Abstract

Image annotation is an important and challenging task when managing large image collections. In this paper, a fuzzy shape annotation approach for semi-automatic image annotation is presented. A fuzzy clustering process guided by partial supervision is applied to shapes represented by Fourier descriptors in order to derive a set of shape prototypes representative of a number of semantic categories. Next, prototypes are manually annotated by attaching textual labels related to semantic categories. Based on the labeled proto-types, a new shape is automatically labeled by associating a fuzzy set that provides membership degrees of the shape to all semantic categories. The proposed annotation approach provides an innovative indexing method for shape-based image retrieval. Indeed, shape prototypes represent an inter-mediate indexing level that allows a faster retrieval process since a query is matched against prototypes, instead of the whole shape database, resulting in a speed up of the retrieval. The proposed approach is tested on synthetic and real-word images in order to show its suitability.

Autore Pugliese

• Fanelli Anna Maria , Castellano Giovanna

Tutti gli autori

• FANELLI A.M.;CASTELLANO G.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2014

ISSN

0020-0255

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

12

Ultimo Aggiornamento Citazioni

Non Disponibile

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile