1. An image clustering apparatus which changes sample class data representative of a selected sample class in response to reading of a new sample vector, the sample class data representative of the selected sample class including covariance matrix data and mean vector data, said apparatus changing the sample class data representative of the selected sample class to provide changed sample class data, said apparatus comprising: (a) a frame memory for storing an image represented by coded pixels, (b) reading means for reading out, from the frame memory, values associated with a pixel at a random horizontal and vertical position on the image, and generating a new sample vector that includes the read out values and horizontal and vertical position data corresponding to the pixel at the random position, (c) a memory means for holding a plurality of sets of sample class data representing sample classes, the sample class data including covariance matrix data and mean vector data derived from sample vectors, (d) likelihood calculating means for determining a likelihood that the new sample vector generated by said reading means is included in one of the plural sets of sample classes based on distances between the new sample vector and the sample classes, the distances each being a sum of: a distance value obtained by determining a difference vector indicative of the difference between the new sample vector and the class data mean vector, and normalizing the difference vector by the covariance matrix, and the magnitude of the covariance matrix, (e) maximum likelihood class selecting means for selecting a selected sample class from among the sample classes represented by the sample class data sets in said memory, the selected sample class having a minimum distance from the new sample vector, and (f) class data changing means for changing the mean vector data and the covariance matrix data of the class data representative of the selected sample class to provide the changed sample class data for said sample data holding memory, said changing means providing the changed sample class data such that the distance between the selected sample class and the new sample vector is reduced by using the difference vector.