Department of Pattern RecognitionDepartment of Pattern Recognition

  • old web
  • ÚTIA
  • AV ČR
  • Log in
  • Home
  • Seminars
  • People
  • Demos
  • Lectures / Tutorials
  • Resources / Software
  • Publications
  • Topics (57)
    • 3D Data Modelling (13)
      • 3D Objects Measurement (2)
      • Bidirectional Texture Function Modelling (7)
        • BTF Measurement (1)
      • Virtual Reality (3)
    • Benchmarking (2)
    • Classification (4)
    • Content Based Image Retrieval (CBIR) (1)
    • Dynamic Textures (3)
      • Colour Dynamic Textures Synthesis (1)
      • Dynamic Texture Modelling (1)
    • Illumination and Rotation Invariance (1)
    • Image & Video Analysis / Processing (11)
      • Image Retrieval (2)
      • Image Segmentation (5)
      • Image Sequence Restoration (2)
      • Remote Sensing (1)
      • Texture Synthesis (1)
    • Machine Learning (11)
      • Mixture Models (11)
        • Application of Distribution Mixtures (3)
        • Feature Selection (4)
        • Mammogram Enhancement (2)
    • Mathematical Image Modelling (1)
    • Medical Image Recognition (1)
    • Pattern Recognition (1)
    • Probabilistic Expert Systems (1)
    • Probabilistic Neural Networks (2)
    • Probabilistic Texture Synthesis (5)
    • Sampling Based Texture Synthesis (2)
    • Spatial Data Modelling (1)
    • Statistical Pattern Recognition (8)
      • Document Classification (1)
    • Textural Features (1)
    • Texture Editing (1)
    • Texture Segmentation (2)
    • Visual quality measures (1)
Home

Rotation invariance

Colour and rotation invariant textural features based on Markov random fields

Vácha, P., M. Haindl, and T. Suk, "Colour and rotation invariant textural features based on Markov random fields", Pattern Recognition Letters, vol. 32, no. 6, pp. 771 - 779, 2011.
  • Rotation invariance
  • BibTex
  • Google Scholar
Syndicate content