Reading handwritten digits: a ZIP code recognition system

Matan, Ofer; Baird, Henry S.; Bromley, Jane M.; Burges, Christopher J. C.; Denker, John S.; Jackel, Lawrence D.; Le Cun, Yann; Pednault, Edwin P. D.; Satterfield, William D.; Stenard, Charles E. and Thompson, Timothy J. (1992). Reading handwritten digits: a ZIP code recognition system. Computer, 25(7) pp. 59–63.

DOI: https://doi.org/10.1109/2.144441

Abstract

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.

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About

• Item ORO ID
• 35664
• Item Type
• Journal Item
• ISSN
• 0018-9162
• Keywords
• optical character recognition; handwriting recognition; neural networks
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 1992 AT&T
• Depositing User
• Jane M. Bromley