A Hybrid Approach for Image Retrieval with Ontological Content-Based Indexing
This paper presents a novel approach for image retrieval from digital collections. Specifically, we describe IRONS (Image Retrieval with Ontological Descriptions of Shapes), a system based on the application of several novel algorithms that combine low-level image analysis techniques with automatic shape extraction and indexing. In order to speed up preprocessing, we have proposed and implemented the convex regions algorithm and discrete curve evolution approach. The image indexing module of IRONS is addressed using two proposed algorithms: the tangent space and the two-segment turning function for shapes representation invariant to rotation and scale. Another goal of the proposed method is the integration of user-oriented descriptions, which leads to more complete retrieval by accelerating the convergence to the expected result. For the definition of image semantics, ontology annotation of sub-regions has been used.
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