A Practical Introduction to Computer Vision with OpenCV

Index

• A-algorithm
• Accuracy
• Affine transformation
  • Change of Scale
  • Panoramic distortion
  • Rotation
  • Skewing
  • Translation
  • Unknown
• Aperture Problem
•  
• Background Model
  • Gaussian Mixture Model
  • Median background image
  • Running Average
  • Running Gaussian Average
  • Selectivity
  • Static background image
• Binary Vision
  • Mathematical Morphology
  • Thresholding
• Border Detection
• Boundary Chain Codes
•  
• Camera Calibration
• Camera Model
  • Distortion
  • Radial Distortion
  • Simple pinhole camera model
  • Tangential Distortion
• Cascade of Haar Classifiers
  • Adaboost
  • Cascade
  • Features
  • Integral Image
  • Strong classifiers
  • Training
  • Weak classifiers
• Chamfer Matching
  • Chamfer Matching Algorithm
  • Chamfering Algorithm
• Colour
  • Bayer
  • CMY
  • Edges
  • HLS
  • HSV
  • L^*a^*b^*
  • L^*u^*v^*
  • Mathematical Morphology
  • Multi-spectral thresholding
  • Red eye detection
  • RGB
  • Skin detection
  • XYZ
  • YCrCb
  • YUV
• Complex transformations
• Computation time
  • Improving
• Connected Components
  • 4-adjacency
  • 8-adjacency
• Connectivity
• Contour Segmentation
  • A-algorithm
  • Border Detection
  • Boundary Chain Codes
  • Cost function
  • Directed Graphs
  • Efficient search
  • Heuristic Search
  • Line segments
• Corners. See Features
• Cost function
• Curved segments
•  
• Datasets
• Difference Images
• Directed Graphs
• Divide and conquer
•  
• Edges
  • Compass
  • Detection
  • First derivative
  • Gradient and Orientation
  • Hough Transform
  • Multiple Scales
  • Multispectral
  • Roberts
  • Second derivative
  • Thresholding
• Efficient search
• Exhaustive Search
•  
• Fβ measure
• Features
  • Aperture Problem
  • FAST
  • Harris
  • Minimum Eigenvalues
  • Moravec
  • SIFT
  • SURF
• First derivative ...