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.