Abstract
We present a novel image indexing and retrieval system based on object contour description. Extended curvature scale space (CSS) descriptors composed of both local and global features are used to represent and index concave and convex object shapes. These features are size, rotation, and translation invariant. The index is saved into an XML database conforming to the MPEG7 standard. Our system contains a graphical user interface that allows a user to search a database using either sample or user-drawn shapes. The system was tested using two image databases: the Tunisian National Library (TNL) database containing 430 color and gray-scale images of historic documents, mosaics, and artifacts; and the Squid dataset containing 1100 contour images of fish. Recall and precision rates of 94% and 87%, respectively, were achieved on the TNL database and 71% and 86% on the Squid database. Average response time to a query is about 2.55 sec on a 2.66 GHz Pentium-based computer with 256 Mbyte of RAM.
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Maghrebi, W., Borchani, A., Khabou, M.A., Alimi, A.M. (2008). A System for Historic Document Image Indexing and Retrieval Based on XML Database Conforming to MPEG7 Standard. In: Liu, W., Lladós, J., Ogier, JM. (eds) Graphics Recognition. Recent Advances and New Opportunities. GREC 2007. Lecture Notes in Computer Science, vol 5046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88188-9_12
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DOI: https://doi.org/10.1007/978-3-540-88188-9_12
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