On indexing the periodicity of image textures

摘要

Texture analysis is an important part in many computer vision tasks, and periodicity (regularity) is one of the most important texture features. Based on the structural view of texture, we describe a new way to index the periodicity of image textures in this paper. We suggest that a texture's periodicity can be further divided into two aspects — the regularity of the placement of its texels and the similarity among the texels.For a given texture image, we first find its gradient field. Then we derive the autocorrelation function of the gradient field. Two placement directions are determined from the autocorrelation function. For each direction, we extract a profile of correlation values. From each profile, we derive a placement regularity value, a texel similarity value, and a general periodicity value. Lastly, we combine the corresponding index values obtained from the two placement directions, using the total gradient magnitude along the two directions as weights, to obtain a final set of indices that describe the periodicity of the texture. We have applied the approach to the entire 112 textures in the Brodatz album. The results show that the suggested indices effectively reflect the periodicity of the test images.