Summary: Unsupervised Detection and Localization of Structural Textures Using Projection Profiles
Ismet Zeki Yalniz1
, Selim Aksoy
Department of Computer Engineering, Bilkent University, Ankara, 06800, Turkey
The main goal of existing approaches for structural texture analysis has been the identification of repeating texture primitives and
their placement patterns in images containing a single type of texture. We describe a novel unsupervised method for simultaneous
detection and localization of multiple structural texture areas along with estimates of their orientations and scales in real images.
First, multi-scale isotropic filters are used to enhance the potential texton locations. Then, regularity of the textons is quantified in
terms of the periodicity of projection profiles of filter responses within sliding windows at multiple orientations. Next, a regularity
index is computed for each pixel as the maximum regularity score together with its orientation and scale. Finally, thresholding of
this regularity index produces accurate localization of structural textures in images containing different kinds of textures as well as
non-textured areas. Experiments using three different data sets show the effectiveness of the proposed method in complex scenes.
Key words: Structural texture analysis, texture periodicity, textons, regularity detection, wavelet analysis
Texture has been acknowledged to be an important visual
feature used for classifying and recognizing objects and scenes.
It can be characterized by textural primitives as unit elements
and neighborhoods in which the organization and relationships
between the properties of these primitives are defined. Haral-