Robustness and Performance Evaluation of the Fuzzy Texture Spectrum encoding

In a previous work we introduced the fuzzy texture spectrum (FTS) as a texture spectrum (TS)-based method wherein, for capturing the ambiguity of texture definitions and texture features variability of real images, unlike the original method the concepts of equal, greater, and smaller grey-levels were considered as fuzzy sets. In this paper both methods are analyzed and compared for robustness evaluation. To compare the FTS and the TS for texture characterization an entropy measure and a similarity-discriminatory criterion are considered for performance and robustness evaluation. Moreover, to make the fuzzy texture spectrum rotations invariant, texture units are grouped into classes.