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A new algorithm for finding straight lines in images under a bounded error model is described. The algorithm is based on a hierarchical and adaptive subdivision of the space of line parameters. It measures errors in image space and thereby guarantees that no solution satisfying the given error bounds will be lost. The algorithm can find interpretations of all the lines in the image that satisfy the constraint that each image feature supports at most one line hypothesis. It can be extended to compute efficiently the maxima of the probabilistic Hough transform and the generalized Hough transform under a variety of statistical error models.
Type
research article
Authors
Breuel, Thomas M.
Publication date
1996
Published in
Volume
29
Issue
01
Start page
167
End page
178
Subjects
Peer reviewed
REVIEWED
EPFL units
Available on Infoscience
March 10, 2006
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