Image Similarity Search: Theory and Practice

NOVÁK, David. Image Similarity Search: Theory and Practice. In MEMICS 2007: Third Doctoral Workshop on Mathematical and Engineering Methods in Computer Science. Brno, Czech Republic: Masaryk University and Technical University of Brno, 2007, p. 154-160. ISBN 978-80-7355-077-6.

Basic information

Original name

Image Similarity Search: Theory and Practice

Name in Czech

Podobnostní vyhledávání v obrázcích: Teorie a praxe

Authors

NOVÁK, David (203 Czech Republic, guarantor, belonging to the institution)

Edition

Brno, Czech Republic, MEMICS 2007: Third Doctoral Workshop on Mathematical and Engineering Methods in Computer Science, p. 154-160, 7 pp. 2007

Publisher

Masaryk University and Technical University of Brno

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

MEMICS

RIV identification code

RIV/00216224:14330/07:00019493

Organization unit

Faculty of Informatics

ISBN

978-80-7355-077-6

Keywords in English

similarity search; content based image retrieval; peer-to-peer

Tags

content based image retrieval, DISA, Peer-to-Peer, similarity search

Tags

International impact, Reviewed

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Abstract

V originále

The data-explosion phenomenon proceeds in two respects: (1) The volume of data produced is increasing rapidly and (2) new data types appear and are widely used. This calls for development of brand new indexing and searching methods which would respect the needs of the recent data types and be efficient on vast amounts of data. This paper describes a transfer of our previous theoretical results in this area into practice by building a fully functional application. The application is able to efficiently manage large collections of digital images and search these images according to their very content (the similarity search). Its distributed architecture is based on the peer-to-peer paradigm and the searching method adopts the metric-based approach to similarity. Currently the application can store and search tens of millions of images downloaded from the Web with dozens of simultaneous users, although it runs on a limited hardware infrastructure.

In Czech

Článek popisuje převod našich teoretických výsledků v oblasti podobnostního vyhledávání do praxe. Výsledkem je funkční systém pro plnohodnotné podobnostní vyhledávání v rozsáhlých kolekcích digitálních obrázků.

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Links

GD102/05/H050, research and development project	Name: Integrovaný přístup k výchově studentů DSP v oblasti paralelních a distribuovaných systémů Investor: Czech Science Foundation, Integrated approach to education of PhD students in the area of parallel and distributed systems
1ET100300419, research and development project	Name: Inteligentní modely, algoritmy, metody a nástroje pro vytváření sémantického webu Investor: Academy of Sciences of the Czech Republic, Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)