Fast texel size estimation in visual texture using homogeneity cues

In this paper, we address the texel size estimation of periodic and near-periodic texture images. Such a problem has shown to be difficult when corrupted and distorted patterns are analyzed, and the accuracy and robustness are significant. In this study, we propose the use of the homogeneity cues computed using a difference histogram. Varying the displacement vector that relates two pixels and localizing the resultant homogeneity maximum value, we can automatically determine the texel size. Experiments were carried out in order to evaluate the performance of our method. Results on artificially distorted images and on natural near-periodic images, show that the proposed approach is more accurate and robust than other state-of-the-art methods. Furthermore, the computation of homogeneity cues is not intricate nor time-consuming, and hence, it can be considered for practical applications where computation time is critical.

► Homogeneity cues are used to detect the texel size in visual textures. ► Homogeneity is a function of a displacement vector between pairs of pixels. ► When the displacement vector matches the texel size, homogeneity reaches a maximum. ► The method is robust to projection deformations, blur distortions and noise corruption. ► The approach is fast enough to be considered for practical applications.