Title: Combined local colour curvelet and mesh pattern for image retrieval system

Authors: Yesubai Rubavathi Charles

Addresses: Musaliar College of Engineering and Technology, Kerala, India

Abstract: This manuscript presents the content based image retrieval system using new textural features such as colour local curvelet (CLC) based textural descriptor and colour local mesh pattern (CLMP), for the intention of increasing the performance of the image retrieval system. The proposed methods can be able to utilise the distinctive details obtained from spatial coloured textural patterns of various spectral components within the particular local image region. Furthermore, to acquire the benefit of harmonising effect through joint colour texture information, the oppugant colour textural features that obtain the texture patterns of spatial interactions among spectral planes are also integrated in to the creation of CLC and CLMP. Extensive and comparative experiments have been conducted on two benchmark databases, i.e., Corel-1k, MIT VisTex. Retrieval results show that image retrieval using colour local texture features yields better precision and recall than retrieval approaches using either by colour or texture features.

Keywords: content-based image retrieval system; curvelet transform; local mesh pattern; local colour curvelets; LCC; local colour mesh pattern; LCMP.

DOI: 10.1504/IJBIDM.2019.101262

International Journal of Business Intelligence and Data Mining, 2019 Vol.15 No.2, pp.190 - 203

Received: 19 Mar 2017
Accepted: 11 May 2017

Published online: 31 May 2019 *

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