4/2011 - 18 |
New Method to Detect Salient Objects in Image Segmentation using Hypergraph StructureGANEA, E. , BURDESCU, D. D. , BREZOVAN, M. |
Extra paper information in |
Click to see author's profile in SCOPUS, IEEE Xplore, Web of Science |
Download PDF (451 KB) | Citation | Downloads: 1,563 | Views: 5,376 |
Author keywords
feature extraction, image processing, image segmentation, hypergraph data structures, object detection
References keywords
segmentation(12), image(12), pattern(10), vision(8), recognition(6), graph(6), multimedia(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2011-11-30
Volume 11, Issue 4, Year 2011, On page(s): 111 - 116
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.04018
Web of Science Accession Number: 000297764500018
SCOPUS ID: 84856623803
Abstract
This paper presents a method for detection of salient objects from images. The proposed algorithms for image segmentation and objects detection use a hexagonal representation of the image pixels and a hypergraph structure to process this hierarchal structure. The main goal of the method is to obtain salient regions, which may be associated with semantic labels. The designed algorithms use color characteristic and syntactic features for image segmentation. The object-oriented model used for storing the results of the segmentation and detection allows directly annotation of regions without a processing of these. The experiments showed that the presented method is robust and accurate comparing with others public methods used for salient objects detection. |
References | | | Cited By |
Web of Science® Times Cited: 2 [View]
View record in Web of Science® [View]
View Related Records® [View]
Updated today
SCOPUS® Times Cited: 5
View record in SCOPUS® [Free preview]
View citations in SCOPUS® [Free preview]
[1] Development of technique for face detection in image based on binarization, scaling and segmentation methods, Fedorov, Eugene, Utkina, Tetyana, Nechyporenko, Olga, Korpan, Yaroslav, Eastern-European Journal of Enterprise Technologies, ISSN 1729-4061, Issue 9 (103), Volume 1, 2020.
Digital Object Identifier: 10.15587/1729-4061.2020.195369 [CrossRef]
[2] An Efficient Solution for Hand Gesture Recognition from Video Sequence, PRODAN, R.-C., PENTIUC, S.-G., VATAVU, R.-D., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 3, Volume 12, 2012.
Digital Object Identifier: 10.4316/aece.2012.03013 [CrossRef] [Full text]
[3] Segmentation of Bone Structure in X-ray Images using Convolutional Neural Network, CERNAZANU-GLAVAN, C., HOLBAN, S., Advances in Electrical and Computer Engineering, ISSN 1582-7445, Issue 1, Volume 13, 2013.
Digital Object Identifier: 10.4316/AECE.2013.01015 [CrossRef] [Full text]
[4] Events Recognition by Tracking Salient Regions from Video Data, Ganea, Eugen, Proceedings of the 7th Balkan Conference on Informatics Conference, ISBN 9781450333351, 2015.
Digital Object Identifier: 10.1145/2801081.2801099 [CrossRef]
[5] On How To Combine Image Segmentation Algorithms Using Entropy, Balutoiu, Maria Anca, Sturzu, Dragos, Boiangiu, Costin-Anton, Voncila, Mihai-Lucian, Tarba, Nicolae, Vlasceanu, Giorgiana Violeta, 2021 20th RoEduNet Conference: Networking in Education and Research (RoEduNet), ISBN 978-1-6654-1351-0, 2021.
Digital Object Identifier: 10.1109/RoEduNet54112.2021.9638272 [CrossRef]
Disclaimer: All information displayed above was retrieved by using remote connections to respective databases. For the best user experience, we update all data by using background processes, and use caches in order to reduce the load on the servers we retrieve the information from. As we have no control on the availability of the database servers and sometimes the Internet connectivity may be affected, we do not guarantee the information is correct or complete. For the most accurate data, please always consult the database sites directly. Some external links require authentication or an institutional subscription.
Web of Science® is a registered trademark of Clarivate Analytics, Scopus® is a registered trademark of Elsevier B.V., other product names, company names, brand names, trademarks and logos are the property of their respective owners.
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.