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Ternary contextualised histogram pattern for curve matching
- Source :
- IET Computer Vision. 8:642-649
- Publication Year :
- 2014
- Publisher :
- Institution of Engineering and Technology (IET), 2014.
-
Abstract
- This study presents a novel texture descriptor for curve matching, called ternary contextualised histogram pattern (TCHP), which is based on the intensity order histogram and local ternary homogeneity patterns. Local ternary homogeneity patterns are firstly adopted to represent the texture features of the curve's neighbourhood, which ensures the robustness and distinctiveness of the descriptor. The proposed TCHP is constructed by three steps: firstly, the curve support region without assigning a dominant orientation is determined and then partitioned into several ordinal bins according to the intensity permutation; then, ternary contextualised histogram (TCH) feature of each point is generated by computing the statistics of the predefined ternary homogeneity patterns; finally, TCHP is achieved by accumulating the TCHs of points in each order bin. Experiments show TCHP can effectively characterise the texture features of the curve's neighbourhood and performs robust to image rotation, viewpoint change and illumination change.
- Subjects :
- business.industry
Homogeneity (statistics)
Texture Descriptor
Feature extraction
Histogram matching
Pattern recognition
Image texture
Robustness (computer science)
Computer Science::Computer Vision and Pattern Recognition
Histogram
Computer Vision and Pattern Recognition
Artificial intelligence
Ternary operation
business
Software
Mathematics
Subjects
Details
- ISSN :
- 17519640
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IET Computer Vision
- Accession number :
- edsair.doi...........d7394dccacce1afeaeafe950c0fbee53