Some approaches to improve tree-based nearest neighbour search algorithms

Some approaches to improve tree-based nearest neighbour search algorithms

Nearest neighbour search is a widely used technique in pattern recognition. During the last three decades a large number of fast algorithms have been proposed. In this work we are interested in algorithms that can be used with any dissimilarity function provided that it fits the mathematical notion of distance. Some of such algorithms organize, in preprocessing time, the data in a tree structur...

Some Improvements in Tree Based Nearest Neighbour Search Algorithms

Nearest neighbour search is one of the most simple and used technique in Pattern Recognition. In this paper we are interested on tree based algorithms that only make use of the metric properties of the space. One of the most known and refereed method in this class was proposed by Fukunaga and Narendra in the 70’s. This algorithm uses a tree that is traversed on search time and uses some elimina...

Fast k nearest neighbour search for R-tree family

A simpliied k nearest neighbour (knn) search for the R-tree 6] family is proposed in this paper. This method is modiied from the technique developed by Roussopoulos et al. 10]. The main approach aims to eliminate redundant searches when the data is highly correlated. We also describe how MINMAXDIST calculations can be avoided using MINDIST as the only distance metric which gives a signiicant sp...

Quick Full Search Equivalent Algorithms for Nearest Neighbour Pattern Matching

We consider the problem of finding the closest match for a given target vector in a codebook of codeword vectors. We present an approach which makes it possible to obtain quick full-search equivalent methods for finding the closest match with respect to some distortion measure. Our algorithms assume that the distortion measure obeys the triangle inequality of metric spaces. Results indicate tha...

Combining Elimination Rules in Tree-Based Nearest Neighbor Search Algorithms