BASIL: Effective near-duplicate image detection using gene sequence alignment

Hung Sik Kim, Hau Wen Chang, Jeongkyu Lee, Dongwon Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations


Finding near-duplicate images is a task often found in Multimedia Information Retrieval (MIR). Toward this effort, we propose a novel idea by bridging two seemingly unrelated fields - MIR and Biology. That is, we propose to use the popular gene sequence alignment algorithm in Biology, i.e., BLAST, in detecting near-duplicate images. Under the new idea, we study how various image features and gene sequence generation methods (using gene alphabets such as A, C, G, and T in DNA sequences) affect the accuracy and performance of detecting near-duplicate images. Our proposal, termed as BLASTed Image Linkage (BASIL), is empirically validated using various real data sets. This work can be viewed as the "first" step toward bridging MIR and Biology fields in the well-studied near-duplicate image detection problem.

Original languageEnglish (US)
Title of host publicationAdvances in Information Retrieval - 32nd European Conference on IR Research, ECIR 2010, Proceedings
PublisherSpringer Verlag
Number of pages12
ISBN (Print)3642122744, 9783642122743
StatePublished - 2010
Event32nd European Conference on Information Retrieval, ECIR 2010 - Milton Keynes, United Kingdom
Duration: Mar 28 2010Mar 31 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5993 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other32nd European Conference on Information Retrieval, ECIR 2010
Country/TerritoryUnited Kingdom
CityMilton Keynes

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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