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Accurate Stereo-Vision-Based Flying Droplet Volume Measurement Method
- Source :
- IEEE Transactions on Instrumentation and Measurement. 71:1-16
- Publication Year :
- 2022
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2022.
-
Abstract
- Accurate volume measurement of flying droplets in the Mura-free manufacturing of inkjet printed organic light-emitting diodes (IJP OLEDs) remains a challenge due to the micrometer scale and high speeds of the droplets. Most existing vision-based methods pay little attention to image segmentation and estimate the droplet volume based on a symmetry assumption, which yields poor accuracy, especially for droplets with an unknown shape. In this paper, an accurate measurement method for flying droplet volume based on stereo vision is proposed. First, an image acquisition technique based on stereo vision and synchronous triggering is used to obtain multiview high-resolution droplet images. Then, an accurate binocular droplet image segmentation algorithm is proposed to segment the images with different degrees of blur to achieve similar accuracy. Finally, a polar-coordinate-Hermite-interpolation-based droplet reconstruction (PHDR) algorithm is proposed to reconstruct droplets and to calculate volume on the basis of the contours obtained by the binocular droplet image segmentation algorithm without any symmetry assumptions. The droplet measurement system (DMS) is set up, and a series of experiments are conducted to verify the performance of the proposed method. The results show the advantages of our algorithms, that the volume measurement accuracy is ±3% and that the relative standard uncertainty is better than 2.1%.
- Subjects :
- Series (mathematics)
Basis (linear algebra)
business.industry
Computer science
System of measurement
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
Volume (computing)
Image segmentation
Symmetry (physics)
Physics::Fluid Dynamics
Set (abstract data type)
Stereopsis
Computer Science::Computer Vision and Pattern Recognition
Hardware_INTEGRATEDCIRCUITS
Computer vision
Artificial intelligence
Hardware_ARITHMETICANDLOGICSTRUCTURES
Electrical and Electronic Engineering
business
Instrumentation
Subjects
Details
- ISSN :
- 15579662 and 00189456
- Volume :
- 71
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Instrumentation and Measurement
- Accession number :
- edsair.doi...........e37744d1a6fdf7ea9014d576469121df