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A robust bitmap-based real-time position tracking algorithm for rats in radial arm maze tests
This paper aims to develop a position tracking algorithm by which a rat in a radial arm maze can be accurately located in real time. An infrared (IR) night-vision camera was hung above the maze to capture IR images of the rat. The IR images were binarized and then duplicated for subsequent intersect...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8599520/ https://www.ncbi.nlm.nih.gov/pubmed/34789865 http://dx.doi.org/10.1038/s41598-021-01974-0 |
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author | Chen, Chi-Chun Hong, Liang-Jyun Wang, Jian-Yong Chang, Ching-Ping |
author_facet | Chen, Chi-Chun Hong, Liang-Jyun Wang, Jian-Yong Chang, Ching-Ping |
author_sort | Chen, Chi-Chun |
collection | PubMed |
description | This paper aims to develop a position tracking algorithm by which a rat in a radial arm maze can be accurately located in real time. An infrared (IR) night-vision camera was hung above the maze to capture IR images of the rat. The IR images were binarized and then duplicated for subsequent intersection and opening operations. Due to simple operations and a high robustness against the noise spots formed by the droppings of the rat, it took just minutes to process more than 9000 frames, and an accuracy above 99% was reached as well. The maze was intruded by an experimenter to further test the robustness, and the accuracy slightly fell to 98%. For comparison purposes, the same experiments were carried out using a pre-trained YOLO v2 model. The YOLO counterpart gave an accuracy beyond 97% in the absence and in the presence of the intruder. In other words, this work slightly outperformed the YOLO counterpart in terms of the accuracy in both cases, which indicates the robustness of this work. However, it took the YOLO counterpart an hour or so to locate a rat contained in the frames, which highlights the contribution of this work. |
format | Online Article Text |
id | pubmed-8599520 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85995202021-11-19 A robust bitmap-based real-time position tracking algorithm for rats in radial arm maze tests Chen, Chi-Chun Hong, Liang-Jyun Wang, Jian-Yong Chang, Ching-Ping Sci Rep Article This paper aims to develop a position tracking algorithm by which a rat in a radial arm maze can be accurately located in real time. An infrared (IR) night-vision camera was hung above the maze to capture IR images of the rat. The IR images were binarized and then duplicated for subsequent intersection and opening operations. Due to simple operations and a high robustness against the noise spots formed by the droppings of the rat, it took just minutes to process more than 9000 frames, and an accuracy above 99% was reached as well. The maze was intruded by an experimenter to further test the robustness, and the accuracy slightly fell to 98%. For comparison purposes, the same experiments were carried out using a pre-trained YOLO v2 model. The YOLO counterpart gave an accuracy beyond 97% in the absence and in the presence of the intruder. In other words, this work slightly outperformed the YOLO counterpart in terms of the accuracy in both cases, which indicates the robustness of this work. However, it took the YOLO counterpart an hour or so to locate a rat contained in the frames, which highlights the contribution of this work. Nature Publishing Group UK 2021-11-17 /pmc/articles/PMC8599520/ /pubmed/34789865 http://dx.doi.org/10.1038/s41598-021-01974-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Chen, Chi-Chun Hong, Liang-Jyun Wang, Jian-Yong Chang, Ching-Ping A robust bitmap-based real-time position tracking algorithm for rats in radial arm maze tests |
title | A robust bitmap-based real-time position tracking algorithm for rats in radial arm maze tests |
title_full | A robust bitmap-based real-time position tracking algorithm for rats in radial arm maze tests |
title_fullStr | A robust bitmap-based real-time position tracking algorithm for rats in radial arm maze tests |
title_full_unstemmed | A robust bitmap-based real-time position tracking algorithm for rats in radial arm maze tests |
title_short | A robust bitmap-based real-time position tracking algorithm for rats in radial arm maze tests |
title_sort | robust bitmap-based real-time position tracking algorithm for rats in radial arm maze tests |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8599520/ https://www.ncbi.nlm.nih.gov/pubmed/34789865 http://dx.doi.org/10.1038/s41598-021-01974-0 |
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