Efficient Near Neighbor Searching Using Multi-Indexes for Content-Based Multimedia Data Retrieval

Many content-based multimedia data retrieval problems can be transformed into the near neighbor searching problem in multidimensional feature space. An efficient near neighbor searching algorithm is needed when developing a multimedia database system. In this paper, we propose an approach to efficiently solve the near neighbor searching problem. In this approach, along each dimension an index is constructed according to the values of feature points of multimedia objects. A user can pose a content-based query by specifying a multimedia query example and a similarity measure. The specified query example will be transformed into a query point in the multi-dimensional feature space. The possible result points in each dimension are then retrieved by searching the value of the query point in the corresponding dimension. The sets of the possible result points are merged one by one by removing the points which are not within the query radius. The resultant points and their distances from the query point form the answer of the query. To show the efficiency of our approach, a series of experiments are performed to compare with the related approaches.