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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 ofExcellence for Document Analysis and Recognition (CEDAR).NABR is currently being used by IRS to read address blocks (hand-print as well as machine-print) on fifteen different tax forms. Although machine-print address reading was relatively straight-forward, 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 haid-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.

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