Meaningful Scales Detection: an Unsupervised Noise Detection Algorithm for Digital Contours

Abstract
This work presents an algorithm which permits to detect locally on digital contour what is the amount of noise estimated from a given maximal scale. The method is based on the asymptotic properties of the length of the maximal segment primitive.
Type
Publication
IPOL Journal, 4: 98-115, 2014
Digital Geometry
2D
Digital Straight Segment
Asymptotic Digital Geoemtry
Noise Detection
Digital Contour

Authors
Professor of Computer Science
My research interests include digital geometry, geometry processing, image analysis, variational models and discrete calculus.