HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

Meaningful Scales Detection along Digital Contours for Unsupervised Local Noise Estimation

Abstract : The automatic detection of noisy or damaged parts along digital contours is a difficult problem since it is hard to distinguish between information and perturbation without further a priori hypotheses. However, solving this issue has a great impact on numerous applications, including image segmentation, geometric estimators, contour reconstruction, shape matching, or image edition. We propose an original strategy to detect what the relevant scales are at which each point of the digital contours should be considered. It relies on theoretical results of asymptotic discrete geometry. A direct consequence is the automatic detection of the noisy or damaged parts of the contour, together with its quantitative evaluation (or noise level). Apart from a given maximal observation scale, the proposed approach does not require any parameter tuning and is easy to implement. We demonstrate its effectiveness on several datasets. We present different direct applications of this local measure to contour smoothing and geometric estimators whose algorithms initially required a noise/scale parameter to tune: They show the pertinence of the proposed measure for digital shape analysis and reconstruction.
Document type :
Journal articles
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-00780689
Contributor : Bertrand Kerautret Connect in order to contact the contributor
Submitted on : Thursday, January 24, 2013 - 4:02:39 PM
Last modification on : Saturday, October 16, 2021 - 11:26:08 AM

Identifiers

Citation

Bertrand Kerautret, Jacques-Olivier Lachaud. Meaningful Scales Detection along Digital Contours for Unsupervised Local Noise Estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2012, 34 (12), pp.2379--2392. ⟨10.1109/TPAMI.2012.38⟩. ⟨hal-00780689⟩

Share

Metrics

Record views

149