A spectrum selection method based on SNR for the machine vision measurement of large hot forgings
A spectrum selection method based on SNR for the machine vision measurement of large hot forgings
复制标题
基于信噪比的大型热锻件机器视觉测量光谱选择方法
DOI：
10.1016/j.ijleo.2015.09.110
复制
发表时间：
2015-12
期刊：
影响因子：
3.1
通讯作者：
Kai Zhao
中科院分区：
文献类型：
--
作者：
Chi Zhang;Jinghao Yang;Lingli Wang;Kai Zhao
机器视觉已经被用于测量大型热锻件的尺寸。然而，由于锻件自身辐射较强，图像质量较差，使得特征提取的稳健性和高效性较差。因此，为了获得大型热锻件的清晰图像，本文提出了一种基于信噪比的光谱选择方法。首先，根据成像理论建立了图像感兴趣特征的信噪比模型。然后，估算了不同温度下锻件图像的信噪比，并讨论了在一定信噪比下的波长范围，为获取大型热锻件的清晰图像提供了必要的参考。选用截止波长的短通滤光片在锻造车间进行了实验研究。实验结果表明，基于信噪比的光谱选择方法对于利用机器视觉技术测量大型热锻件尺寸是有效的。
Machine vision has been already used in measuring the dimensions of large hot forgings. However, the features of forgings are hard to extract robustness and efficiency, because of poor image quality caused by strong self-emitted radiation of hot forging. Therefore, in order to obtain clear images of large hot forgings, a spectrum selection method based on SNR is proposed in this paper. First, the SNR model of interest features in images is established according to theory of image formation. Then, the SNRs of forging image in different temperature are estimated, and the wavelength range for a certain SNR is discussed, which can provide a necessary reference for capturing clear images of large hot forgings. A short-pass filter of a cut-off wavelength is selected to conduct experiments in forging workshop. Experimental results indicate that the spectrum selection method based on SNR is effective for measuring the dimensions of large hot forgings with machine vision technology.
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DOI：
10.1117/12.807046
发表时间：
2008-12
期刊：
--
影响因子：
--
作者：
Chunhai Hu;Xiaoxue Song
通讯作者：
Chunhai Hu;Xiaoxue Song
影响因子：
6.3
作者：
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通讯作者：
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影响因子：
5.6
作者：
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通讯作者：
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DOI：
--
发表时间：
2006
期刊：
Journal of Plasticity Engineering
影响因子：
--
作者：
Xu Yong-dong
通讯作者：
Xu Yong-dong
影响因子：
0.3
作者：
T. J. Nye;A. M. Elbadan;G. Bone
通讯作者：
T. J. Nye;A. M. Elbadan;G. Bone