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Proceedings Paper

Document image restoration using binary morphological filters
Author(s): Jisheng Liang; Robert M. Haralick; Ihsin T. Phillips
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Paper Abstract

This paper discusses a method for binary morphological filter design to restore document images degraded by subtractive or additive noise, given a constraint on the size of filters. With a filter size restriction (for example 3 by 3), each pixel in output image depends only on its (3 by 3) neighborhood of input image. Therefore, we can construct a look-up table between input and output. Each output image pixel is determined by this table. So the filter design becomes the search for the optimal look-up table. By considering the degradation condition of the input image, we provide a methodology for knowledge based look-up table design, to achieve computational tractability. The methodology can be applied iteratively so that the final output image is the input image after being transformed through successive 3 by 3 operations. An experimental protocol is developed for restoring degraded document images, and improving the corresponding recognition accuracy rates of an OCR algorithm. We present results for a set of real images which are manually ground-truthed. The performance of each filter is evaluated by the OCR accuracy.

Paper Details

Date Published: 7 March 1996
PDF: 12 pages
Proc. SPIE 2660, Document Recognition III, (7 March 1996); doi: 10.1117/12.234709
Show Author Affiliations
Jisheng Liang, Univ. of Washington (United States)
Robert M. Haralick, Univ. of Washington (United States)
Ihsin T. Phillips, Seattle Univ. (United States)

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

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