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Proceedings Paper

Application Of Mathematical Morphology To Handwritten ZIP Code Recognition
Author(s): Andrew M. Gillies; Paul D. Gader; Michael P. Whalen; Brian T. Mitchell
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Paper Abstract

This paper describes applications of mathematical morphology to a system for recognizing handwritten ZIP Codes. It discusses morphological techniques used for preprocessing address block images, locating address block lines, splitting touching characters, and identifying handwritten numerals. These techniques combine mathematical morphology, hierarchical matching of object models to symbolic image representations, and a strategy of propagating multiple hypotheses. The various submodules of the system have been trained on over two thousand real address block images and tested on one thousand representative images. On the one thousand test images, the system correctly located 82.5 percent, correctly identified 45.6 percent, and incorrectly classified only 0.8% of the ZIP Codes. This system performance level could lead to a significant cost savings in mail piece sorting.

Paper Details

Date Published: 1 November 1989
PDF: 10 pages
Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); doi: 10.1117/12.970049
Show Author Affiliations
Andrew M. Gillies, Environmental Research Institute of Michigan (United States)
Paul D. Gader, Environmental Research Institute of Michigan (United States)
Michael P. Whalen, Environmental Research Institute of Michigan (United States)
Brian T. Mitchell, Environmental Research Institute of Michigan (United States)


Published in SPIE Proceedings Vol. 1199:
Visual Communications and Image Processing IV
William A. Pearlman, Editor(s)

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