2014
Conference article  Open Access

Enriching image feature description supporting effective content-based retrieval and annotation

Debole F., Gennaro C., Savino P.

Pattern Recognition  Information Storage and Retrieval  Similarity Search  Content Based Image Retrieval 

The paper describes a technique that supports efficient and effective Content-Based Image Retrieval (CBIR) in very large image archives as well as automatic image tagging. The proposed technique uses a unified representation for image visual features and for image textual descriptions. Images are clustered according to their image visual features while textual content is used to associate relevant tags to images belonging to the same cluster. The system supports image retrieval based on image query similarity, on textual queries, and on mixed mode queries composed of an image and a textual part and automatic image tagging.

Source: VSMM 2014 - International Conference on Virtual Systems & Multimedia, pp. 80–87, Hong Kong, China, 8-12/12/2014

Publisher: IEEE Communications Society, Piscataway, USA


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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:343515,
	title = {Enriching image feature description supporting effective content-based retrieval and annotation},
	author = {Debole F. and Gennaro C. and Savino P.},
	publisher = {IEEE Communications Society, Piscataway, USA},
	doi = {10.1109/vsmm.2014.7136647},
	booktitle = {VSMM 2014 - International Conference on Virtual Systems \& Multimedia, pp. 80–87, Hong Kong, China, 8-12/12/2014},
	year = {2014}
}