In this paper, we present a fast and versatile algorithm which can rapidly perform a variety of
nearest neighbor searches. Efficiency improvement is achieved by utilizing the distance …

Nearest neighbour (NN) searches and k nearest neighbour (k-NN) searches are widely
used in pattern recognition and image retrieval. An NN (k-NN) search finds the closest object …

The problem of k nearest neighbors (kNN) is to find the nearest k neighbors for a query point
from a given data set. In this paper, a novel fast kNN search method using an orthogonal …

The nearest neighbour problem is of practical significance in a number of fields. Often we
are interested in finding an object near to a given query object. The problem is old, and a …

Approximate nearest neighbor algorithms are used to speed up nearest neighbor search in
a wide array of applications. However, current indexing methods feature several …

We present two new neighbor query algorithms, including range query (RNN) and nearest
neighbor (NN) query, based on revised kd tree by using two techniques. The first technique …

This paper presents a novel algorithm for fast nearest neighbor search. At the preprocessing
stage, the proposed algorithm constructs a lower bound tree by agglomeratively clustering …

Nearest neighbor searching is an important issue in both pattern recognition and image
processing. However, most of the previous methods suffer from high computational …

The problem of k-nearest neighbors (kNN) is to find the nearest k neighbors for a query point
from a given data set. Among available methods, the principal axis search tree (PAT) …

Abstract The goal of Nearest Neighbour (NN) search is to find the objects in a dataset A that
are closest to a query point q. Existing algorithms presume that the dataset is indexed by an …