Paper
7 March 1996 Reading handprinted addresses on IRS tax forms
Vemulapati Ramanaprasad, Yong-Chul Shin, Sargur N. Srihari
Author Affiliations +
Proceedings Volume 2660, Document Recognition III; (1996) https://doi.org/10.1117/12.234706
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
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.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Vemulapati Ramanaprasad, Yong-Chul Shin, and Sargur N. Srihari "Reading handprinted addresses on IRS tax forms", Proc. SPIE 2660, Document Recognition III, (7 March 1996); https://doi.org/10.1117/12.234706
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Cited by 1 scholarly publication and 1 patent.
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KEYWORDS
Image segmentation

Detection and tracking algorithms

Databases

Image processing algorithms and systems

Optical character recognition

Computing systems

Feature extraction

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