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Reading Handwritten Digits: A ZIP Code Recognition System
July 1992 (vol. 25 no. 7)
pp. 59-63

A neural network algorithm-based system that reads handwritten ZIP codes appearing on real US mail is described. The system uses a recognition-based segmenter, that is a hybrid of connected-components analysis (CCA), vertical cuts, and a neural network recognizer. Connected components that are single digits are handled by CCA. CCs that are combined or dissected digits are handled by the vertical-cut segmenter. The four main stages of processing are preprocessing, in which noise is removed and the digits are deslanted, CCA segmentation and recognition, vertical-cut-point estimation and segmentation, and directly lookup. The system was trained and tested on approximately 10000 images, five- and nine-digit ZIP code fields taken from real mail.

Ofer Matan, Henry S. Baird, Jane Bromley, Christopher J.C. Burges, John S. Denker, Lawrence D. Jackel, Yann Le Cun, Edwin P.D. Pednault, William D. Satterfield, Charles E. Stenard, Timothy J. Thompson, "Reading Handwritten Digits: A ZIP Code Recognition System," Computer, vol. 25, no. 7, pp. 59-63, July 1992, doi:10.1109/2.144441
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