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Large-scale duplicate detection for web image search

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

Finding visually identical images in large image collections is important for many applications such as intelligence propriety protection and search result presentation. Several algorithms have been reported in the literature, but they are not suitable for large image collections. In this paper, a novel algorithm is proposed to handle the situation, in which each image is compactly represented by a hash code. To detect duplicate images, only the hash codes are required. In addition, a very efficient search method is implemented to quickly group images with similar hash codes for fast detection. The experiments show that our algorithm can be both efficient and effective for duplicate detection in web image search. © 2006 IEEE.
Original languageEnglish
Title of host publication2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings
Pages353-356
Volume2006
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Toronto, ON, Canada
Duration: 9 Jul 200612 Jul 2006

Publication series

Name2006 IEEE International Conference on Multimedia and Expo, ICME 2006 - Proceedings
Volume2006

Conference

Conference2006 IEEE International Conference on Multimedia and Expo, ICME 2006
PlaceCanada
CityToronto, ON
Period9/07/0612/07/06

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

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