Rotation-invariant texture recognition

Montoya Zegarra, Javier; Paulo Papa, Joao; Leite, Neucimar; da Silva Torres, Ricardo; Falcao, Alexandre

Rotation-invariant texture recognition

Date

2007

Authors

Montoya Zegarra, Javier

Paulo Papa, Joao

Leite, Neucimar

da Silva Torres, Ricardo

Falcao, Alexandre

Publisher

Scopus

Abstract

This paper proposes a new texture classification system, which is distinguished by: (1) a new rotation-invariant image descriptor based on Steerable Pyramid Decomposition, and (2) by a novel multi-class recognition method based on Optimum Path Forest. By combining the discriminating power of our image descriptor and classifier, our system uses small size feature vectors to characterize texture images without compromising overall classification rates. State-of-the-art recognition results are further presented on the Brodatz dataset. High classification rates demonstrate the superiority of the proposed method. © Springer-Verlag Berlin Heidelberg 2007.