An indexing and retrieval system of historic art images based on fuzzy shape similarity

Authors:
Wafa Maghrebi;Leila Baccour;Mohamed A. Khabou;Adel M. Alimi
Affiliations:
REsearch Group on Intelligent Machines, University of Sfax, ENIS, DGE, Sfax, Tunisia;REsearch Group on Intelligent Machines, University of Sfax, ENIS, DGE, Sfax, Tunisia;Electrical and Computer Engineering Dept., University of West Florida, Pensacola, FL;REsearch Group on Intelligent Machines, University of Sfax, ENIS, DGE, Sfax, Tunisia
Venue:
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Year:
2007

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Abstract

We present an indexing and retrieval system of historic art images based on fuzzy shape similarity. The system is composed of three principal components: object annotation, object shape indexing, and query/retrieval. The object annotation in database images is done manually offline. The object shape indexing and retrieval, however, are done automatically. Annotated object shapes are indexed using an extended curvature scale space (CSS) descriptor suitable for concave and convex shapes. The query/retrieval of pertinent shapes from the database starts with a user drawing query (with a computer mouse or a pen) that is compared to entries in the database using a fuzzy similarity measure. The system is tested on a set of complex color and grey scale images of ancient documents, mosaics, and artifacts from the National Library of Tunisia, the National Archives of Tunisia, and a selection of Tunisian museums. The system's recall and precision rates were 83% and 60%, respectively.