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In this paper, we propose a new approach for color textured image segmentation. It is a two stage technique, where in the first stage, textural features using gray level co-occurrence matrix (GLCM) are computed for regions of interest (ROI)considered for each class. ROI act as ground truths for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Mean at inter pixel distance...
This paper examines hybrid genetic algorithm and Gaussian Markov random field model based method for unsupervised segmentation of multi-spectral textured images. It also evaluates the popular unsupervised image segmentation approaches, Genetic algorithm (GA) based clustering and simple Gaussian Markov random field (GMRF) model with the hybrid GA-GMRF method for high spatial resolution textured imagery...
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