Analysis and recognition of alphanumeric handprints by parts

An advanced hierarchical model has been proposed to produce a more effective character recognizer based on the probability of occurrence of the patterns. New definitions such as crucial parts, efficiency ratios, degree of confusion, similar character pairs, etc. have also been given to facilitate pattern analysis and character recognition. Using these definitions, computer algorithms have been developed to recognize the characters by parts, including halves, quarters, and sixths. The recognition rates have been analyzed and compared with those obtained from subjective experiments. Based on the results of both computer and human experiments, a detailed analysis of the crucial parts and the Canadian standard alphanumeric character set has been made revealing some interesting fundamental characteristics of these handprint models. The results should be useful for pattern analysis and recognition, character understanding, handwriting education, and human-computer communication