An a contrario decision method for shape element recognition
Resumen:
Shape recognition is the field of computer vision which addresses the problem of finding out whethera query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simplysort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is thedecision 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 shapeamong 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
| 2005 | |
|
Planar shape recognition Background model Number of false alarms Meaningful matches Level lines PROCESAMIENTO de SEÑALES |
|
| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/21194 | |
| Acceso abierto |
| Sumario: | Shape recognition is the field of computer vision which addresses the problem of finding out whethera query shape lies or not in a shape database, up to a certain invariance. Most shape recognition methods simplysort shapes from the database along some (dis-)similarity measure to the query shape. Their main weakness is thedecision 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 shapeamong 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 |
|---|
