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231223s2010 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2009.2039372
|2 doi
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|a eng
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| 100 |
1 |
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|a Baloch, Sajjad
|e verfasserin
|4 aut
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| 245 |
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|a Object recognition through topo-geometric shape models using error-tolerant subgraph isomorphisms
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|c 2010
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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| 500 |
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|a Date Completed 29.11.2010
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|a Date Revised 23.07.2010
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a We propose a method for 3-D shape recognition based on inexact subgraph isomorphisms, by extracting topological and geometric properties of a shape in the form of a shape model, referred to as topo-geometric shape model (TGSM). In a nutshell, TGSM captures topological information through a rigid transformation invariant skeletal graph that is constructed in a Morse theoretic framework with distance function as the Morse function. Geometric information is then retained by analyzing the geometric profile as viewed through the distance function. Modeling the geometric profile through elastic yields a weighted skeletal representation, which leads to a complete shape signature. Shape recognition is carried out through inexact subgraph isomorphisms by determining a sequence of graph edit operations on model graphs to establish subgraph isomorphisms with a test graph. Test graph is recognized as a shape that yields the largest subgraph isomorphism with minimal cost of edit operations. In this paper, we propose various cost assignments for graph edit operations for error correction that takes into account any shape variations arising from noise and measurement errors
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|a Journal Article
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|a Research Support, U.S. Gov't, Non-P.H.S.
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| 700 |
1 |
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|a Krim, Hamid
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 19(2010), 5 vom: 19. Mai, Seite 1191-200
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|x 1941-0042
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|g year:2010
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|g pages:1191-200
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|u http://dx.doi.org/10.1109/TIP.2009.2039372
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