Shape complexity based on mutual information
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| Názov: | Shape complexity based on mutual information |
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| Autori: | Rigau Vilalta, Jaume, Feixas Feixas, Miquel, Sbert, Mateu |
| Zdroj: | © International Conference Shape Modeling and Applications, 2005, p. 355-360 Articles publicats (D-IMA) DUGiDocs – Universitat de Girona instname Recercat. Dipósit de la Recerca de Catalunya |
| Informácie o vydavateľovi: | IEEE Comput. Soc, 2006. |
| Rok vydania: | 2006 |
| Predmety: | Computational complexity, Geometria integral, Percepció de les formes, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, Integral geometry, Complexitat computacional, Geometria computacional, Computational geometry, Form perception |
| Popis: | 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 |
| Druh dokumentu: | Article |
| Popis súboru: | application/pdf |
| DOI: | 10.1109/smi.2005.42 |
| Prístupová URL adresa: | https://dugi-doc.udg.edu/bitstream/10256/3066/1/192.pdf http://hdl.handle.net/10256/3066 http://ieeexplore.ieee.org/document/1563243/ https://dugi-doc.udg.edu/bitstream/handle/10256/3066/192.pdf?sequence=1 https://dugi-doc.udg.edu/bitstream/10256/3066/1/192.pdf https://dugi-doc.udg.edu/handle/10256/3066 https://ieeexplore.ieee.org/document/1563243/ https://dblp.uni-trier.de/db/conf/smi/smi2005.html#RigauFS05 https://hdl.handle.net/10256/3066 |
| Rights: | CC 0 |
| Prístupové číslo: | edsair.doi.dedup.....95b8dde1457de36ac6b1c81be9ab8af8 |
| Databáza: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | 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 |
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| DOI: | 10.1109/smi.2005.42 |