Three-dimensional connectivity index for texture recognition

Joao B. Florindo and Gabriel Landini and Odemir M. Bruno

PATTERN RECOGNITION LETTERS, 84():239-244, 2016

This work proposes a new method of texture analysis for grey-level images based on the distribution of connectivity indexes in local neighbourhoods. The connectivity index acts as a measure of homogeneity of textures and its distribution is computed at various local neighbourhood sizes. The resulting descriptors provide an efficient multiscale representation of connectivity at different scales. The method was tested in the classification of UIUC, Outex, and KTH-TIPS2b databases and outperformed several state-of-the-art approaches, including such as LBP, LBP+VAR, MR8, multifractals among others. (C) 2016 The Authors. Published by Elsevier B.V.