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Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference
This paper presents an improved Oriented Features from Accelerated Segment Test (FAST) and Rotated BRIEF (ORB) algorithm named ORB using three-patch and local gray difference (ORB-TPLGD). ORB takes a breakthrough in real-time aspect. However, subtle changes of the image may greatly affect its final...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070684/ https://www.ncbi.nlm.nih.gov/pubmed/32059395 http://dx.doi.org/10.3390/s20040975 |
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author | Ma, Chaoqun Hu, Xiaoguang Xiao, Jin Du, Huanchao Zhang, Guofeng |
author_facet | Ma, Chaoqun Hu, Xiaoguang Xiao, Jin Du, Huanchao Zhang, Guofeng |
author_sort | Ma, Chaoqun |
collection | PubMed |
description | This paper presents an improved Oriented Features from Accelerated Segment Test (FAST) and Rotated BRIEF (ORB) algorithm named ORB using three-patch and local gray difference (ORB-TPLGD). ORB takes a breakthrough in real-time aspect. However, subtle changes of the image may greatly affect its final binary description. In this paper, the feature description generation is focused. On one hand, instead of pixel patch pairs comparison method used in present ORB algorithm, a three-pixel patch group comparison method is adopted to generate the binary string. In each group, the gray value of the main patch is compared with that of the other two companion patches to determine the corresponding bit of the binary description. On the other hand, the present ORB algorithm simply uses the gray size comparison between pixel patch pairs, while ignoring the information of the gray difference value. In this paper, another binary string based on the gray difference information mentioned above is generated. Finally, the feature fusion method is adopted to combine the binary strings generated in the above two steps to generate a new feature description. Experiment results indicate that our improved ORB algorithm can achieve greater performance than ORB and some other related algorithms. |
format | Online Article Text |
id | pubmed-7070684 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70706842020-03-19 Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference Ma, Chaoqun Hu, Xiaoguang Xiao, Jin Du, Huanchao Zhang, Guofeng Sensors (Basel) Article This paper presents an improved Oriented Features from Accelerated Segment Test (FAST) and Rotated BRIEF (ORB) algorithm named ORB using three-patch and local gray difference (ORB-TPLGD). ORB takes a breakthrough in real-time aspect. However, subtle changes of the image may greatly affect its final binary description. In this paper, the feature description generation is focused. On one hand, instead of pixel patch pairs comparison method used in present ORB algorithm, a three-pixel patch group comparison method is adopted to generate the binary string. In each group, the gray value of the main patch is compared with that of the other two companion patches to determine the corresponding bit of the binary description. On the other hand, the present ORB algorithm simply uses the gray size comparison between pixel patch pairs, while ignoring the information of the gray difference value. In this paper, another binary string based on the gray difference information mentioned above is generated. Finally, the feature fusion method is adopted to combine the binary strings generated in the above two steps to generate a new feature description. Experiment results indicate that our improved ORB algorithm can achieve greater performance than ORB and some other related algorithms. MDPI 2020-02-12 /pmc/articles/PMC7070684/ /pubmed/32059395 http://dx.doi.org/10.3390/s20040975 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ma, Chaoqun Hu, Xiaoguang Xiao, Jin Du, Huanchao Zhang, Guofeng Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference |
title | Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference |
title_full | Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference |
title_fullStr | Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference |
title_full_unstemmed | Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference |
title_short | Improved ORB Algorithm Using Three-Patch Method and Local Gray Difference |
title_sort | improved orb algorithm using three-patch method and local gray difference |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070684/ https://www.ncbi.nlm.nih.gov/pubmed/32059395 http://dx.doi.org/10.3390/s20040975 |
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