Computer Recognition of Totally Unconstrained Handwritten Zip Codes

This paper deals with the application of automatic sorting of envelopes with totally unconstrained handwritten numeric postal ZIP codes and presents a complete model (including preprocessing, feature extraction and classification modules) of a ZIP code reader/sorter. Different recognition methods, including statistical, structural and combined were developed and their performance on real-life ZIP code samples (8540 numerals) were measured. The statistical recognition method was used as a front-end recognizer and predictor of an unknown character. Based on edge classification, a new technique was implemented to define and extract the structural features. In the combined recognition method, unknown characters were identified either by the statistical or structural method. Its recognition reliability was found to be in the interval (96.29%, 95.94%) with substitution and rejection rates between (3.45%, 3.96%) and (2.36%, 7.01%) respectively.