29 December 2000 Extraction of texture regions using region-based local correlation
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Abstract
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 homogeneous 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 256 X 256 8-bit pixels. Experimental results show that the proposed feature suitably extracts the regions that appear visually as texture regions.
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Sang Yong Seo, Sang Yong Seo, Chae Whan Lim, Chae Whan Lim, Young Deok Chun, Young Deok Chun, Nam Chul Kim, Nam Chul Kim, } "Extraction of texture regions using region-based local correlation", Proc. SPIE 4310, Visual Communications and Image Processing 2001, (29 December 2000); doi: 10.1117/12.411849; https://doi.org/10.1117/12.411849
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