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Proceedings Paper

Reading handprinted addresses on IRS tax forms
Author(s): Vemulapati Ramanaprasad; Yong-Chul Shin; Sargur N. Srihari
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Paper Abstract

The hand-printed address recognition system described in this paper is a part of the Name and Address Block Reader (NABR) system developed by the Center of Excellence for Document Analysis and Recognition (CEDAR). NABR is currently being used by the IRS to read address blocks (hand-print as well as machine-print) on fifteen different tax forms. Although machine- print address reading was relatively straightforward, hand-print address recognition has posed some special challenges due to demands on processing speed (with an expected throughput of 8450 forms/hour) and recognition accuracy. We discuss various subsystems involved in hand- printed address recognition, including word segmentation, word recognition, digit segmentation, and digit recognition. We also describe control strategies used to make effective use of these subsystems to maximize recognition accuracy. We present system performance on 931 address blocks in recognizing various fields, such as city, state, ZIP Code, street number and name, and personal names.

Paper Details

Date Published: 7 March 1996
PDF: 8 pages
Proc. SPIE 2660, Document Recognition III, (7 March 1996); doi: 10.1117/12.234706
Show Author Affiliations
Vemulapati Ramanaprasad, SUNY/Buffalo (United States)
Yong-Chul Shin, SUNY/Buffalo (United States)
Sargur N. Srihari, SUNY/Buffalo (United States)


Published in SPIE Proceedings Vol. 2660:
Document Recognition III
Luc M. Vincent; Jonathan J. Hull, Editor(s)

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