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Analysis of grey level weighted Hough transforms

Authors: Topor, James E.;

Analysis of grey level weighted Hough transforms

Abstract

The Hough transform is a well known method for detecting lines in digital imagery. The results of the transform may be termed accurate if the lines detected correspond to lines occurring in the digital image. The accuracy of the transform is affected by the manner in which the transform is designed. Factors which affect transform accuracy include parameter space resolution, image space quantizing errors, parameter space quantizing errors, and Hough space peak detection strategy. One way to improve the accuracy of the transform is to weight each pixel’s Hough space sinusoid by an amount which reflects the pixel’s grey level contribution to an image space feature. This paper examines the behavior of the transform when a grey level weighting scheme is used. The effects of image space quantizing errors, parameter space quantizing errors, and parameter space resolution on the accuracy of the transform are also investigated. A general Hough space peak detection filter is proposed, and experimental results showing the feasibility of both the grey level weighting scheme and peak detection filter are presented.

Master of Science

Country
United States
Related Organizations
Keywords

LD5655.V855 1990.T666, Image processing -- Digital techniques -- Mathematical models

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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