Generic Multimedia Database Architecture Based upon Semantic Libraries

Semantic-based storage and retrieval of multimedia data requires accurate annotation of the data. Annotation can be done either manually or automatically. The retrieval performance of the manual annotation based approaches is quite good, as compared to approaches based on automatic annotation. However, manual annotation is time consuming and labor extensive. Therefore, it is quite difficult to apply this technique on huge volume of multimedia data. On the other hand, automatic annotation is commonly used to annotate the multimedia data based on low level features, which obviously lacks the semantic nature of the multimedia data. Yet, we have not come across with any such system which automatically annotate the multimedia data based on the extracted semantics accurately. In this paper, we have performed automatic annotation of the images by extracting their semantics (high level features) with the help of semantic libraries. Semantic libraries use semantic graphs. Each graph consists of related concepts along with their relationships. We have also demonstrated with the help of a case study that our proposed approach ensures an improvement in the semantic based retrieval of multimedia data.