O3S-MTP: Oriented star sampling structure based multi-scale ternary pattern for texture classification

Highlights：

• Based on the dominating set and graph theory, we introduce a new orientation graphic structure, which will contribute to solve the non-orientation problem of LGS (local graph structure) based methods (LGS, ELGS, SLGS, etc.).

• We propose a new prominent image representation approach referred to as oriented star sampling structure based multi-scale ternary pattern (O3S-MTP) for texture classification.

• Instead of binary coding, multi-level coding in different orientations is used as well.

• Extensive evaluation on twelve challenging representative texture datasets is performed, showing that the proposed descriptor demonstrates superior performance to a large number of old and recent state-of-the-art LBP variants and non-LBP methods.

• The optimized user-specified parameters for the parametric methods on each dataset is generated to represent and demonstrate the effectiveness and the stability of the proposed O3S-MTP operator.