SNR Analysis for Quantitative Comparison of Line Detection Methods

The need for line detection in images is growing rapidly due to its importance in many image processing applications. The selection of an appropriate line detection method is essential for accurate detection of line pixels, but few studies provide an analytical basis for selecting a specific line de...

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Autor principal:	Suyoung Seo
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	error propagation line detection quantitative comparison signal-to-noise ratio Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/3115564cdc9a4e8d82a3b8bebfc4aec6
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id	oai:doaj.org-article:3115564cdc9a4e8d82a3b8bebfc4aec6
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spelling	oai:doaj.org-article:3115564cdc9a4e8d82a3b8bebfc4aec62021-11-11T15:09:29ZSNR Analysis for Quantitative Comparison of Line Detection Methods10.3390/app1121100882076-3417https://doaj.org/article/3115564cdc9a4e8d82a3b8bebfc4aec62021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10088https://doaj.org/toc/2076-3417The need for line detection in images is growing rapidly due to its importance in many image processing applications. The selection of an appropriate line detection method is essential for accurate detection of line pixels, but few studies provide an analytical basis for selecting a specific line detection method. In this study, to solve the problem, a method to analytically determine the signal-to-noise ratio (SNR) of line detection methods is proposed. Three line detection methods were selected for comparison: edge-detection (ED)-based, second derivative (SD)-based, and the sum of gradient angle differences (SGAD)-based line detection methods. Then, this study quantifies the SNR of the three line detectors through error propagation and signal noise coupling. In addition, the derived SNRs are graphically visualized to explicitly compare the performance of line detectors. Then, the quantified SNRs were validated by showing that they are highly correlated with the completeness and correctness observed in the experiment with a set of natural images. The experimental results show that the proposed SNR analysis can be used to select or design a suitable line detector.Suyoung SeoMDPI AGarticleerror propagationline detectionquantitative comparisonsignal-to-noise ratioTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10088, p 10088 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	error propagation line detection quantitative comparison signal-to-noise ratio Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	error propagation line detection quantitative comparison signal-to-noise ratio Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Suyoung Seo SNR Analysis for Quantitative Comparison of Line Detection Methods
description	The need for line detection in images is growing rapidly due to its importance in many image processing applications. The selection of an appropriate line detection method is essential for accurate detection of line pixels, but few studies provide an analytical basis for selecting a specific line detection method. In this study, to solve the problem, a method to analytically determine the signal-to-noise ratio (SNR) of line detection methods is proposed. Three line detection methods were selected for comparison: edge-detection (ED)-based, second derivative (SD)-based, and the sum of gradient angle differences (SGAD)-based line detection methods. Then, this study quantifies the SNR of the three line detectors through error propagation and signal noise coupling. In addition, the derived SNRs are graphically visualized to explicitly compare the performance of line detectors. Then, the quantified SNRs were validated by showing that they are highly correlated with the completeness and correctness observed in the experiment with a set of natural images. The experimental results show that the proposed SNR analysis can be used to select or design a suitable line detector.
format	article
author	Suyoung Seo
author_facet	Suyoung Seo
author_sort	Suyoung Seo
title	SNR Analysis for Quantitative Comparison of Line Detection Methods
title_short	SNR Analysis for Quantitative Comparison of Line Detection Methods
title_full	SNR Analysis for Quantitative Comparison of Line Detection Methods
title_fullStr	SNR Analysis for Quantitative Comparison of Line Detection Methods
title_full_unstemmed	SNR Analysis for Quantitative Comparison of Line Detection Methods
title_sort	snr analysis for quantitative comparison of line detection methods
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3115564cdc9a4e8d82a3b8bebfc4aec6
work_keys_str_mv	AT suyoungseo snranalysisforquantitativecomparisonoflinedetectionmethods
_version_	1718437119163105280

SNR Analysis for Quantitative Comparison of Line Detection Methods

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