Ribas, Lucas C.
Sa Junior, Jarbas Joaci de Mesquita
Scabini, Leonardo F. S.
Bruno, Odemir M.
Total Authors: 4
 Univ Sao Paulo, Inst Math & Comp Sci, Ave Trabalhador Sao Carlense, Sao Carlos 13566590, SP - Brazil
 Univ Sao Paulo, Sao Carlos Inst Phys, POB 369, Sao Carlos 13560970, SP - Brazil
 Univ Fed Ceara, Curso Engn Computacao, Programa Posgrad Engn Eletr & Computacao, Campus Sobral, Rua Coronel Estanislau Frota 563, Sobral 62010560, CE - Brazil
Total Affiliations: 3
Web of Science Citations:
This paper presents a high discriminative texture analysis method based on the fusion of complex networks and randomized neural networks. In this approach, the input image is modeled as a complex network and its topological properties as well as the image pixels are used to train randomized neural networks to create a signature that represents the deep characteristics of the texture. The results obtained surpassed the accuracy of many methods available in the literature. This performance demonstrates that our proposed approach opens a promising source of research, which consists of exploring the synergy of neural networks and complex networks in the texture analysis field. (C) 2019 Published by Elsevier Ltd. (AU)