Distributed image retrieval with colour and keypoint features

Content-based image retrieval poses many problems to computer systems. The content of images has to be described by some feature extraction methods. As image databases are often very large, they are sometimes to complex to be processed by traditional computing methods. We have to use big data soluti...

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Main Authors: Michał Ła̧giewka, Marcin Korytkowski, Rafal Scherer
Format: Article
Language:English
Published: Taylor & Francis Group 2019-10-01
Series:Journal of Information and Telecommunication
Subjects:
Online Access:http://dx.doi.org/10.1080/24751839.2019.1620023
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spelling doaj-dfde43d1dd364e0b96b9521635db3c692020-11-25T00:53:56ZengTaylor & Francis GroupJournal of Information and Telecommunication2475-18392475-18472019-10-013443044510.1080/24751839.2019.16200231620023Distributed image retrieval with colour and keypoint featuresMichał Ła̧giewka0Marcin Korytkowski1Rafal Scherer2Czestochowa University of TechnologyCzestochowa University of TechnologyCzestochowa University of TechnologyContent-based image retrieval poses many problems to computer systems. The content of images has to be described by some feature extraction methods. As image databases are often very large, they are sometimes to complex to be processed by traditional computing methods. We have to use big data solutions to fast retrieve images. The paper presents a system for retrieving images in relational databases in a distributed environment. Content of the query image and images in the database is compared using global colour information and local image keypoints. Image keypoint descriptors are indexed by fuzzy sets directly in a relational database by our algorithm. The process is distributed to several machines thanks to the Apache Hadoop software framework with HDFS.http://dx.doi.org/10.1080/24751839.2019.1620023hadoophdfsdistributed storagecontent-based image retrievalcolour histogramimage keypointsrelational databases
collection DOAJ
language English
format Article
sources DOAJ
author Michał Ła̧giewka
Marcin Korytkowski
Rafal Scherer
spellingShingle Michał Ła̧giewka
Marcin Korytkowski
Rafal Scherer
Distributed image retrieval with colour and keypoint features
Journal of Information and Telecommunication
hadoop
hdfs
distributed storage
content-based image retrieval
colour histogram
image keypoints
relational databases
author_facet Michał Ła̧giewka
Marcin Korytkowski
Rafal Scherer
author_sort Michał Ła̧giewka
title Distributed image retrieval with colour and keypoint features
title_short Distributed image retrieval with colour and keypoint features
title_full Distributed image retrieval with colour and keypoint features
title_fullStr Distributed image retrieval with colour and keypoint features
title_full_unstemmed Distributed image retrieval with colour and keypoint features
title_sort distributed image retrieval with colour and keypoint features
publisher Taylor & Francis Group
series Journal of Information and Telecommunication
issn 2475-1839
2475-1847
publishDate 2019-10-01
description Content-based image retrieval poses many problems to computer systems. The content of images has to be described by some feature extraction methods. As image databases are often very large, they are sometimes to complex to be processed by traditional computing methods. We have to use big data solutions to fast retrieve images. The paper presents a system for retrieving images in relational databases in a distributed environment. Content of the query image and images in the database is compared using global colour information and local image keypoints. Image keypoint descriptors are indexed by fuzzy sets directly in a relational database by our algorithm. The process is distributed to several machines thanks to the Apache Hadoop software framework with HDFS.
topic hadoop
hdfs
distributed storage
content-based image retrieval
colour histogram
image keypoints
relational databases
url http://dx.doi.org/10.1080/24751839.2019.1620023
work_keys_str_mv AT michałłagiewka distributedimageretrievalwithcolourandkeypointfeatures
AT marcinkorytkowski distributedimageretrievalwithcolourandkeypointfeatures
AT rafalscherer distributedimageretrievalwithcolourandkeypointfeatures
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