Shape complexity based on mutual information
dc.contributor.author
dc.date.accessioned
2010-10-01T11:21:42Z
dc.date.available
2010-08-10T09:05:28Z
2010-10-01T11:21:42Z
dc.date.issued
2005
dc.identifier.citation
Rigau, J., Feixas, M., i Sbert, M. (2005). Shape complexity based on mutual information. International Conference Shape Modeling and Applications : 2005, 355 - 360. Recuperat 1 octubre 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1563243
dc.identifier.isbn
0-7695-2379-X
dc.identifier.uri
dc.description.abstract
Shape complexity has recently received attention from different fields, such as computer vision and psychology. In this paper, integral geometry and information theory tools are applied to quantify the shape complexity from two different perspectives: from the inside of the object, we evaluate its degree of structure or correlation between its surfaces (inner complexity), and from the outside, we compute its degree of interaction with the circumscribing sphere (outer complexity). Our shape complexity measures are based on the following two facts: uniformly distributed global lines crossing an object define a continuous information channel and the continuous mutual information of this channel is independent of the object discretisation and invariant to translations, rotations, and changes of scale. The measures introduced in this paper can be potentially used as shape descriptors for object recognition, image retrieval, object localisation, tumour analysis, and protein docking, among others
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
IEEE
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Reproducció digital del document publicat a: http://dx.doi.org/10.1109/SMI.2005.42
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© International Conference Shape Modeling and Applications, 2005, p. 355-360
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Articles publicats (D-IMA)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Shape complexity based on mutual information
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.identifier.doi