Aggregation of color and shape features for hybrid query generation in content based visual information retrieval

Authors:
P. Androutsos;A. Kushki;K. N. Plataniotis;A. N. Venetsanopoulos
Affiliations:
Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ont., Canada M5S 3G4;Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ont., Canada M5S 3G4;Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ont., Canada M5S 3G4;Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, 10 King's College Road, Toronto, Ont., Canada M5S 3G4
Venue:
Signal Processing - Special section on content-based image and video retrieval
Year:
2005

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Abstract

A fuzzy approach for the aggregation of multiple features in content-based image retrieval is outlined. Color, shape and spatial features extracted using both computational and manual segmentation techniques are used for subsequent generation of hybrid queries to a ground truth image database consisting of architectural photographs. Retrieval results for multiple-feature queries are shown in the form of precision recall graphs. The results indicate that the fuzzy approach presented herein can perform at least as well as a weighted mean approach.