Improvements of a lexicon directed algorithm for recognition of unconstrained handwritten words

Abstract

Discusses improvements made to a lexicon directed algorithm for recognition of unconstrained handwritten words (cursive, discrete, or mixed) such as those encountered in mail pieces. The procedure consists of binarization, pre-segmentation, intermediate feature extraction, segmentation recognition, and post-processing. The segmentation recognition and the post-processing are repeated for all lexicon words while the binarization to the intermediate feature extraction are applied once for an input word. The result of performance evaluation using large handwritten address block database is described, and algorithm improvements are described and discussed, in order to achieve higher recognition accuracy and speed. As a result the performance for lexicons of size 10, 100, and 1000 are improved to 98.01%, 95.46%, and 91.49% respectively. The processing speed for each lexicon is improved to 2.0, 2.5, and 3.5 sec/word on a SUN SPARC station 2.