Fast Nearest-Neighbor Search Based on Voronoi Projections and Its Application to Vector Quantization Encoding
File version
Author(s)
Paliwal, KK
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
Size
214208 bytes
File type(s)
application/pdf
Location
License
Abstract
In this work, we consider two fast nearest-neighbor search methods based on the projections of Voronoi regions, namely, the box-search method and the cell-partition search method. We provide their comprehensive study in the contest of vector quantization encoding. We show that the use of principal component transformation reduces the complexity of Voronoi-projection based search significantly for data with high degree of correlation across their components.
Journal Title
IEEE Transactions on Speech and Audio Processing
Conference Title
Book Title
Edition
Volume
7
Issue
2
Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
© 1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Item Access Status
Note
Access the data
Related item(s)
Subject
Artificial Intelligence and Image Processing
Electrical and Electronic Engineering