The texture gives useful information for dividing a picture into segments, and the analysis by using this information is called a texture analysis. Here two fundamental problems will be encountered; namely, 1) how this texture is characterized or modeled, and 2) how the demands on the class separability and on the segmentation accuracy are compromised. For the first problem this paper gives a mathematical model of texture to descrive the 1st order density function of pixcell grayness and the

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... ocorrelation function. By synthesizing a texture sample following this model, the model fitness is investigated visually. For the second problem is given a classification method which uses minimum pixcells for classification through the above mentioned mathematical model under the condition that the class separability must be greater than a given value. Simulation of this classification method resulted to provide sufficient class separability without much loss of the segmentation accuracy.