Subpixel localization of optical vortices using artificial neural networks

IF 1.1 4区 工程技术 Q4 INSTRUMENTS & INSTRUMENTATION
A. Popiołek-Masajada, E. Fraczek, Emilia Burnecka
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引用次数: 5

Abstract

Optical vortices are getting attention in modern optical metrology. Because of their unique features, they can be used as precise position markers. In this paper, we show that an artificial neural network can be used to improve vortex localization. A deep neural network with several hidden layers was trained to find subpixel vortex positions on the spiral phase maps. Several thousand training samples, differing by spiral density, its orientation, and vortex position, were generated numerically for teaching purposes. As a result, Best Validation Performance of the order of 10−5 pixel has been reached. To verify the usefulness of the proposed method, a related experiment in the setup of an optical vortex scanning microscope has been reported. It is shown that the vortex can be localized with subpixel accuracy also on experimental phase maps.
基于人工神经网络的光学涡旋亚像素定位
光学涡旋在现代光学计量学中越来越受到重视。由于它们的独特特性,它们可以用作精确的位置标记。在本文中,我们证明了人工神经网络可以用来改进涡流定位。训练了一个具有多个隐藏层的深度神经网络,以在螺旋相位图上找到亚像素涡流位置。为了教学目的,用数字生成了数千个训练样本,这些样本因螺旋密度、方向和涡流位置而异。因此,达到了10−5像素数量级的最佳验证性能。为了验证所提出的方法的有效性,已经报道了在光学涡旋扫描显微镜的设置中的相关实验。结果表明,在实验相位图上,涡流也可以亚像素精度定位。
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来源期刊
Metrology and Measurement Systems
Metrology and Measurement Systems INSTRUMENTS & INSTRUMENTATION-
CiteScore
2.00
自引率
10.00%
发文量
0
审稿时长
6 months
期刊介绍: Contributions are invited on all aspects of the research, development and applications of the measurement science and technology. The list of topics covered includes: theory and general principles of measurement; measurement of physical, chemical and biological quantities; medical measurements; sensors and transducers; measurement data acquisition; measurement signal transmission; processing and data analysis; measurement systems and embedded systems; design, manufacture and evaluation of instruments. The average publication cycle is 6 months.
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