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Filtering of meaningful features of fuzzy hough transform

Authors: E. V. Pugin; A. L. Zhiznyakov;

Filtering of meaningful features of fuzzy hough transform

Abstract

Hough Transform and its modifications are used to find straight lines or simple geometric figures on images. But this cannot prevent us from detecting not interesting objects completely. The paper introduces a novel method of filtering or fusion of straight lines after performing Fuzzy Hough Transform. The analysis of mutual arrangements of lines on the image is given. Possible distances between lines are described. A novel distance based on intersection of lines and borders of an image is introduced. Methods of line grouping and fusion based on some criteria selection are shown. Testing on real and test images of pipes was performed. Developed methods shows good robustness (less than 5% of errors) and performance (0.2–0.4 s. per image).

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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!
1
Average
Average
Average
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