Texture Classification Based on Random Threshold Vector Technique
نویسنده
چکیده
A new feature set derived from the fractal geometry, called the random threshold vector (RTV) is proposed for texture analysis. The RTV is computed for different run length entropy dimensions. The run length entropy dimensions are calculated based on different thresholds. To test the rotationally invariant feature, the run length entropies are calculated in different directions. The experimental results show that the RTV contains great discriminatory information needed for a successful classification.
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