The interpretation of natural scenes, generally so obvious and effortless for humans, still remains a challenge in computer vision. To allow the search of image-based documents in digital libraries, we propose to design classifiers able to annotate images with keywords. First, we propose an image representation appropriate for scene description. Images are segmented into regions, and then indexed according to the presence of given region types. Second, we propound a classification scheme designed to separate images in the descriptor space. This is achieved by combining feature selection and kernel-method-based classification.

Image recognition for digital libraries

Amato G
2004

Abstract

The interpretation of natural scenes, generally so obvious and effortless for humans, still remains a challenge in computer vision. To allow the search of image-based documents in digital libraries, we propose to design classifiers able to annotate images with keywords. First, we propose an image representation appropriate for scene description. Images are segmented into regions, and then indexed according to the presence of given region types. Second, we propound a classification scheme designed to separate images in the descriptor space. This is achieved by combining feature selection and kernel-method-based classification.
2004
Istituto di Scienza e Tecnologie dell'Informazione "Alessandro Faedo" - ISTI
1-58113-940-3
Scene analysis
Image Segmentation
Clustering
Feature selection
Image classification
Kernel-method
File in questo prodotto:
File Dimensione Formato  
prod_91077-doc_57595.pdf

solo utenti autorizzati

Descrizione: Articolo
Tipologia: Versione Editoriale (PDF)
Dimensione 544.51 kB
Formato Adobe PDF
544.51 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

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/20.500.14243/57537
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 14
  • ???jsp.display-item.citation.isi??? ND
social impact