A DNN-Based UVI Calculation Method Using Representative Color Information of Sun Object Images

As outdoor activities are necessary for maintaining our health, research interest in environmental conditions such as the weather, atmosphere, and ultraviolet (UV) radiation is increasing. In particular, UV radiation, which can benefit or harm the human body depending on the degree of exposure, is r...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Deog-Hyeon Ga, Seung-Taek Oh, Jae-Hyun Lim
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	UVI UV index DNN sky image representative color Mask R-CNN Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/3185fc7aaca6426fae90f1bc55829873
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:3185fc7aaca6426fae90f1bc55829873
record_format	dspace
spelling	oai:doaj.org-article:3185fc7aaca6426fae90f1bc558298732021-11-25T18:59:09ZA DNN-Based UVI Calculation Method Using Representative Color Information of Sun Object Images10.3390/s212277661424-8220https://doaj.org/article/3185fc7aaca6426fae90f1bc558298732021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7766https://doaj.org/toc/1424-8220As outdoor activities are necessary for maintaining our health, research interest in environmental conditions such as the weather, atmosphere, and ultraviolet (UV) radiation is increasing. In particular, UV radiation, which can benefit or harm the human body depending on the degree of exposure, is recognized as an essential environmental factor that needs to be identified. However, unlike the weather and atmospheric conditions, which can be identified to some extent by the naked eye, UV radiation corresponds to wavelength bands that humans cannot recognize; hence, the intensity of UV radiation cannot be measured. Recently, although devices and sensors that can measure UV radiation have been launched, it is very difficult for ordinary users to acquire ambient UV radiation information directly because of the cost and inconvenience caused by operating separate devices. Herein, a deep neural network (DNN)-based ultraviolet index (UVI) calculation method is proposed using representative color information of sun object images. First, Mask-region-based convolutional neural networks (R-CNN) are applied to sky images to extract sun object regions and then detect the representative color of the sun object regions. Then, a deep learning model is constructed to calculate the UVI by inputting RGB color values, which are representative colors detected later along with the altitude angle and azimuth of the sun at that time. After selecting each day of spring and autumn, the performance of the proposed method was tested, and it was confirmed that accurate UVI could be calculated within a range of mean absolute error of 0.3.Deog-Hyeon GaSeung-Taek OhJae-Hyun LimMDPI AGarticleUVIUV indexDNNsky imagerepresentative colorMask R-CNNChemical technologyTP1-1185ENSensors, Vol 21, Iss 7766, p 7766 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	UVI UV index DNN sky image representative color Mask R-CNN Chemical technology TP1-1185
spellingShingle	UVI UV index DNN sky image representative color Mask R-CNN Chemical technology TP1-1185 Deog-Hyeon Ga Seung-Taek Oh Jae-Hyun Lim A DNN-Based UVI Calculation Method Using Representative Color Information of Sun Object Images
description	As outdoor activities are necessary for maintaining our health, research interest in environmental conditions such as the weather, atmosphere, and ultraviolet (UV) radiation is increasing. In particular, UV radiation, which can benefit or harm the human body depending on the degree of exposure, is recognized as an essential environmental factor that needs to be identified. However, unlike the weather and atmospheric conditions, which can be identified to some extent by the naked eye, UV radiation corresponds to wavelength bands that humans cannot recognize; hence, the intensity of UV radiation cannot be measured. Recently, although devices and sensors that can measure UV radiation have been launched, it is very difficult for ordinary users to acquire ambient UV radiation information directly because of the cost and inconvenience caused by operating separate devices. Herein, a deep neural network (DNN)-based ultraviolet index (UVI) calculation method is proposed using representative color information of sun object images. First, Mask-region-based convolutional neural networks (R-CNN) are applied to sky images to extract sun object regions and then detect the representative color of the sun object regions. Then, a deep learning model is constructed to calculate the UVI by inputting RGB color values, which are representative colors detected later along with the altitude angle and azimuth of the sun at that time. After selecting each day of spring and autumn, the performance of the proposed method was tested, and it was confirmed that accurate UVI could be calculated within a range of mean absolute error of 0.3.
format	article
author	Deog-Hyeon Ga Seung-Taek Oh Jae-Hyun Lim
author_facet	Deog-Hyeon Ga Seung-Taek Oh Jae-Hyun Lim
author_sort	Deog-Hyeon Ga
title	A DNN-Based UVI Calculation Method Using Representative Color Information of Sun Object Images
title_short	A DNN-Based UVI Calculation Method Using Representative Color Information of Sun Object Images
title_full	A DNN-Based UVI Calculation Method Using Representative Color Information of Sun Object Images
title_fullStr	A DNN-Based UVI Calculation Method Using Representative Color Information of Sun Object Images
title_full_unstemmed	A DNN-Based UVI Calculation Method Using Representative Color Information of Sun Object Images
title_sort	dnn-based uvi calculation method using representative color information of sun object images
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3185fc7aaca6426fae90f1bc55829873
work_keys_str_mv	AT deoghyeonga adnnbaseduvicalculationmethodusingrepresentativecolorinformationofsunobjectimages AT seungtaekoh adnnbaseduvicalculationmethodusingrepresentativecolorinformationofsunobjectimages AT jaehyunlim adnnbaseduvicalculationmethodusingrepresentativecolorinformationofsunobjectimages AT deoghyeonga dnnbaseduvicalculationmethodusingrepresentativecolorinformationofsunobjectimages AT seungtaekoh dnnbaseduvicalculationmethodusingrepresentativecolorinformationofsunobjectimages AT jaehyunlim dnnbaseduvicalculationmethodusingrepresentativecolorinformationofsunobjectimages
_version_	1718410454530785280

A DNN-Based UVI Calculation Method Using Representative Color Information of Sun Object Images

Ejemplares similares