Image indexing using shape-based visual features

Efficient image retrieval by contents from database requires that selective access methods are provided to prune out uninteresting items during the search process. Image indexing based on visual features is particularly challenging, owing to the difficulty to derive a representation of the shapes that closely models the visual appearance perceived by humans. In this paper we present a novel approach for indexing planar and closed curves, on the basis on their visual appearance. A hierarchical model of the curve is derived from its multi-scale analysis, and it is used to provide a description of the curve which is able to distinguish between its structural parts and its details. To cope with the inherent uncertainty of shape appearance, fuzzy sets are used to represent the visual attributes of the shapes. In this way the shapes which share similar structural parts can be gathered and embedded into an index structure which retains the imprecision of shape description by embedding fuzziness in the index itself.