In content-based image retrieval a major problem is the presence of noisy shapes. It is well known that persistent Betti numbers area shape descriptor that admits a dissimilarity distance, the matchingdistance, stable under continuous shape deformations. In this paper wefocus on the problem of dealing with noise that changes the topologyof the studied objects. We present a general method to turn persistentBetti numbers into stable descriptors also in the presence of topologicalchanges. Retrieval tests on the Kimia-99 database show the effectivenessof the method.
Persistent Betti Numbers for a Noise Tolerant Shape-Based Approach to Image Retrieval / P., Frosini; Landi, Claudia. - STAMPA. - 6854:1(2011), pp. 294-301. (Intervento presentato al convegno 14th International Conference on Computer Analysis of Images and Patterns, CAIP 2011 tenutosi a Seville, esp nel 29-31 agosto 2011) [10.1007/978-3-642-23672-3_36].
Persistent Betti Numbers for a Noise Tolerant Shape-Based Approach to Image Retrieval
LANDI, Claudia
2011
Abstract
In content-based image retrieval a major problem is the presence of noisy shapes. It is well known that persistent Betti numbers area shape descriptor that admits a dissimilarity distance, the matchingdistance, stable under continuous shape deformations. In this paper wefocus on the problem of dealing with noise that changes the topologyof the studied objects. We present a general method to turn persistentBetti numbers into stable descriptors also in the presence of topologicalchanges. Retrieval tests on the Kimia-99 database show the effectivenessof the method.File | Dimensione | Formato | |
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