  In this paper, we generalize image (texture) statistical descriptors and
propose algorithms that improve their efficacy. Recently, a new method showed
how the popular Co-Occurrence Matrix (COM) can be modified into a fuzzy version
(FCOM) which is more effective and robust to noise. Here, we introduce new
fuzzy versions of two additional higher order statistical matrices: the Run
Length Matrix (RLM) and the Size Zone Matrix (SZM). We define the fuzzy zones
and propose an efficient algorithm to compute the descriptors. We demonstrate
the advantage of the proposed improvements over several state-of-the-art
methods on three tasks from quantitative cell biology: analyzing and
classifying Human Epithelial type 2 (HEp-2) cells using Indirect
Immunofluorescence protocol (IFF).
