Texture segmentation using zero crossings information

Image texture can be defined as a local two-dimensional random field. The Gauss Markov random field (GMRF) and grey level co-occurrence (GLC) algorithms compute features from models of this random field. However, the GMRF and GLC algorithms capture only second-order interactions between pixels. We describe an algorithm which models texture as a local two-dimensional random field and captures high-order interactions.

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