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Proceedings Paper

Document Image Binarization: Evaluation Of Algorithms
Author(s): Paul W. Palumbo; Puducode Swaminathan; Sargur N. Srihari
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Paper Abstract

The extraction of a binary image from a gray level image is a common image processing operation particularly for document image analysis and optical character recognition. Various methods for this task are described in the literature including global and adaptive binarization. This paper evaluates three adaptive binarization techniques viz., a contrast measure approach, a weighted running average approach and a second derivative approach, and compares them to global binarization methods. Experiments with noisy document (postal letter mail) images lead to the following conclusions. Image contrast binarization often yields nearly the same results as the edge operator, with considerably less computation and is less sensitive to parameter settings. In addition, the edge operator is more sensitive to image resolution than the contrast operator. The weighted running-average approach is highly sensitive to the parameters involved in the calculation of the average but produces a quick binarization.

Paper Details

Date Published: 10 December 1986
PDF: 8 pages
Proc. SPIE 0697, Applications of Digital Image Processing IX, (10 December 1986); doi: 10.1117/12.976229
Show Author Affiliations
Paul W. Palumbo, State University of New York (United States)
Puducode Swaminathan, State University of New York (United States)
Sargur N. Srihari, State University of New York (United States)

Published in SPIE Proceedings Vol. 0697:
Applications of Digital Image Processing IX
Andrew G. Tescher, Editor(s)

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