This paper introduces a new measure for computing the similarity among 3D objects as the average volume of the largest sub-cubes matching in the objects. The match is approximate and only verified within a neighbourhood from the position of the sub-cubes. Preliminary tests performed on random and synthetic datasets prove the efficacy of the similarity measure in capturing the visual similarity among the 3D objects and a reduction in the execution time when the neighbourhood is considered.

3D Average Common Submatrix Measure

Amelio A.
;
Greco S.
2020-01-01

Abstract

This paper introduces a new measure for computing the similarity among 3D objects as the average volume of the largest sub-cubes matching in the objects. The match is approximate and only verified within a neighbourhood from the position of the sub-cubes. Preliminary tests performed on random and synthetic datasets prove the efficacy of the similarity measure in capturing the visual similarity among the 3D objects and a reduction in the execution time when the neighbourhood is considered.
2020
3D objects
Image similarity
Pattern matching
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/320290
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact