Efficient near neighbor searching using multi-indexes for content-based multimedia data retrieval

Many content-based multimedia data retrieval problems can be transformed in to the near neighbor searching problem in multidimensional feature space. A n efficient near neighbor searching algorithm is needed when developing a m ultimedia database system. In this paper, we propose an approach to efficie ntly solve the near neighbor searching problem. In this approach, along eac h dimension an index is constructed according to the values of feature poin ts of multimedia objects. A user can pose a content-based query by specifyi ng a multimedia query example and a similarity measure. The specified query example will be transformed into a query point in the multi-dimensional fe ature space. The possible result points in each dimension are then retrieve d by starching the value of the query point ill the corresponding dimension . The sets of the possible result points are merged one by one by removing the point, which are nut 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 co mpare with the related approaches.