Dynamic refractive index measurement method for droplets based on digital image correlation and inverse method

Abstract The measurement and analysis of the refractive index of droplets is a crucial aspect of exploring liquid compositions and studying the physicochemical properties of liquids. The optical measurement techniques currently used to determine the refractive index of transparent droplets are impeded by the substantial liquid volume requirements, making the accurate measurement of the refractive index of micro-scale droplets a significant challenge. To address this issue, the present study proposes a non-contact method for measuring the refractive index of droplets based on digital image correlation (DIC) and inverse method, to achieve high-precision analysis of the refractive index and concentration of micro-droplets. The proposed method designs a dual-module optical imaging system to measure the refractive index of transparent droplets precisely. A physical model is constructed to derive the mathematical mapping between the droplet’s refractive index, image displacement, and geometric contour. The segmentation-aided DIC method enables subpixel-level full-field displacement vector measurements, providing key data for the refractive index inversion model. A side-view camera captures the droplet’s contour, and edge detection algorithm extracts feature coordinates. A synchronization calibration method aligns the spatial coordinates of the dual imaging systems. Finally, the refractive index parameters are inverted using experimental data and a particle swarm optimization algorithm. Experimental results demonstrate high precision in measuring the refractive index of micro-scale droplets.

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Publication Details

Journal
Measurement Science and Technology
Published
2025-06-02
DOI
https://doi.org/10.1088/1361-6501/addf6a
Citations
1
Primary Topic
Advanced Measurement and Detection Methods
Type
article
Field-Weighted Citation Impact
0.73

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Dynamic refractive index measurement method for droplets based on digital image correlation and inverse method

Xinyun Tan, Jubing Chen, Shigui Yan, Haoyu Zhang et al.
1 citations
Measurement Science and Technology
Advanced Measurement and Detection Methods
0.73
article

Dynamic refractive index measurement method for droplets based on digital image correlation and inverse method

Xinyun Tan, Jubing Chen, Shigui Yan, Haoyu Zhang, Chen Sun
article en
1 citations

Abstract

Abstract The measurement and analysis of the refractive index of droplets is a crucial aspect of exploring liquid compositions and studying the physicochemical properties of liquids. The optical measurement techniques currently used to determine the refractive index of transparent droplets are impeded by the substantial liquid volume requirements, making the accurate measurement of the refractive index of micro-scale droplets a significant challenge. To address this issue, the present study proposes a non-contact method for measuring the refractive index of droplets based on digital image correlation (DIC) and inverse method, to achieve high-precision analysis of the refractive index and concentration of micro-droplets. The proposed method designs a dual-module optical imaging system to measure the refractive index of transparent droplets precisely. A physical model is constructed to derive the mathematical mapping between the droplet’s refractive index, image displacement, and geometric contour. The segmentation-aided DIC method enables subpixel-level full-field displacement vector measurements, providing key data for the refractive index inversion model. A side-view camera captures the droplet’s contour, and edge detection algorithm extracts feature coordinates. A synchronization calibration method aligns the spatial coordinates of the dual imaging systems. Finally, the refractive index parameters are inverted using experimental data and a particle swarm optimization algorithm. Experimental results demonstrate high precision in measuring the refractive index of micro-scale droplets.

Measurement Science and TechnologyVol. 36(6)
Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 28%
Advanced Measurement and Detection Methods
0.73
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