Solving Intersection Searching problem for spatial data using bloom filters

Abstract

In a generalized Intersection Searching problem, a set S of spatial objects is pre-processed so that for a given a query object q, the question that whether q intersects with any object of S can be answered efficiently. A technique to solve Intersection Searching problem on spatial data using bloom filter is presented. Bloom filter on conventional data has been proved to be one of the most successful technique for solving set-membership problem. The presented method applies space filling curves on spatial objects to fetch appropriate information about these divisions. It then converts this information into a bloom filter which can be used for addressing intersection searching problem. The technique performs the intersection search query in O(1) amortized time. The space required to store the pre-processed spatial data set is linear to number of objects in the dataset.