Application Of Mathematical Morphology To Handwritten ZIP Code Recognition

Andrew M. Gillies; Paul D. Gader; Michael P. Whalen; Brian T. Mitchell

doi:10.1117/12.970049

1 November 1989 Application Of Mathematical Morphology To Handwritten ZIP Code Recognition

Andrew M. Gillies, Paul D. Gader, Michael P. Whalen, Brian T. Mitchell

Proceedings Volume 1199, Visual Communications and Image Processing IV; (1989) https://doi.org/10.1117/12.970049
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States

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.

Citation Download Citation

Andrew M. Gillies, Paul D. Gader, Michael P. Whalen, and Brian T. Mitchell "Application Of Mathematical Morphology To Handwritten ZIP Code Recognition", Proc. SPIE 1199, Visual Communications and Image Processing IV, (1 November 1989); https://doi.org/10.1117/12.970049

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