Speeding up the similarity search in multimedia database

In recent years, applications in multimedia databases have been more and more important. One new capability is to search by similarity in low-level image features (such as color, texture, shape, and motion). The performance of the similarity search highly relies on efficient index structures. However, current high-dimensional indexing techniques have limitations and a simple sequential scan algorithm can outperform them in many cases. We notice that few researchers have really evaluated the utilization of the actual memory size and the trade-off between I/O access time and computation time. Some methods tried to reduce the I/O access time but caused computation overhead. We propose a novel indexing technique, the RA-Blocks (Region Approximated Blocks), to overcome these limitations and improve the similarity search in multimedia databases. We also demonstrate the better performance of our work in experiments.