Research On High Precision Contact Angle Measurement Method Based On Machine Vision

Contact angle is a key parameter for determining the surface energy and wettability of solid materials,and its measurement plays an important role in the research of semiconductor materials,it is widely used in modern industry,agriculture,textile industry,medicine and other industries.In recent years,with the development of image processing technology and machine measurement technology,machine vision has become more and more widely used in the field of automatic measurement.The application of machine vision in contact angle measurement can theoretically provide technical support for improving measurement accuracy and efficiency.In this topic,we first completed the construction of a high-precision contact angle measurement software experimental platform.The software realizes image acquisition,image preprocessing,machine measurement,data feedback and other functions based on C++ language and Opencv image processing library function in Visual Studio 2013 integrated development environment,and combines MFC to realize software interface.The software has the characteristics of open source and sharing.Due to the development of the underlying C++ language,the function development is flexible,and optimized,it can add or innovate existing image processing algorithms,reducing the dependence on hardware level and shooting quality.After testing the contact angle measurement platform,the average error of the automatic measurement is 0.95° which is less than the manual measurement error of 1.81°.In order to further improve the accuracy of automatic measurement,this paper proposes an automatic measurement method of contact angle based on feature point detection,the main idea is to use circular template to move and traverse the feature points at the boundary of the droplet,and combine it with existing machine measurement algorithms.The article theoretically illustrates the feasibility of the algorithm,and through experimental comparison and analysis,the average error of the circular fitting automatic measurement is 0.83°,which is smaller than the elliptical fitting automatic measurement and the high-volume automatic measurement.It shows that the automatic measurement method of contact angle based on feature point detection can improve measurement accuracy and efficiency,and it has certain engineering application value.Then,the influence of uneven background illumination on the measurement error of contact angle is analyzed.The experiment is to change the uneven illumination intensity,apply Canny edge detection,cubic spline interpolation to fit the edge,and so on.Regularity,the principle is explained by Mie light scattering theory,and the relationship between illumination intensity and contact angle measurement error is summarized.Based on the original Otsu binarization,the FCM clustering fuzzy algorithm is combined to improve the traditional single threshold global segmentation accuracy.It is proved that the segmentation effect of the droplet boundary is more accurate and it is more able to cope.A case of contact angle measurement in which a droplet boundary exists in a blurred state due to light scattering.This article starts from two aspects: improving the accuracy of contact angle measurement and enhancing practicality,studies the contact angle measurement method based on machine vision,realizes and improves the automatic measurement of high-precision contact angle,improves the problem of droplet boundary caused by light scattering,improves the traditional Otsu binarization algorithm,and reduces the measurement error,improve measurement efficiency.