Paper Info
Title
A Combined Fuzzy and Probabilistic Data Descriptor for Distributed CBIR
Abstract
With the wide diffusion of digital image acquisition devices, the cost of managing hundreds of digital images is quickly increasing. Currently, the main way to search digital image libraries is by keywords given by the user. However, users usually add ambiguos keywords for large set of images. A content-based system intended to automatically find a query image, or similar images, within the whole collection is needed. In our work we address the scenario where medical image collections, which nowadays are rapidly expanding in quantity and heterogeneity, are shared in a distributed system to support diagnostic and preventive medicine. Our goal is to produce an efficient content-based description of each image collection in order to perform content-based image retrieval (CBIR) just in the node where the searched images are supposed to be. A novel combined fuzzy and probabilistic data descriptor is presented and experimental results are illustrated.
Year
DOI
Venue
2009
10.1007/978-3-642-02282-1_24
WILF
Keywords
Field
DocType
efficient content-based description,similar image,combined fuzzy,content-based system,query image,digital image,medical image collection,content-based image retrieval,digital image library,digital image acquisition device,image collection,probabilistic data descriptor,preventive medicine,distributed system,fuzzy clustering
Fuzzy clustering,Data mining,Automatic image annotation,Information retrieval,Computer science,Image retrieval,Image analysis,Digital image,Digital imaging,Probabilistic logic,Digital image processing
Conference
Volume
ISSN
Citations 
5571
0302-9743
0
PageRank 
References 
Authors
0.34
10
3
Name
Order
Citations
PageRank
Roberto Gallea1498.66
Marco La Cascia265571.39
Marco Morana311114.78