Spot Detection for Laser Sensors Based on Annular Convolution Filtering

Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of...
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Autor*in:	Lingjiang Li [verfasserIn] Maolin Li [verfasserIn] Weijun Sun [verfasserIn] Zhenni Li [verfasserIn] Zuyuan Yang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2023

Schlagwörter:	laser sensor spot detection image processing ACF

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 23(2023), 8, p 3891
Übergeordnetes Werk:	volume:23 ; year:2023 ; number:8, p 3891

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s23083891

Katalog-ID:	DOAJ089775856

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520			\|a Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of interference, we propose a novel method called annular convolution filtering (ACF). In our method, the region of interest (ROI) in the spot image is first searched by using the statistical properties of pixels. Then, the annular convolution strip is constructed based on the energy attenuation property of the laser and the convolution operation is performed in the ROI of the spot image. Finally, a feature similarity index is designed to estimate the parameters of the laser spot. Experiments on three datasets with different kinds of background light show the advantages of our ACF method, with comparison to the theoretical method based on international standard, the practical method used in the market products, and the recent benchmark methods AAMED and ALS.
650		4	\|a laser sensor
650		4	\|a spot detection
650		4	\|a image processing
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spelling	10.3390/s23083891 doi (DE-627)DOAJ089775856 (DE-599)DOAJ805c319380884ad085f8267e01dd5e1a DE-627 ger DE-627 rakwb eng TP1-1185 Lingjiang Li verfasserin aut Spot Detection for Laser Sensors Based on Annular Convolution Filtering 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of interference, we propose a novel method called annular convolution filtering (ACF). In our method, the region of interest (ROI) in the spot image is first searched by using the statistical properties of pixels. Then, the annular convolution strip is constructed based on the energy attenuation property of the laser and the convolution operation is performed in the ROI of the spot image. Finally, a feature similarity index is designed to estimate the parameters of the laser spot. Experiments on three datasets with different kinds of background light show the advantages of our ACF method, with comparison to the theoretical method based on international standard, the practical method used in the market products, and the recent benchmark methods AAMED and ALS. laser sensor spot detection image processing ACF Chemical technology Maolin Li verfasserin aut Weijun Sun verfasserin aut Zhenni Li verfasserin aut Zuyuan Yang verfasserin aut In Sensors MDPI AG, 2003 23(2023), 8, p 3891 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:23 year:2023 number:8, p 3891 https://doi.org/10.3390/s23083891 kostenfrei https://doaj.org/article/805c319380884ad085f8267e01dd5e1a kostenfrei https://www.mdpi.com/1424-8220/23/8/3891 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 8, p 3891
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allfieldsGer	10.3390/s23083891 doi (DE-627)DOAJ089775856 (DE-599)DOAJ805c319380884ad085f8267e01dd5e1a DE-627 ger DE-627 rakwb eng TP1-1185 Lingjiang Li verfasserin aut Spot Detection for Laser Sensors Based on Annular Convolution Filtering 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of interference, we propose a novel method called annular convolution filtering (ACF). In our method, the region of interest (ROI) in the spot image is first searched by using the statistical properties of pixels. Then, the annular convolution strip is constructed based on the energy attenuation property of the laser and the convolution operation is performed in the ROI of the spot image. Finally, a feature similarity index is designed to estimate the parameters of the laser spot. Experiments on three datasets with different kinds of background light show the advantages of our ACF method, with comparison to the theoretical method based on international standard, the practical method used in the market products, and the recent benchmark methods AAMED and ALS. laser sensor spot detection image processing ACF Chemical technology Maolin Li verfasserin aut Weijun Sun verfasserin aut Zhenni Li verfasserin aut Zuyuan Yang verfasserin aut In Sensors MDPI AG, 2003 23(2023), 8, p 3891 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:23 year:2023 number:8, p 3891 https://doi.org/10.3390/s23083891 kostenfrei https://doaj.org/article/805c319380884ad085f8267e01dd5e1a kostenfrei https://www.mdpi.com/1424-8220/23/8/3891 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 8, p 3891
allfieldsSound	10.3390/s23083891 doi (DE-627)DOAJ089775856 (DE-599)DOAJ805c319380884ad085f8267e01dd5e1a DE-627 ger DE-627 rakwb eng TP1-1185 Lingjiang Li verfasserin aut Spot Detection for Laser Sensors Based on Annular Convolution Filtering 2023 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of interference, we propose a novel method called annular convolution filtering (ACF). In our method, the region of interest (ROI) in the spot image is first searched by using the statistical properties of pixels. Then, the annular convolution strip is constructed based on the energy attenuation property of the laser and the convolution operation is performed in the ROI of the spot image. Finally, a feature similarity index is designed to estimate the parameters of the laser spot. Experiments on three datasets with different kinds of background light show the advantages of our ACF method, with comparison to the theoretical method based on international standard, the practical method used in the market products, and the recent benchmark methods AAMED and ALS. laser sensor spot detection image processing ACF Chemical technology Maolin Li verfasserin aut Weijun Sun verfasserin aut Zhenni Li verfasserin aut Zuyuan Yang verfasserin aut In Sensors MDPI AG, 2003 23(2023), 8, p 3891 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:23 year:2023 number:8, p 3891 https://doi.org/10.3390/s23083891 kostenfrei https://doaj.org/article/805c319380884ad085f8267e01dd5e1a kostenfrei https://www.mdpi.com/1424-8220/23/8/3891 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 23 2023 8, p 3891
language	English
source	In Sensors 23(2023), 8, p 3891 volume:23 year:2023 number:8, p 3891
sourceStr	In Sensors 23(2023), 8, p 3891 volume:23 year:2023 number:8, p 3891
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	laser sensor spot detection image processing ACF Chemical technology
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container_title	Sensors
authorswithroles_txt_mv	Lingjiang Li @@aut@@ Maolin Li @@aut@@ Weijun Sun @@aut@@ Zhenni Li @@aut@@ Zuyuan Yang @@aut@@
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callnumber-first	T - Technology
author	Lingjiang Li
spellingShingle	Lingjiang Li misc TP1-1185 misc laser sensor misc spot detection misc image processing misc ACF misc Chemical technology Spot Detection for Laser Sensors Based on Annular Convolution Filtering
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topic_title	TP1-1185 Spot Detection for Laser Sensors Based on Annular Convolution Filtering laser sensor spot detection image processing ACF
topic	misc TP1-1185 misc laser sensor misc spot detection misc image processing misc ACF misc Chemical technology
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title	Spot Detection for Laser Sensors Based on Annular Convolution Filtering
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title_full	Spot Detection for Laser Sensors Based on Annular Convolution Filtering
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title_sort	spot detection for laser sensors based on annular convolution filtering
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title_auth	Spot Detection for Laser Sensors Based on Annular Convolution Filtering
abstract	Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of interference, we propose a novel method called annular convolution filtering (ACF). In our method, the region of interest (ROI) in the spot image is first searched by using the statistical properties of pixels. Then, the annular convolution strip is constructed based on the energy attenuation property of the laser and the convolution operation is performed in the ROI of the spot image. Finally, a feature similarity index is designed to estimate the parameters of the laser spot. Experiments on three datasets with different kinds of background light show the advantages of our ACF method, with comparison to the theoretical method based on international standard, the practical method used in the market products, and the recent benchmark methods AAMED and ALS.
abstractGer	Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of interference, we propose a novel method called annular convolution filtering (ACF). In our method, the region of interest (ROI) in the spot image is first searched by using the statistical properties of pixels. Then, the annular convolution strip is constructed based on the energy attenuation property of the laser and the convolution operation is performed in the ROI of the spot image. Finally, a feature similarity index is designed to estimate the parameters of the laser spot. Experiments on three datasets with different kinds of background light show the advantages of our ACF method, with comparison to the theoretical method based on international standard, the practical method used in the market products, and the recent benchmark methods AAMED and ALS.
abstract_unstemmed	Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of interference, we propose a novel method called annular convolution filtering (ACF). In our method, the region of interest (ROI) in the spot image is first searched by using the statistical properties of pixels. Then, the annular convolution strip is constructed based on the energy attenuation property of the laser and the convolution operation is performed in the ROI of the spot image. Finally, a feature similarity index is designed to estimate the parameters of the laser spot. Experiments on three datasets with different kinds of background light show the advantages of our ACF method, with comparison to the theoretical method based on international standard, the practical method used in the market products, and the recent benchmark methods AAMED and ALS.
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title_short	Spot Detection for Laser Sensors Based on Annular Convolution Filtering
url	https://doi.org/10.3390/s23083891 https://doaj.org/article/805c319380884ad085f8267e01dd5e1a https://www.mdpi.com/1424-8220/23/8/3891 https://doaj.org/toc/1424-8220
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