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

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: printed version "print"
• WWW: 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

Abstract

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.

Abstract (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.

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)