Enhancing CBIR through feature optimization, combination and selection

Hilaire, X. and Jose, J. (2007) Enhancing CBIR through feature optimization, combination and selection. In: International Workshop on Content-Based Multimedia Indexing 2007 (CBMI'07), Bordeaux, France, 25-27 June 2007, pp. 267-274. ISBN 1424410118 (doi: 10.1109/CBMI.2007.385421)

Abstract

We present a content-based image retrieval (CBIR) method based on the combination and selection of several image features. The novelty of our approach over existing methods is threefold: we provide a statistical optimization of the similarity distance for each feature; we replace certain features by a selection in a non-linear expansion of them; and we perform a linear combination of the features. We demonstrate superior capabilities of our method in certain cases over support vector machines (SVM) on a COREL image collection.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Jose, Professor Joemon and Hilaire, Dr Xavier
• Authors: Hilaire, X., and Jose, J.
• Subjects: Z Bibliography. Library Science. Information Resources > Z665 Library Science. Information Science; Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Computing Science
• ISBN: 1424410118