IEEE Transactions on Pattern Analysis and Machine Intelligence
An Automated Defect Management for Document Images
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
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The reading of names and addresses is one of the most complex tasks in automated forms processing. The paper describes an integrated real time system to read names and addresses on tax forms of the Internal Revenue Service of the United States. The Name and Address Block Reader (NABR) system accepts both machine printed and hand printed address block images as input. The application software has two major steps: document analysis (connected component analysis, address block extraction, label detection, hand print/machine print discrimination); and document recognition. Document recognition has two non identical streams for machine print and hand print; key steps are: address parsing, character recognition, word recognition and postal database lookup (ZIP+4 and City-State-ZIP files). Real time throughput (8,500 forms per hour) is achieved by employing a loosely coupled multiprocessing architecture. The functional architecture, software design, system architecture and hardware implementation are described. Performance evaluation on machine printed and handwritten addresses are presented.