The paper presents an highly selective algorithm for detecting extended and almost rectilinear shapes in digital images, in presence of structured and unstructured noise; it exploits the Gradient-based Hough Transform, followed by a special purpose correlation process in the parameter space. The paper discusses the algorithm and its application in a quality inspection task for detecting fabrication defects in mechanical pieces.

A highly selective HT based algorithm for detecting extended, almost rectilinear shapes / Cucchiara, R.; Filicori, F.. - 970:(1995), pp. 692-698. ( 6th International Conference on Computer Analysis of Images and Patterns, CAIP 1995 cze 1995) [10.1007/3-540-60268-2_366].

A highly selective HT based algorithm for detecting extended, almost rectilinear shapes

Cucchiara R.;
1995

Abstract

The paper presents an highly selective algorithm for detecting extended and almost rectilinear shapes in digital images, in presence of structured and unstructured noise; it exploits the Gradient-based Hough Transform, followed by a special purpose correlation process in the parameter space. The paper discusses the algorithm and its application in a quality inspection task for detecting fabrication defects in mechanical pieces.
1995
no
Inglese
6th International Conference on Computer Analysis of Images and Patterns, CAIP 1995
cze
1995
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
970
692
698
978-3-540-60268-2
978-3-540-44781-8
Springer Verlag
Cucchiara, R.; Filicori, F.
Atti di CONVEGNO::Relazione in Atti di Convegno
273
2
A highly selective HT based algorithm for detecting extended, almost rectilinear shapes / Cucchiara, R.; Filicori, F.. - 970:(1995), pp. 692-698. ( 6th International Conference on Computer Analysis of Images and Patterns, CAIP 1995 cze 1995) [10.1007/3-540-60268-2_366].
none
info:eu-repo/semantics/conferenceObject
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1247281
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? ND
social impact