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Content-Based Image Retrieval Method using the Relative Location of Multiple ROIsLEE, J.   , NANG, J. |
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Author keywords
image retrieval, information retrieval, content based retrieval, search methods, nearest neighbor searches
References keywords
image(14), retrieval(8), content(5), mpeg(4), icip(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2011-08-31
Volume 11, Issue 3, Year 2011, On page(s): 85 - 90
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.03014
Web of Science Accession Number: 000296186700014
SCOPUS ID: 80055071456
Abstract
Recently the method of specifying multiple regions of interest (ROI) based image retrieval has been suggested. However it measures the similarity of the images without proper consideration of the spatial layouts of the ROIs and thus fails to accurately reflect the intent of the user. In this paper, we propose a new similarity measurement using the relative layouts of the ROIs. The proposed method divides images into blocks of certain size and extracted MPEG-7 dominant colors from the blocks overlapping with the user-designated ROIs to measure their similarities with the target images. At this point, similarity was weighted when the relative location of the ROIs in the query image and the target image was the same. The relative location was calculated by four directions (i.e. up, down, left and right) of the basis ROI. The proposed method by an experiment using MPEG-7 XM shows that its performance is higher than the global image retrieval method or the retrieval method that does not consider the relative location of ROIs. |
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[1] Region-based surveillance video retrieval with effective object representation, Chamasemani, Fereshteh Falah, Affendey, Lilly Suriani, Mustapha, Norwati, Khalid, Fatimah, The Imaging Science Journal, ISSN 1368-2199, Issue 3, Volume 66, 2018.
Digital Object Identifier: 10.1080/13682199.2017.1395547 [CrossRef]
[2] Tekrarlı Ortalama Yardımıyla Renk İndirgeme ve Görüntü Erişimi, KILIÇASLAN, Mahmut, TANYERİ, Ufuk, DEMİRCİ, Recep, Düzce Üniversitesi Bilim ve Teknoloji Dergisi, ISSN 2148-2446, Issue 1, Volume 8, 2020.
Digital Object Identifier: 10.29130/dubited.643351 [CrossRef]
[3] Improving content-based image retrieval with compact global and local multi-features, Alzu’bi, Ahmad, Amira, Abbes, Ramzan, Naeem, Jaber, Tareq, International Journal of Multimedia Information Retrieval, ISSN 2192-6611, Issue 4, Volume 5, 2016.
Digital Object Identifier: 10.1007/s13735-016-0109-4 [CrossRef]
[4] A novel technique for location independent object based image retrieval, Raghuwanshi, Ghanshyam, Tyagi, Vipin, Multimedia Tools and Applications, ISSN 1380-7501, Issue 12, Volume 76, 2017.
Digital Object Identifier: 10.1007/s11042-016-3747-x [CrossRef]
[5] An integrated approach for image retrieval using local binary pattern, Shrivastava, Nishant, Tyagi, Vipin, Multimedia Tools and Applications, ISSN 1380-7501, Issue 11, Volume 75, 2016.
Digital Object Identifier: 10.1007/s11042-015-2589-2 [CrossRef]
[6] An Efficient Deep Learning-based Content-based Image Retrieval Framework, Sivakumar, M., M. Saravana Kumar, N., Karthikeyan, N., Computer Systems Science and Engineering, ISSN 0267-6192, Issue 2, Volume 43, 2022.
Digital Object Identifier: 10.32604/csse.2022.021459 [CrossRef]
[7] Semantic content-based image retrieval: A comprehensive study, Alzu’bi, Ahmad, Amira, Abbes, Ramzan, Naeem, Journal of Visual Communication and Image Representation, ISSN 1047-3203, Issue , 2015.
Digital Object Identifier: 10.1016/j.jvcir.2015.07.012 [CrossRef]
[8] Content based image retrieval based on relative locations of multiple regions of interest using selective regions matching, Shrivastava, Nishant, Tyagi, Vipin, Information Sciences, ISSN 0020-0255, Issue , 2014.
Digital Object Identifier: 10.1016/j.ins.2013.08.043 [CrossRef]
[9] Region based image retrieval using ranking concept of local binary pattern, Obulesu, A., Kumar, V. Vijay, Sumalatha, L., Niranjan, S K, 2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), ISBN 978-1-5090-6400-7, 2017.
Digital Object Identifier: 10.1109/ICBDACI.2017.8070863 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
All rights reserved: Advances in Electrical and Computer Engineering is a registered trademark of the Stefan cel Mare University of Suceava. No part of this publication may be reproduced, stored in a retrieval system, photocopied, recorded or archived, without the written permission from the Editor. When authors submit their papers for publication, they agree that the copyright for their article be transferred to the Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University of Suceava, Romania, if and only if the articles are accepted for publication. The copyright covers the exclusive rights to reproduce and distribute the article, including reprints and translations.
Permission for other use: The copyright owner's consent does not extend to copying for general distribution, for promotion, for creating new works, or for resale. Specific written permission must be obtained from the Editor for such copying. Direct linking to files hosted on this website is strictly prohibited.
Disclaimer: Whilst every effort is made by the publishers and editorial board to see that no inaccurate or misleading data, opinions or statements appear in this journal, they wish to make it clear that all information and opinions formulated in the articles, as well as linguistic accuracy, are the sole responsibility of the author.
