Set of texture similarity measures
A. Carkacioglu, Fatoş T. Yarman-Vural · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1997
This paper deals with a class of textures which can be represented by Markov Random Fields (MRF) model. It is well known that by changing the MRF parameters, extremely wide group of textures can be generated. However, it is not easy to model and classify a textured image, since there is no clear-cut mathematical demition of texture. Although, many classification methods exist in the literature, the success of the results heavily depends on the data type. Thus, appropriate measures which give visually meaningful representation of texture are highly deskable.