Multi-level 3-D rotational invariant classification

A two-level 3D rotational invariant classification is developed based on fractional differencing model. In first level, classification has been done with a fractal scale, and in second level, textures have been classified further in detail with the additional frequency parameters. Because of the properties of the fractal scale and multi-level procedure, the proposed 3D rotational invariant classification scheme reduces the processing time and gives enough accuracy of the classification simultaneously. As a result of a series of experiments involving the differently oriented samples of natural textures, it is concluded that these combined features make possible for this multi-level classification method to have a strong class separability power for arbitrary oriented 3D texture patterns