Texture Analysis By Bag-Of-Visual-Words Of Complex Networks

The texture is an important property of images, and it has been widely used to image characterization and classification. In this paper, we propose a novel method for texture analysis based on Complex Network theory. Basically, we show how to build networks from images, and then construct a vocabulary of visual words with Bag-Of-Visual-Words method. To build the vocabulary, the degree and strength of each vertex are extracted from the networks. The feature vector is composed by the visual word occurrence, unlike most traditional Complex Network works that extract global statistical measures of vertices. We show through experiments in four databases the effectiveness of our approach, which has overcome traditional texture analysis methods.