期刊
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
卷 71, 期 -, 页码 -出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2021.3129216
关键词
Image segmentation; Volume measurement; Organic light emitting diodes; Image reconstruction; Stereo vision; Level set; Ultrasonic variables measurement; 3-D reconstruction; flying droplet measurement; level set; stereo vision
资金
- National Key Research and Development Program of China [2018YFA0703203]
- National Natural Science Foundation of China [51975236]
- Research and Development Program in Key Areas of Guangdong Province [2019B010924005]
This article proposes an accurate measurement method for the volume of flying droplets based on stereo vision. The method uses a technique for acquiring high-resolution droplet images from multiple viewpoints and an accurate binocular droplet image segmentation algorithm to reconstruct and calculate the droplet volume without any symmetry assumptions. The results show a high measurement accuracy and low relative standard uncertainty.
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 article, 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%.
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