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Proceedings Paper

Estimation of linear stroke parameters using iterative total least squares methods
Author(s): Jan A. Van Mieghem; Hadar I. Avi-Itzhak; Roger D. Melen
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Paper Abstract

In this paper we present an algorithm to enhance the accuracy of the estimation of the parameters of linear stroke segments in a two-dimensional printed character image. The algorithm achieves high accuracy in comparatively less computational time than most traditional methods. It is invariant under rotation and translation and no a priori information about the image is required. The Iterative Total Least Squares (ITLS) method begins at a randomly assigned initial approximation of the line parameters. A rectangular window is centered using the current stroke approximation, and a new line estimate is generated by making a total least squares fit through the pixels contained within the window. This is then repeated until convergence is reached. Adaptive adjustments of the window size and choice of profile can further improve the obtained accuracy. In addition, a `fast'' ITLS method has been developed.

Paper Details

Date Published: 1 August 1992
PDF: 6 pages
Proc. SPIE 1661, Machine Vision Applications in Character Recognition and Industrial Inspection, (1 August 1992); doi: 10.1117/12.130277
Show Author Affiliations
Jan A. Van Mieghem, Canon Research Ctr. America, Inc. (United States)
Hadar I. Avi-Itzhak, Canon Research Ctr. America, Inc. (United States)
Roger D. Melen, Canon Research Ctr. America, Inc. (United States)


Published in SPIE Proceedings Vol. 1661:
Machine Vision Applications in Character Recognition and Industrial Inspection
Donald P. D'Amato; Wolf-Ekkehard Blanz; Byron E. Dom; Sargur N. Srihari, Editor(s)

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