Li, Chang-Tsun A conditional random field approach to unsupervised texture image segmentation. (English) Zbl 1204.94019 EURASIP J. Adv. Signal Process. 2010, Article ID 167942, 12 p. (2010). Summary: An unsupervised multiresolution conditional random field (CRF) approach to texture segmentation problems is introduced. This approach involves local and long-range information in the CRF neighbourhood to determine the classes of image blocks. Like most Markov random field (MRF) approaches, the proposed method treats the image as an array of random variables and attempts to assign an optimal class label to each. While most MRFs involve only local information extracted from a small neighbourhood, our method also allows a few long-range blocks to be involved in the labelling process. This alleviates the problem of assigning different class labels to disjoint regions of the same texture and oversegmentation due to the lack of long-range interaction among the neighbouring and distant blocks. The proposed method requires no a priori knowledge of the number and types of regions/textures. Cited in 1 Document MSC: 94A08 Image processing (compression, reconstruction, etc.) in information and communication theory PDFBibTeX XMLCite \textit{C.-T. Li}, EURASIP J. Adv. Signal Process. 2010, Article ID 167942, 12 p. (2010; Zbl 1204.94019) Full Text: DOI References: [1] doi:10.1109/TPAMI.2003.1159945 · Zbl 05110372 [2] doi:10.1109/TGRS.2003.809940 [3] doi:10.1109/36.843012 [4] doi:10.1109/34.946985 · Zbl 05111967 [5] doi:10.1109/83.847834 [6] doi:10.1109/TMM.2002.802023 [7] doi:10.1109/TGRS.2002.1010897 [8] doi:10.1109/TIP.2003.819311 · Zbl 05452984 [9] doi:10.1016/S0031-3203(01)00077-2 · Zbl 0997.68156 [10] doi:10.1109/83.847836 [11] doi:10.1016/S0031-3203(03)00131-6 · Zbl 1054.68159 [12] doi:10.1109/78.978390 · Zbl 1369.62252 [13] doi:10.1016/S0165-1684(00)00235-8 · Zbl 1080.62540 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.