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Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network

In this paper, a multidisciplinary cross-fusion of bionics, robotics, computer vision, and cloud service networks was used as a research platform to study wide-field bionic compound eye target recognition and detection from multiple perspectives. The current research status of wide-field bionic comp...

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Autores principales: Han, Yibo, Li, Xia, Li, XiaoCui, Zhou, Zhangbing, Li, Jinshuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9014010/
https://www.ncbi.nlm.nih.gov/pubmed/35445001
http://dx.doi.org/10.3389/fbioe.2022.865130
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author Han, Yibo
Li, Xia
Li, XiaoCui
Zhou, Zhangbing
Li, Jinshuo
author_facet Han, Yibo
Li, Xia
Li, XiaoCui
Zhou, Zhangbing
Li, Jinshuo
author_sort Han, Yibo
collection PubMed
description In this paper, a multidisciplinary cross-fusion of bionics, robotics, computer vision, and cloud service networks was used as a research platform to study wide-field bionic compound eye target recognition and detection from multiple perspectives. The current research status of wide-field bionic compound-eye target recognition and detection was analyzed, and improvement directions were proposed. The surface microlens array arrangement was designed, and the spaced surface bionic compound eye design principle cloud service network model was established for the adopted spaced-type circumferential hierarchical microlens array arrangement. In order to realize the target localization of the compound eye system, the content of each step of the localization scheme was discussed in detail. The distribution of virtual spherical targets was designed by using the subdivision of the positive icosahedron to ensure the uniformity of the targets. The spot image was pre-processed to achieve spot segmentation. The energy symmetry-based spot center localization algorithm was explored and its localization effect was verified. A suitable spatial interpolation method was selected to establish the mapping relationship between target angle and spot coordinates. An experimental platform of wide-field bionic compound eye target recognition and detection system was acquired. A super-resolution reconstruction algorithm combining pixel rearrangement and an improved iterative inverse projection method was used for image processing. The model was trained and evaluated in terms of detection accuracy, leakage rate, time overhead, and other evaluation indexes, and the test results showed that the cloud service network-based wide-field bionic compound eye target recognition and detection performs well in terms of detection accuracy and leakage rate. Compared with the traditional algorithm, the correct rate of the algorithm was increased by 21.72%. Through the research of this paper, the wide-field bionic compound eye target recognition and detection and cloud service network were organically provide more technical support for the design of wide-field bionic compound eye target recognition and detection system.
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spelling pubmed-90140102022-04-19 Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network Han, Yibo Li, Xia Li, XiaoCui Zhou, Zhangbing Li, Jinshuo Front Bioeng Biotechnol Bioengineering and Biotechnology In this paper, a multidisciplinary cross-fusion of bionics, robotics, computer vision, and cloud service networks was used as a research platform to study wide-field bionic compound eye target recognition and detection from multiple perspectives. The current research status of wide-field bionic compound-eye target recognition and detection was analyzed, and improvement directions were proposed. The surface microlens array arrangement was designed, and the spaced surface bionic compound eye design principle cloud service network model was established for the adopted spaced-type circumferential hierarchical microlens array arrangement. In order to realize the target localization of the compound eye system, the content of each step of the localization scheme was discussed in detail. The distribution of virtual spherical targets was designed by using the subdivision of the positive icosahedron to ensure the uniformity of the targets. The spot image was pre-processed to achieve spot segmentation. The energy symmetry-based spot center localization algorithm was explored and its localization effect was verified. A suitable spatial interpolation method was selected to establish the mapping relationship between target angle and spot coordinates. An experimental platform of wide-field bionic compound eye target recognition and detection system was acquired. A super-resolution reconstruction algorithm combining pixel rearrangement and an improved iterative inverse projection method was used for image processing. The model was trained and evaluated in terms of detection accuracy, leakage rate, time overhead, and other evaluation indexes, and the test results showed that the cloud service network-based wide-field bionic compound eye target recognition and detection performs well in terms of detection accuracy and leakage rate. Compared with the traditional algorithm, the correct rate of the algorithm was increased by 21.72%. Through the research of this paper, the wide-field bionic compound eye target recognition and detection and cloud service network were organically provide more technical support for the design of wide-field bionic compound eye target recognition and detection system. Frontiers Media S.A. 2022-04-04 /pmc/articles/PMC9014010/ /pubmed/35445001 http://dx.doi.org/10.3389/fbioe.2022.865130 Text en Copyright © 2022 Han, Li, Li, Zhou and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Han, Yibo
Li, Xia
Li, XiaoCui
Zhou, Zhangbing
Li, Jinshuo
Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network
title Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network
title_full Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network
title_fullStr Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network
title_full_unstemmed Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network
title_short Recognition and Detection of Wide Field Bionic Compound Eye Target Based on Cloud Service Network
title_sort recognition and detection of wide field bionic compound eye target based on cloud service network
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9014010/
https://www.ncbi.nlm.nih.gov/pubmed/35445001
http://dx.doi.org/10.3389/fbioe.2022.865130
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