Header menu link for other important links
X
Improved content-based image retrieval via discriminant analysis
S BOSE, A PAL, D CHAKRABARTI, T MUKHERJEE
Published in International Association of Computer Science and Information Technology
2017
Volume: 7
   
Issue: 3
Pages: 44 - 48
Abstract
The objective of Content-Based Image Retrieval (CBIR) methods is essentially to extract, from large (image) databases, a specified number of images similar in visual and semantic content to a so- called query image. To bridge the semantic gap that exists between the representation of an image by low-level features (namely, colour, shape, texture) and its high-level semantic content as perceived by humans, CBIR systems typically make use of the relevance feedback (RF) mechanism. RF iteratively incorporates user-given inputs regarding the relevance of retrieved images, to improve retrieval efficiency. One approach is to vary the weights of the features dynamically via feature reweighting. In this work, a novel approach has been proposed for improving the retrieval accuracy of CBIR system which incorporates RF based on feature reweighting using discriminant analysis. Results of a number of experiments have been presented to illustrate the significant improvement is retrieval accuracy with the proposed approach.
About the journal
JournalInternational Journal of Machine Learning and Computing
PublisherInternational Association of Computer Science and Information Technology
ISSN2010-3700
Open AccessYes