This correspondence presents a procedure to recognize handprinted alphanumeric characters written on a graphic tablet. After preprocessing, the input character is segmented into a polygon using a simple segmentation procedure. A feature vector is formed by the parameters which describe the segments of the polygon. Classification is done in two steps, the first one based on structural information extracted from the feature vector and the second based on statistical decision rule using parameters of the segments. A recursive learning procedure is introduced in the statistical classifier. The evaluation includes the measurement of recognition rates using several statistical classifiers, the validity test on the hypothesis concerning the distribution of feature vectors and the possibility of further simplification using principal axis analysis. Databases were created and used for the evaluation.