Title: Generic Multimedia Database Architecture: Towards High-Level Semantic Retrieval

Abstract
: Extraction of semantics has been a challenging problem in multimedia databases. Common methods for semantic extraction are based on manual annotation of multimedia data and/or content retrieval based on local or global feature distribution. Content retrieval based feature extraction (e.g. color, texture and location) fails to extract the semantics. Manual annotation of multimedia data for semantics presents promising results but it is time consuming and will be impossible when considering the huge database compose of thousands of images. In this paper we have presented the idea of semantic extraction by using semantic libraries. In our approach we extract the semantics by considering the dominant objects in the image, the relationships among these objects, state of these objects and the environment in which they exist. Design and working along with proposed results of these semantic libraries have been shown. Our proposed generic multimedia database architecture could give better results with the improvement in the technologies related to object detection, region splitting and feature extraction.

Authors
Omara Abdul Hamid, Muhammad Abdul Qadir, Mohib ur Rehman, Nadeem Iftikhar, Mobin Uddin Ahmed, and Imran Ihsan

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