Quick Full Search Equivalent Algorithms for Nearest Neighbour Pattern Matching

نویسندگان

  • Joselito Chua
  • Peter Tischer
  • David Ng
چکیده

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 that it may be possible to search an arbitrary codebook as efficiently as a tree-structured codebook. We believe these algorithms will find general applicability in problem domains other than Vector Quantization, particularly those where static codebooks are used.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Testing Some Improvements of the Fukunaga and Narendra's Fast Nearest Neighbour Search Algorithm in a Spelling Task

Nearest neighbour search is one of the most simple and used technique in Pattern Recognition. One of the most known fast nearest neighbour algorithms was proposed by Fukunaga and Narendra. The algorithm builds a tree in preprocess time that is traversed on search time using some elimination rules to avoid its full exploration. This paper tests two new types of improvements in a real data enviro...

متن کامل

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...

متن کامل

Some improvements on NN based classifiers in metric spaces

The nearest neighbour (NN) and k-nearest neighbour (k-NN) classification rules have been widely used in Pattern Recognition due to its simplicity and good behaviour. Exhaustive nearest neighbour search may become unpractical when facing large training sets, high dimensional data or expensive dissimilarity measures (distances). During the last years a lot of fast NN search algorithms have been d...

متن کامل

Nearest Neighbour Strategies for Image Understanding

Nearest Neighbour algorithms for pattern recognition have been widely studied. It is now well-established that they offer a quick and reliable method of data classification. In this paper we further develop the basic definition of the standard k-nearest neighbour algorithm to include the ability to resolve conflicts when the highest number of nearest neighbours are found for more than one train...

متن کامل

Extending LAESA Fast Nearest Neighbour Algorithm to Find the k Nearest Neighbours

Many pattern recognition tasks make use of the k nearest neighbour (k–NN) technique. In this paper we are interested on fast k– NN search algorithms that can work in any metric space i.e. they are not restricted to Euclidean–like distance functions. Only symmetric and triangle inequality properties are required for the distance. A large set of such fast k–NN search algorithms have been develope...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2004