caa a22 4500 467914346 CHVBK 20180406152857.0 cr unu---uuuuu 170328e20060901xx s 000 0 eng 10.1007/s11263-006-7546-0 doi (NATIONALLICENCE)springer-10.1007/s11263-006-7546-0 An A Contrario Decision Method for Shape Element Recognition [Elektronische Daten] [Pablo Musé, Frédéric Sur, Frédéric Cao, Yann Gousseau, Jean-Michel Morel] Shape recognition is the field of computer vision which addresses the problem of finding out whether a query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simply sort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is the decision stage, which should aim at giving a clear-cut answer to the question: "do these two shapes look alike?” In this article, the proposed solution consists in bounding the number of false correspondences of the query shape among the database shapes, ensuring that the obtained matches are not likely to occur "by chance”. As an application, one can decide with a parameterless method whether any two digital images share some shapes or not. Springer Science + Business Media, LLC, 2006 planar shape recognition nationallicence background model nationallicence number of false alarms nationallicence meaningful matches nationallicence level lines nationallicence Musé Pablo CMLA, ENS de Cachan, 61 avenue du Président Wilson, 94235, Cachan Cedex, France aut Sur Frédéric CMLA, ENS de Cachan, 61 avenue du Président Wilson, 94235, Cachan Cedex, France aut Cao Frédéric IRISA, INRIA Rennes, Campus Universitaire de Beaulieu, 35042, Rennes Cedex, France aut Gousseau Yann Signal and Image Processing Department, CNRS UMR 5141, Télécom Paris, 46 rue Barrault, 75643, Paris Cedex 13, France aut Morel Jean-Michel CMLA, ENS de Cachan, 61 avenue du Président Wilson, 94235, Cachan Cedex, France aut International Journal of Computer Vision Kluwer Academic Publishers 69/3(2006-09-01), 295-315 0920-5691 69:3<295 2006 69 11263 https://doi.org/10.1007/s11263-006-7546-0 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11263-006-7546-0 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Musé Pablo CMLA, ENS de Cachan, 61 avenue du Président Wilson, 94235, Cachan Cedex, France aut NATIONALLICENCE 700 1- Sur Frédéric CMLA, ENS de Cachan, 61 avenue du Président Wilson, 94235, Cachan Cedex, France aut NATIONALLICENCE 700 1- Cao Frédéric IRISA, INRIA Rennes, Campus Universitaire de Beaulieu, 35042, Rennes Cedex, France aut NATIONALLICENCE 700 1- Gousseau Yann Signal and Image Processing Department, CNRS UMR 5141, Télécom Paris, 46 rue Barrault, 75643, Paris Cedex 13, France aut NATIONALLICENCE 700 1- Morel Jean-Michel CMLA, ENS de Cachan, 61 avenue du Président Wilson, 94235, Cachan Cedex, France aut NATIONALLICENCE 773 0- International Journal of Computer Vision Kluwer Academic Publishers 69/3(2006-09-01), 295-315 0920-5691 69:3<295 2006 69 11263 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer