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Performance of Interpolated Histogram of Oriented Gradients on the Feature Calculation of SIFTOZTURK, A.   , CAYIROGLU, I. |
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Author keywords
image processing, computer vision, image analysis, feature extraction, object detection
References keywords
vision(9), image(9), scale(8), recognition(7), pattern(7), invariant(6), processing(5), local(5), feature(5), space(4)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2022-08-31
Volume 22, Issue 3, Year 2022, On page(s): 87 - 94
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2022.03010
Web of Science Accession Number: 000861021000010
SCOPUS ID: 85137667974
Abstract
Scale Invariant Feature Transform (SIFT) is the most dominant and robust object detection algorithm. It utilizes the Histogram of Oriented Gradients (HOG) method for feature computation. HOG is applied with trilinear interpolation to gain performance improvement. This paper examines the effect of interpolation on the performance of SIFT on both OXFORD and HPatches datasets. The various algorithms of interpolation for HOG, and the spatial binning process algorithm, are presented here. The performance is evaluated with Intersection Over Union, Correct Match Percentage, as well as the execution time of the algorithms. Moreover, we used the multiplication of the Intersection Over Union and Correct Match Percentage to take advantage of both metrics. It was observed that the interpolation did not significantly affect the performance of the SIFT. |
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[CrossRef] Web of Science® Citations for all references: 71,651 TCR SCOPUS® Citations for all references: 0 Web of Science® Average Citations per reference: 2,559 ACR SCOPUS® Average Citations per reference: 0 TCR = Total Citations for References / ACR = Average Citations per Reference We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more Citations for references updated on 2024-04-22 17:58 in 131 seconds. Note1: Web of Science® is a registered trademark of Clarivate Analytics. Note2: SCOPUS® is a registered trademark of Elsevier B.V. Disclaimer: All queries to the respective databases were made by using the DOI record of every reference (where available). Due to technical problems beyond our control, the information is not always accurate. Please use the CrossRef link to visit the respective publisher site. |
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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.
