ぱらぱらめくる『Momemnts and Moment Invariants in Pattern Recognition』

Moments and Moment Invariants in Pattern Recognition

• 大目次
  • 1 Introduction to moments
  • 2 Moment invariants to translation, rotation and scaling
  • 3 Affine moment invariants
  • 4 Implicit invariants to elastic transformations
  • 5 Invariants to convolution
  • 6 Orthogonal moments
  • 7 Algorithms for moment computation
  • 8 Applications
• 中目次
  • 1 Introduction to moments
    • Motivation
    • What are invariants?
    • What are moments?
    • Outline of the book
  • 2 Moment invariants to translation, rotation and scaling
    • Introduction
    • Rotation invariants from complex moments
    • Pseudoinvariants
    • Combined invariants to TRS and constract changes
    • Rotation invariants for recognition of symmetric objects
    • Rotation invariants via image normalization
    • Invariants to nonuniform scaling
    • TRS invariants in 3D
    • Conclusion
  • 3 Affine moment invariants
    • Introduction
    • AMIs derived from the Funcamental theorem
    • AMIs generated by graphs
    • AMIs via image normalization
    • Derivation of the AMIs from the Cayley-Aronhold equation
    • Numerical experiments
    • Affine invariants of color images
    • Generalization of three dimensions
    • Conclusion
  • 4 Implicit invariants to elastic transformations
    • Introduction
    • General moments under a polynomial transform
    • Explicit and implicit invariants
    • Implicit invariants as a minimization task
    • Numerical experiments
    • Conclusion
  • 5 Invariants to convolution
    • Introduction
    • Blur invariants for centrosymmetric PSFs
    • Blur invariants for N-fold symmetric PSFs
    • Combined invariants
    • Conclusion
  • 6 Orthogonal moments
    • Introduction
    • Moments orthogonal on a rectangle
    • Moments orthogonal on a disk
    • Object recognition by ZMs
    • Image reconstruction from moments
    • Three-dimensional OG moments
    • Conclustion
  • 7 Algorithms for moment computation
    • Introduction
    • Moments in a discrete domain
    • Geometric moments of binary images
    • Geometric moments of graylevel images
    • Efficient methods for calculating OG moments
    • Generalization to n dimensions
    • Conclusion
  • 8 Applications
    • Introduction
    • Object representation and recognition
    • Image registration
    • Robot navigation
    • Image retrieval
    • Watermarking
    • Medical imaging
    • Forensic applications
    • Miscellaneous applications
    • Conclusion