1. A pattern recognition process, comprising the steps of, starting from an input pattern: a) normalization of the input pattern into a normalized pattern of predetermined size; b) generation of a reliable pattern from the normalized pattern by using at least one morphological operator; c) calculation of a distance between the reliable pattern and selected templates which are selected from a template library by means of a decision tree, wherein each template belongs to a class; d) said decision tree comprising a plurality of nodes leading to a plurality of terminal nodes, each node containing a list of reliable black pixels and reliable white pixels and each terminal node forming one of said selected templates; e) said distance calculation comprising calculating a local distance at each node by comparing reliable pixels of said reliable pattern with said reliable black and white pixels in said list; and incrementing at each node a running distance by the local distance, such that the running distance at the terminal node is said distance between the reliable pattern and the selected template; and f) classification of the reliable pattern into at least one of the classes of the selected templates by means of at least one non-parametric classification method, which uses said classes of the selected templates and said calculated distances as inputs and outputs identified classes along with confidence levels.