Computer vision-based on-site estimation of contact angle from 3D reconstruction of droplets

• Published in: IEEE transactions on instrumentation and measurement p. 1
• Main Authors: Kumar, Akash, Chandraprakash, C.
• Format: Journal Article
• Language: English
• Published: IEEE 16.08.2023
• Subjects: 3D transparent reconstruction; Cameras; Image reconstruction; liquid contact angle; Optical surface waves; semantic seg-mentation; Semiconductor device measurement; shape-from-silhouette; Substrates; Surface reconstruction; Three-dimensional displays; U-Net
• ISSN: 0018-9456; 1557-9662
• DOI: 10.1109/TIM.2023.3291797

Current methods to measure the contact angle require orthogonal imaging of the droplet and substrate. We have developed a novel computer vision-based technique to reconstruct the surface of the 3D transparent microdroplet from non-orthogonal images and determined the contact angle using custom-made equipment comprising a smartphone camera and macro lens. After estimating the intrinsic and extrinsic camera parameters using a printed pattern, the EfficientNet-B4 model of U-Net CNN architecture was used to extract silhouettes of droplets from images using semantic segmentation. Finally, the shape-from-silhouette method was employed involving a space carving algorithm to estimate the visual hull containing the droplet volume. Comparison with measurements from a state-of-the-art goniometer of static and dynamic contact angles on various substrates using a standard goniometer revealed an average error of 4%. Our method, using non-orthogonal images, was found to be successful for the on-site measurement of static and dynamic contact angles, as well as 3D reconstruction of the transparent droplets.