Extraction of texture regions using region-based local correlation

We present an efficient algorithm using a region-based texture feature for the extraction of texture regions. The key idea of this algorithm is based on the fact that most of the variations of local correlation coefficients (LCCs) according to different orientations are clearly larger in texture regions than in shade regions. An object image is first segmented into homogenous regions. The variations of LCCs are next averaged in each segmented region. Based on the averaged variations of LCCs, each region is then classified as a texture or shade region. The threshold for classification is found automatically by an iterative threshold selection technique. In order to evaluate the performance of the proposed algorithm, we use six test images (Lena, Woman, Tank, Jet, Face and Tree) of 256x256 8-bit pixels. Experimental results show that the proposed feature suitably extracts the regions that appear visually as texture regions.