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Ternary contextualised histogram pattern for curve matching

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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.
Institution of Engineering and Technology (IET)
Title: Ternary contextualised histogram pattern for curve matching
Description:
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.

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