Jacques-Olivier Lachaud
Jacques-Olivier Lachaud
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noise detection
Meaningful Scales Detection: an Unsupervised Noise Detection Algorithm for Digital Contours
This work presents an algorithm which permits to detect locally on digital contour what is the amount of noise estimated from a given …
B. Kerautret
,
Jacques-Olivier Lachaud
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Digital Shape Analysis with Maximal Segments
We show in this paper how a digital shape can be efficiently analyzed through the maximal segments defined along its digital contour. …
Jacques-Olivier Lachaud
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Meaningful Scales Detection along Digital Contours for Unsupervised Local Noise Estimation
The automatic detection of noisy or damaged parts along digital contours is a difficult problem since it is hard to distinguish between …
B. Kerautret
,
Jacques-Olivier Lachaud
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DOI
IPOL demo
Meaningful Thickness Detection On Polygonal Curve
The notion of meaningful scale was recently introduced to detect the amount of noise present along a digital contour (Kerautret and …
B. Kerautret
,
Jacques-Olivier Lachaud
,
M. Said
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Unsupervised, Fast and Precise Recognition of Digital Arcs in Noisy Images
In image processing and pattern recognition, the accuracy of most algorithms is dependent on a good parameterization, generally a …
T. P. Nguyen
,
B. Kerautret
,
I. Debled-Rennesson
,
Jacques-Olivier Lachaud
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Multiscale Analysis of Discrete Contours for Unsupervised Noise Detection
Blurred segments [2] were introduced in discrete geometry to address possible noise along discrete contours. The noise is not really …
B. Kerautret
,
Jacques-Olivier Lachaud
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