface
- 1. Overview
- 2. Introduction to OpenCV
- 3. Getting to Know OpenCV Data Types
- 4. Images and Large Array Types
- Dynamic and Variable Storage
- The cv::Mat Class: N-Dimensional Dense Arrays
- Creating an Array
- Accessing Array Elements Individually
- The N-ary Array Iterator: NAryMatIterator
- Accessing Array Elements by Block
- Matrix Expressions: Algebra and cv::Mat
- Saturation Casting
- More Things an Array Can Do
- The cv::SparseMat Class: Sparse Arrays
- Accessing Sparse Array Elements
- Functions Unique to Sparse Arrays
- Template Structures for Large Array Types
- Summary
- Exercises
- Dynamic and Variable Storage
- 5. Array Operations
- More Things You Can Do with Arrays
- cv::abs()
- cv::absdiff()
- cv::add()
- cv::addWeighted()
- cv::bitwise_and()
- cv::bitwise_not()
- cv::bitwise_or()
- cv::bitwise_xor()
- cv::calcCovarMatrix()
- cv::cartToPolar()
- cv::checkRange()
- cv::compare()
- cv::completeSymm()
- cv::convertScaleAbs()
- cv::countNonZero()
- cv::cvarrToMat()
- cv::dct()
- cv::dft()
- cv::cvtColor()
- cv::determinant()
- cv::divide()
- cv::eigen()
- cv::exp()
- cv::extractImageCOI()
- cv::flip()
- cv::gemm()
- cv::getConvertElem() and cv::getConvertScaleElem()
- cv::idct()
- cv::idft()
- cv::inRange()
- cv::insertImageCOI()
- cv::invert()
- cv::log()
- cv::LUT()
- cv::magnitude()
- cv::Mahalanobis()
- cv::max()
- cv::mean()
- cv::meanStdDev()
- cv::merge()
- cv::min()
- cv::minMaxIdx()
- cv::minMaxLoc()
- cv::mixChannels()
- cv::mulSpectrums()
- cv::multiply()
- cv::mulTransposed()
- cv::norm()
- cv::normalize()
- cv::perspectiveTransform()
- cv::phase()
- cv::polarToCart()
- cv::pow()
- cv::randu()
- cv::randn()
- cv::randShuffle()
- cv::reduce()
- cv::repeat()
- cv::scaleAdd()
- cv::setIdentity()
- cv::solve()
- cv::solveCubic()
- cv::solvePoly()
- cv::sort()
- cv::sortIdx()
- cv::split()
- cv::sqrt()
- cv::subtract()
- cv::sum()
- cv::trace()
- cv::transform()
- cv::transpose()
- Summary
- Exercises
- More Things You Can Do with Arrays
- 6. Drawing and Annotating
- 7. Functors in OpenCV
- 8. Image, Video, and Data Files
- 9. Cross-Platform and Native Windows
- 10. Filters and Convolution
- 11. General Image Transforms
- 12. Image Analysis
- 13. Histograms and Templates
- Histogram Representation in OpenCV
- Basic Manipulations with Histograms
- Some More Sophisticated Histograms Methods
- Template Matching
- Square Difference Matching Method (cv::TM_SQDIFF)
- Normalized Square Difference Matching Method (cv::TM_SQDIFF_NORMED)
- Correlation Matching Methods (cv::TM_CCORR)
- Normalized Cross-Correlation Matching Method (cv::TM_CCORR_NORMED)
- Correlation Coefficient Matching Methods (cv::TM_CCOEFF)
- Normalized Correlation Coefficient Matching Method (cv::TM_CCOEFF_NORMED)
- Summary
- Exercises
- 14. Contours
- 15. Background Subtraction
- 16. Keypoints and Descriptors
- 17. Tracking
- 18. Camera Models and Calibration
- 19. Projection and Three-Dimensional Vision
- 20. The Basics of Machine Learning in OpenCV
- 21. StatModel: The Standard Model for Learning in OpenCV
- 22. Object Detection
- 23. Future of OpenCV
- A. Planar Subdivisions
- B. opencv_contrib
- C. Calibration Patterns
- Bibliography
- Index
Learning OpenCV 3
Computer Vision in C++ with the OpenCV Library
Adrian Kaehler and Gary Bradski
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