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Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment

For some measurement and detection applications based on video (sequence images), if the exposure time of camera is not suitable with the motion speed of the photographed target, fuzzy edges will be produced in the image, and some poor lighting condition will aggravate this edge blur phenomena. Espe...

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Detalles Bibliográficos
Autores principales: Han, Fangfang, Liu, Bin, Zhu, Junchao, Zhang, Baofeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359385/
https://www.ncbi.nlm.nih.gov/pubmed/30654538
http://dx.doi.org/10.3390/s19020343
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author Han, Fangfang
Liu, Bin
Zhu, Junchao
Zhang, Baofeng
author_facet Han, Fangfang
Liu, Bin
Zhu, Junchao
Zhang, Baofeng
author_sort Han, Fangfang
collection PubMed
description For some measurement and detection applications based on video (sequence images), if the exposure time of camera is not suitable with the motion speed of the photographed target, fuzzy edges will be produced in the image, and some poor lighting condition will aggravate this edge blur phenomena. Especially, the existence of noise in industrial field environment makes the extraction of fuzzy edges become a more difficult problem when analyzing the posture of a high-speed moving target. Because noise and edge are always both the kind of high-frequency information, it is difficult to make trade-offs only by frequency bands. In this paper, a noise-tolerant edge detection method based on the correlation relationship between layers of wavelet transform coefficients is proposed. The goal of the paper is not to recover a clean image from a noisy observation, but to make a trade-off judgment for noise and edge signal directly according to the characteristics of wavelet transform coefficients, to realize the extraction of edge information from a noisy image directly. According to the wavelet coefficients tree and the Lipschitz exponent property of noise, the idea of neural network activation function is adopted to design the activation judgment method of wavelet coefficients. Then the significant wavelet coefficients can be retained. At the same time, the non-significant coefficients were removed according to the method of judgment of isolated coefficients. On the other hand, based on the design of Daubechies orthogonal compactly-supported wavelet filter, rational coefficients wavelet filters can be designed by increasing free variables. By reducing the vanishing moments of wavelet filters, more high-frequency information can be retained in the wavelet transform fields, which is benefit to the application of edge detection. For a noisy image of high-speed moving targets with fuzzy edges, by using the length 8-4 rational coefficients biorthogonal wavelet filters and the algorithm proposed in this paper, edge information could be detected clearly. Results of multiple groups of comparative experiments have shown that the edge detection effect of the proposed algorithm in this paper has the obvious superiority.
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spelling pubmed-63593852019-02-06 Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment Han, Fangfang Liu, Bin Zhu, Junchao Zhang, Baofeng Sensors (Basel) Article For some measurement and detection applications based on video (sequence images), if the exposure time of camera is not suitable with the motion speed of the photographed target, fuzzy edges will be produced in the image, and some poor lighting condition will aggravate this edge blur phenomena. Especially, the existence of noise in industrial field environment makes the extraction of fuzzy edges become a more difficult problem when analyzing the posture of a high-speed moving target. Because noise and edge are always both the kind of high-frequency information, it is difficult to make trade-offs only by frequency bands. In this paper, a noise-tolerant edge detection method based on the correlation relationship between layers of wavelet transform coefficients is proposed. The goal of the paper is not to recover a clean image from a noisy observation, but to make a trade-off judgment for noise and edge signal directly according to the characteristics of wavelet transform coefficients, to realize the extraction of edge information from a noisy image directly. According to the wavelet coefficients tree and the Lipschitz exponent property of noise, the idea of neural network activation function is adopted to design the activation judgment method of wavelet coefficients. Then the significant wavelet coefficients can be retained. At the same time, the non-significant coefficients were removed according to the method of judgment of isolated coefficients. On the other hand, based on the design of Daubechies orthogonal compactly-supported wavelet filter, rational coefficients wavelet filters can be designed by increasing free variables. By reducing the vanishing moments of wavelet filters, more high-frequency information can be retained in the wavelet transform fields, which is benefit to the application of edge detection. For a noisy image of high-speed moving targets with fuzzy edges, by using the length 8-4 rational coefficients biorthogonal wavelet filters and the algorithm proposed in this paper, edge information could be detected clearly. Results of multiple groups of comparative experiments have shown that the edge detection effect of the proposed algorithm in this paper has the obvious superiority. MDPI 2019-01-16 /pmc/articles/PMC6359385/ /pubmed/30654538 http://dx.doi.org/10.3390/s19020343 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Han, Fangfang
Liu, Bin
Zhu, Junchao
Zhang, Baofeng
Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment
title Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment
title_full Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment
title_fullStr Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment
title_full_unstemmed Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment
title_short Algorithm Design for Edge Detection of High-Speed Moving Target Image under Noisy Environment
title_sort algorithm design for edge detection of high-speed moving target image under noisy environment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359385/
https://www.ncbi.nlm.nih.gov/pubmed/30654538
http://dx.doi.org/10.3390/s19020343
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