Classification of natural textures by means of two-dimensional orthogonal masks

Abstract
An approach to texture classification in which each local neighborhood is transformed reversibly into a minimal set of uncorrelated features is described. These features are found to represent local average, as well as first- and second-order derivative information of the texture. Comparison to other techniques of similar complexity, using identical classification procedures, shows the superiority of the proposed approach. Moreover, this approach leads directly to a real-time parallel implementation.<>

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