Soft query in image retrieval systems

We explore the use of soft computing and user defined classifications in multimedia database systems for content- based queries to obtain the members of a class is a fixed set. With multimedia databases, however, an object may belong to different classes with different probabilities. In addition, alternative users may classify objects differently due to subjectivity of human perception on multimedia objects. In order to remedy for this situation, we propose a unified model that captures both conventional techniques and soft memberships. We implemented the model by extending the traditional database query capabilities such that the result of a query depends on the user who submits the query. We compared our proposed system with conventional image retrieval systems and observed a significant margin of improvement in matching the user expectations.

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