Abstract:
The explosive growth of digital media content from various domains has given rise to the need for
efficient techniques for retrieval of relevant information is getting more and more attention, especially
in the large-scale Multimedia Digital Database (MDD) applications. It is for this reason that there has
been an increased interest in the query reformulation for use in Multimedia Information Retrieval
(MIR) using a combination of various techniques. In this paper, we propose a retrieval method that is
formalized as an optimized similarity search process that combines Singular Value Decomposition
(SVD), Query Quality Refinement (QQR) using Histogram Equalization and Genetic Algorithm (GA)
enhancement. Experimental results show that the approach significantly narrows the search process by
retrieving similar images satisfying the needs of the user.
