Monotonicity Analysis over Chains and Curves

Kucerovsky, Dan et Lemire, Daniel (2007). « Monotonicity Analysis over Chains and Curves », dans Curves and Surfaces 2006 (Sixth International Conference on Curves and Surfaces 2006, Avignon, France) pp. 180-190.

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Chains are vector-valued signals sampling a curve. They are important to motion signal processing and to many scientific applications including location sensors. We propose a novel measure of smoothness for chains curves by generalizing the scalar-valued concept of monotonicity. Monotonicity can be defined by the connectedness of the inverse image of balls. This definition is coordinate-invariant and can be computed efficiently over chains. Monotone curves can be discontinuous, but continuous monotone curves are differentiable a.e. Over chains, a simple sphere-preserving filter shown to never decrease the degree of monotonicity. It outperforms moving average filters over a synthetic data set. Applications include Time Series Segmentation, chain reconstruction from unordered data points, Optical Character Recognition, and Pattern Matching.

Type: Communication, article de congrès ou colloque
Mots-clés ou Sujets: Signal Processing, Monotonicity, Curves, Chains
Unité d'appartenance: Télé-université > UER Science et Technologie
Déposé par: Daniel Lemire
Date de dépôt: 16 juill. 2007
Dernière modification: 20 avr. 2009 14:28
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