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A Cluster-based Approach for Efficient Content-based Image Retrieval Using a Similarity-preserving Space Transformation Method by Biren Shah; Vijay Raghavan; Praveen Dhatric; Xiaoquan Zhao is a Computer Science article available to read on EtoBox.

What is A Cluster-based Approach for Efficient Content-based Image Retrieval Using a Similarity-preserving Space Transformation Method about?

The techniques of clustering and space transformation have been successfully used in the past to solve a number of pattern recognition problems. In this article, the authors propose a new approach to content-based image retrieval (CBIR) that uses (a) a newly proposed similarity-preserving space transformation method to transform the original low-level image space into a highlevel vector space that enables efficient query processing, and (b) a clustering scheme that further improves the efficiency of our retrieval system. This combination is unique and the resulting system provides synergistic advantages of using both clustering and space transformation. The proposed space transformation method is shown to preserve the order of the distances in the transformed feature space. This strategy makes this approach to retrieval generic as it can be applied to object types, other than images, and feature spaces more general than metric spaces. The CBIR approach uses the inexpensive "estimated" distance in the transformed space, as opposed to the computationally inefficient "real" distance in the original space, to retrieve the desired results for a given query image. The authors also provid

Who reads A Cluster-based Approach for Efficient Content-based Image Retrieval Using a Similarity-preserving Space Transformation Method?

Author

Biren Shah; Vijay Raghavan; Praveen Dhatric; Xiaoquan Zhao

Publisher

John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Inc.; Publons; Wiley (ISSN 1532-2882)

Published

2006

Language

EN

Field

Computer Science (Physical Sciences)