research-article

An efficient fast-response content-based image retrieval framework for big data

Authors:

Ali.I. ELdesouky,

Hesham ArafatAuthors Info & Claims

Computers and Electrical Engineering, Volume 54, Issue C

Pages 522 - 538

https://doi.org/10.1016/j.compeleceng.2016.04.015

Published: 01 August 2016 Publication History

Abstract

In this paper, an efficient fast-response content-based image retrieval (CBIR) framework based on Hadoop MapReduce is proposed to operate stably with high performance targeting big data. It provides a novel bag of visual words (BOVW) technique based on a proposed chain-clustering binary search-tree (CC-BST) algorithm to build the visual statements for representing the image. As well, it introduces a proposed methodology for creating representatives for these visual statements as a solution for big-data' high-dimensionality. Further, those representatives are utilized to provide an indexing scheme for building one large file as an input for Hadoop. Moreover, an efficient-MapReduce technique is presented to exploit the created visual-representatives of the images to retrieve the top-relevant images for the input query. Empirical tests for the proposed techniques outperform the state-of-art compared techniques.

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Cited By

Ghahremani MGhadiri HHamghalam M(2021)Local features integration for content-based image retrieval based on color, texture, and shapeMultimedia Tools and Applications10.1007/s11042-021-10895-z80:18(28245-28263)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.1007/s11042-021-10895-z
Arulmozhi PAbirami S(2020)DSHPoolF: deep supervised hashing based on selective pool feature map for image retrievalThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-020-01993-437:8(2391-2405)Online publication date: 28-Oct-2020
https://dl.acm.org/doi/10.1007/s00371-020-01993-4
Prasanth TGunasekaran M(2019)Effective Big Data Retrieval Using Deep Learning Modified Neural NetworksMobile Networks and Applications10.1007/s11036-018-1204-y24:1(282-294)Online publication date: 15-Feb-2019
https://dl.acm.org/doi/10.1007/s11036-018-1204-y
Show More Cited By

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cover image Computers and Electrical Engineering

Computers and Electrical Engineering Volume 54, Issue C

August 2016

551 pages

ISSN:0045-7906

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Copyright © Elsevier Ltd.

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Pergamon Press, Inc.

United States

Publication History

Published: 01 August 2016

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Cited By

Ghahremani MGhadiri HHamghalam M(2021)Local features integration for content-based image retrieval based on color, texture, and shapeMultimedia Tools and Applications10.1007/s11042-021-10895-z80:18(28245-28263)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.1007/s11042-021-10895-z
Arulmozhi PAbirami S(2020)DSHPoolF: deep supervised hashing based on selective pool feature map for image retrievalThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-020-01993-437:8(2391-2405)Online publication date: 28-Oct-2020
https://dl.acm.org/doi/10.1007/s00371-020-01993-4
Prasanth TGunasekaran M(2019)Effective Big Data Retrieval Using Deep Learning Modified Neural NetworksMobile Networks and Applications10.1007/s11036-018-1204-y24:1(282-294)Online publication date: 15-Feb-2019
https://dl.acm.org/doi/10.1007/s11036-018-1204-y
Pouyanfar SYang YChen SShyu MIyengar S(2018)Multimedia Big Data AnalyticsACM Computing Surveys10.1145/315022651:1(1-34)Online publication date: 10-Jan-2018
https://dl.acm.org/doi/10.1145/3150226

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