Rotated image based photomosaic using combination of principal component hashing

Hideaki Uchiyama, Hideo Saito

Research output: Contribution to journalArticle

Abstract

This paper introduces a new method of Photomosaic. In this method, we propose to use tiled images that can be rotated in a restricted range. The tiled images are selected from a database. The selection of an image is done by a hashing method based on principal component analysis of a database. After computing the principal components of the database, various kinds of hash tables based on the linear combination of the principal component are prepared beforehand. Using our hashing method, we can reduce the computation time for selecting the tiled images based on the approximated nearest neighbor searching in consideration of a distribution of data in a database. We demonstrate the effectiveness of our hashing method by using a huge number of data in high dimensional space and better looking results of our tiling in experimental results.

Original languageEnglish
Pages (from-to)668-679
Number of pages12
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5414 LNCS
DOIs
Publication statusPublished - 2009

Fingerprint

Hashing
Principal Components
Principal component analysis
Tiling
Principal Component Analysis
Tables
Linear Combination
Nearest Neighbor
High-dimensional
Computing
Experimental Results
Range of data
Demonstrate

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

@article{287f0fadb8c744bd855592a19726fa46,
title = "Rotated image based photomosaic using combination of principal component hashing",
abstract = "This paper introduces a new method of Photomosaic. In this method, we propose to use tiled images that can be rotated in a restricted range. The tiled images are selected from a database. The selection of an image is done by a hashing method based on principal component analysis of a database. After computing the principal components of the database, various kinds of hash tables based on the linear combination of the principal component are prepared beforehand. Using our hashing method, we can reduce the computation time for selecting the tiled images based on the approximated nearest neighbor searching in consideration of a distribution of data in a database. We demonstrate the effectiveness of our hashing method by using a huge number of data in high dimensional space and better looking results of our tiling in experimental results.",
author = "Hideaki Uchiyama and Hideo Saito",
year = "2009",
doi = "10.1007/978-3-540-92957-4_58",
language = "English",
volume = "5414 LNCS",
pages = "668--679",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",
publisher = "Springer Verlag",

}

TY - JOUR

T1 - Rotated image based photomosaic using combination of principal component hashing

AU - Uchiyama, Hideaki

AU - Saito, Hideo

PY - 2009

Y1 - 2009

N2 - This paper introduces a new method of Photomosaic. In this method, we propose to use tiled images that can be rotated in a restricted range. The tiled images are selected from a database. The selection of an image is done by a hashing method based on principal component analysis of a database. After computing the principal components of the database, various kinds of hash tables based on the linear combination of the principal component are prepared beforehand. Using our hashing method, we can reduce the computation time for selecting the tiled images based on the approximated nearest neighbor searching in consideration of a distribution of data in a database. We demonstrate the effectiveness of our hashing method by using a huge number of data in high dimensional space and better looking results of our tiling in experimental results.

AB - This paper introduces a new method of Photomosaic. In this method, we propose to use tiled images that can be rotated in a restricted range. The tiled images are selected from a database. The selection of an image is done by a hashing method based on principal component analysis of a database. After computing the principal components of the database, various kinds of hash tables based on the linear combination of the principal component are prepared beforehand. Using our hashing method, we can reduce the computation time for selecting the tiled images based on the approximated nearest neighbor searching in consideration of a distribution of data in a database. We demonstrate the effectiveness of our hashing method by using a huge number of data in high dimensional space and better looking results of our tiling in experimental results.

UR - http://www.scopus.com/inward/record.url?scp=60149109656&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=60149109656&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-92957-4_58

DO - 10.1007/978-3-540-92957-4_58

M3 - Article

VL - 5414 LNCS

SP - 668

EP - 679

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

ER -