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Unsupervised Elimination of Media Items in Content-Based Image Retrieval

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2 Author(s)
Guldogan, E. ; Inst. of Signal Process., Tampere Univ. of Technol., Tampere, Finland ; Gabbouj, M.

A novel unsupervised method for elimination of irrelevant media items for retrieval is presented. The proposed method aims to decrease retrieval complexity and memory consumption of content-based indexing and retrieval systems. The method is suitable for layered systems that iterates query process more than one time to improve and/or refine the query results. The elimination is performed on the query results of the first step of retrieval. Experiments show that, the error rate of missing relevant images in the eliminated part of the database is ~0.01%. Low complexity and successful accuracy allow the proposed method to be used in various platforms such as distributed and limited systems.

Published in:

Signal Processing and Communications, 2007. ICSPC 2007. IEEE International Conference on

Date of Conference:

24-27 Nov. 2007