Title :
Similarity retrieval of trademark images
Author :
Ciocca, G. ; Schettini, R.
Author_Institution :
ITIM, CNR, Milano, Italy
Abstract :
We investigate the hypothesis that the low-level image features used to index the trademark images can be correlated with image contents by applying a relevance feedback mechanism that evaluates the feature distributions of the images judged relevant, or not relevant, by the user, and dynamically updates both the similarity measure and query in order to better represent the user´s particular information needs. Experimental results on a database of 1100 trademarks are reported
Keywords :
content-based retrieval; copyright; database indexing; feature extraction; information needs; relevance feedback; visual databases; dynamic updating; feature distributions; image contents; image database; indexing; information needs; low-level image features; relevance feedback; similarity query; similarity retrieval; trademark images; Computational efficiency; Electrical capacitance tomography; Feedback; Histograms; Image retrieval; Indexing; Postal services; Shape; Trademarks; Wavelet transforms;
Conference_Titel :
Image Analysis and Processing, 1999. Proceedings. International Conference on
Conference_Location :
Venice
Print_ISBN :
0-7695-0040-4
DOI :
10.1109/ICIAP.1999.797712
