Abstract: A method of classification for a content-based digital-image, including: defining a set of low-level features describing the semantic content of the image, the features being quantities obtainable from the image by means of logico-mathematical expressions that are known beforehand, and the choice of said features depending upon the image classes used for the classification; indexing an image to be classified, with the purpose of extracting therefrom a feature vector, the components of which consist of the values assumed, in the image, by said low-level features; splitting the feature space defined by the low-level features into a plurality of classification regions, to each one of the regions there being associated a respective image class, and each classification region being the locus of the points of the feature space defined by a finite set of conditions laid on at least one component of the feature vector; associating the feature vector to the feature space; identifying, among the classification regions,

Abstract: A hardware accelerator for a coding system for pictures includes an array of lines and columns of pixels, and calculates the variance of macroblocks of a digitized video image for a real-time coding of the current image together with the preceding and successive images, according to the MPEG-2 video algorithm. The architecture minimizes the silicon area needed for implementing the hardware accelerator for a cost-effective reduction on the CPU of the coding system. The use of a plurality of distinct filter/demultiplexers of known architectures is eliminated by conveying the incoming pixels to the respective input lines of distinct variance calculation paths by the use of a simple counter.