Shape recognition via an a contrario model for size functions

Authors:
Andrea Cerri;Daniela Giorgi;Pablo Musé;Frédéric Sur;Federico Tomassini
Affiliations:
Dipartimento di Matematica, Università di Bologna, Bologna, Italy;Dipartimento di Matematica, Università di Bologna, Bologna, Italy;Centre de Mathématiques et de Leurs Applications, École Normale Supérieure de Cachan, Cachan, France;Loria & INPL, Loria, Vandoeuvre-lès-Nancy, France;Dipartimento di Matematica, Università di Bologna, Bologna, Italy
Venue:
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Year:
2006

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Abstract

Shape recognition methods are often based on feature comparison. When features are of different natures, combining the value of distances or (dis-)similarity measures is not easy since each feature has its own amount of variability. Statistical models are therefore needed. This article proposes a statistical method, namely an a contrario method, to merge features derived from several families of size functions. This merging is usually achieved through a touchy normalizing of the distances. The proposed model consists in building a probability measure. It leads to a global shape recognition method dedicated to perceptual similarities.