Texture analysis based on the extraction of contrast features is very effective in terms of both computational complexity and discrimination capability. In this framework, max-min approaches have been proposed in the past as a simple and powerful tool to characterize a statistical texture. In the present work, a method is proposed that allows exploiting the potential of max -min approaches to efficiently solve the problem of detecting local alterations in a uniform statistical texture. Experimental results show a high defect discrimination capability and a good attitude to real-time applications, which make it particularly attractive for the development of industrial visual inspection systems.

A Contrast-Based Approach to the Identification of Texture Faults / Granelli, Fabrizio; Vernazza, Gianni; De Natale, Francesco G. B.. - ELETTRONICO. - (2002).

A Contrast-Based Approach to the Identification of Texture Faults

Granelli, Fabrizio;De Natale, Francesco G. B.
2002-01-01

Abstract

Texture analysis based on the extraction of contrast features is very effective in terms of both computational complexity and discrimination capability. In this framework, max-min approaches have been proposed in the past as a simple and powerful tool to characterize a statistical texture. In the present work, a method is proposed that allows exploiting the potential of max -min approaches to efficiently solve the problem of detecting local alterations in a uniform statistical texture. Experimental results show a high defect discrimination capability and a good attitude to real-time applications, which make it particularly attractive for the development of industrial visual inspection systems.
2002
Trento, Italia
Università degli Studi di Trento. DEPARTMENT OF INFORMATION AND COMMUNICATION TECHNOLOGY
A Contrast-Based Approach to the Identification of Texture Faults / Granelli, Fabrizio; Vernazza, Gianni; De Natale, Francesco G. B.. - ELETTRONICO. - (2002).
Granelli, Fabrizio; Vernazza, Gianni; De Natale, Francesco G. B.
File in questo prodotto:
File Dimensione Formato  
02.PDF

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 374.7 kB
Formato Adobe PDF
374.7 kB Adobe PDF Visualizza/Apri

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/11572/358465
 Attenzione

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

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