A new approach to estimate lacunarity of texture images

A new approach is proposed based on gliding-box method to estimate the lacunaritys of texture images. The first approach uses a local threshold to enhance local features of the texture pattern, so that, lacunarity is computed in terms of the local binary patterns that exist in the image, a characteristic which is proven to be a very powerful texture feature. The second approach simply expands the concept of gliding a box over the gray level intensity axis of the texture. As this task is a very time consuming one, we present an algorithm to speed up this process. The results have been tested in a natural texture database, a real and complex problem because the high variability intra-class and great similarity between classes, and compared with traditional lacunarity approaches to show that this new method is computationally simple, convenient and accurate.

•In this study we propose two approaches to estimate the lacunarity of texture images.•The first approach uses a local threshold to enhance local features of the texture pattern.•Then, lacunarity is computed in terms of the local binary patterns of the image.•The second approach simply expands the concept of gliding a box over the gray level intensity axis.•As this task is a very time consuming one, we present an algorithm to speed up this process.