文献类型：期刊文献

中文题名：Intelligent droplet tracking with correlation filters for digital microfluidics

作者：Libin Li[1];Zhen Gu[1];Jia-Le Zhou[1];Bingyong Yan[1];Cong Kong[2];Hua Wang[3];Hui-Feng Wang[1]

机构：[1]Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education,East China University of Science and Technology,Shanghai 200237,China;[2]Key Laboratory of East China Sea Fishery Resources Exploitation,Ministry of Agriculture and Rural Affairs,East China Sea Fisheries Research Institute,Chinese Academy of Fishery Sciences,Shanghai 200090,China;[3]Department of Laboratory Medicine,Renji Hospital,School of Medicine,Shanghai Jiao Tong University,Shanghai 200137,China

年份：2021

卷号：32

期号：11

起止页码：3416

中文期刊名：Chinese Chemical Letters

外文期刊名：中国化学快报（英文版）

收录：CSTPCD;;Scopus;CSCD:【CSCD2021_2022】；PubMed;

基金：the financial support from the National Natural Science Foundation of China(Nos.31701698,81972017);Shanghai Key Laboratory of Forensic Medicine,Academy of Forensic Science(No.KF1910);Shanghai Shenkang Hospital Development Center to promote clinical skills and clinical innovation ability in municipal hospitals of the Three-year Action Plan Project(No.SHDC2020CR3006A).

语种：英文

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

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.