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Proceedings Paper

Using morphology in document image processing
Author(s): Vicente P. Concepcion; Matthew P. Grzech; Donald P. D'Amato
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Paper Abstract

To improve the readability, image compression, and optical character recognition (OCR) system performance for two-tone (binary) text image data, we investigated morphological methods of image processing. We found them to be fast and effective not only with noise text images but with relatively noise-free images as well. Using morphology, we improved text image readability as judged in a blind test, increased compression ratio using CCITT Group 4, and reduced OCR error (cluster) rates in a commercial omnifront scanner.

Paper Details

Date Published: 1 November 1991
PDF: 9 pages
Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); doi: 10.1117/12.50380
Show Author Affiliations
Vicente P. Concepcion, MITRE Corp. (United States)
Matthew P. Grzech, MITRE Corp. (United States)
Donald P. D'Amato, MITRE Corp. (United States)

Published in SPIE Proceedings Vol. 1606:
Visual Communications and Image Processing '91: Image Processing
Kou-Hu Tzou; Toshio Koga, Editor(s)

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