This paper analyzes the use of histograms of low level image features, such as color and luminance, as descriptors for image retrieval purposes. A novel definition of histogram capacity curve taking into account the density distribution of histograms in the corresponding spaces is proposed and used to quantify the effectiveness of image descriptors and histogram dissimilarities in image retrieval applications. The results permit the design of scalable image retrieval systems which make optimal use of computational and storage resources.
Histograms analysis for image retrieval
Brunelli, Roberto;Mich, Ornella
2001-01-01
Abstract
This paper analyzes the use of histograms of low level image features, such as color and luminance, as descriptors for image retrieval purposes. A novel definition of histogram capacity curve taking into account the density distribution of histograms in the corresponding spaces is proposed and used to quantify the effectiveness of image descriptors and histogram dissimilarities in image retrieval applications. The results permit the design of scalable image retrieval systems which make optimal use of computational and storage resources.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.