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An a Contrario decision method for shape element recognition
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DOI：10.1007/s11263-006-7546-0.png)
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Abstract
En 中文
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.
Keywords:
planar shape recognition
background model
number of false alarms
meaningful matches
level lines
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