Texture analysis using volume-radius fractal dimension
This addresses texture analysis for computer vision applications, but appears incremental as it adapts an existing method to a new domain.
The paper tackles texture characterization in computer vision by proposing a novel approach based on complexity analysis, expanding the Mass-radius fractal dimension from shape analysis to 3D-space coordinates for texture, and demonstrates performance using images from the Brodatz album.
Texture plays an important role in computer vision. It is one of the most important visual attributes used in image analysis, once it provides information about pixel organization at different regions of the image. This paper presents a novel approach for texture characterization, based on complexity analysis. The proposed approach expands the idea of the Mass-radius fractal dimension, a method originally developed for shape analysis, to a set of coordinates in 3D-space that represents the texture under analysis in a signature able to characterize efficiently different texture classes in terms of complexity. An experiment using images from the Brodatz album illustrates the method performance.