Intelligent droplet tracking with correlation filters for digital microfluidics

文献类型： 外文期刊

第一作者： Li, Libin

作者： Li, Libin;Gu, Zhen;Zhou, Jia-Le;Yan, Bingyong;Wang, Hui-Feng;Kong, Cong;Wang, Hua

作者机构：

关键词： Digital microfluidics; Correlation filter trackers; Machine vision; Reaction kinetics; Colorimetric assay

期刊名称：CHINESE CHEMICAL LETTERS （ 影响因子：8.455； 五年影响因子：5.935 ）

ISSN： 1001-8417

年卷期： 2021 年 32 卷 11 期

页码：

收录情况： SCI

摘要： Tracking the movement of droplets in digital microfluidics is essential to improve its control stability and obtain dynamic information for its applications such as point-of-care testing, environment monitoring and chemical synthesis. Herein, an intelligent, accurate and fast droplet tracking method based on machine vision is developed for applications of digital microfluidics. To continuously recognize the transparent droplets in real-time and avoid the interferes from background patterns or inhomogeneous illumination, we introduced the correlation filter tracker, enabling online learning of the multi-features of the droplets in Fourier domain. Results show the proposed droplet tracking method could accurately locate the droplets. We also demonstrated the capacity of the proposed method for estimation of the droplet velocity as faster as 20 mm/s, and its application in online monitoring the Griess reaction for both colorimetric assay of nitrite and study of reaction kinetics. (C) 2021 Published by Elsevier B.V. on behalf of Chinese Chemical Society and Institute of Materia Medica, Chinese Academy of Medical Sciences.

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