Modular classification architecture for a pattern recognition application

A method and computer program product are disclosed for use in classifying an input pattern into one of a plurality of output classes. A plurality of modular classifiers each represent a set of at least one associated output class. The modular classifiers are capable of being trained separately from the system. The classifiers select one of the associated output classes as a classification result and compute an associated confidence value. This confidence value possesses common significance across the plurality of modular classifiers. A processing stage processes the confidence values from the plurality of modular classifiers. As a result of this processing, the processing stage selects an associated classification result.