Research Of Contact Angle Measurement Method Based On Image Analysis

The contact angle is one of the important parameters of surface wettability. The surface energy of the solid material can be acquired by measuring the contact angle. Measurement of contact angle is a technical involving a very wide range. There are important applications in many areas like scientific research, defense, industry, agriculture.Currently, a common contact angle measuring method is collecting images of droplets forming process through the camera, and obtaining information of contact angle using image analysis techniques. As the droplet formation is a dynamic process, and there may be solid surface horizontal deviation and material rough, poor droplets images often be collected in the process of image acquisition. This brought problems to automatic measurement of the contact angle. Many contact angle meter only take handmade way to measure inferior droplet images, and the detection efficiency is low.This article researches the contact angle measuring method based on image analysis, and achieves automatic detection of contact angle of the droplet images. In order to distinguish between qualified and unqualified droplets, and to improve the overall detection efficiency of system, the article proposed a kind of droplet classification and recognition algorithm based on the slope and curvature feature of rough boundary of droplet image. For the phenomenon that there is noise in the droplet image, the article proposed a droplet image filtering algorithm based on FCM clustering analysis. The algorithm can effectively filter massive particles noise and false horizontal noise in the droplet image. In order to properly calculate the contact angle information, a clear and accurate droplet boundary must be obtained. This paper presents a droplet boundary extraction algorithm based on sub-image neighborhood gradient information metrics. Experiments show that, the algorithm can effectively extract droplet boundary. It can get a clear and accurate droplet boundary information even for low-quality droplet images. In addition, this paper studies the calculation of the contact angle, and achieves the automatic measurement ofθ/2method and tangent method. Experiments show that the automatic measurement results obtained by this algorithm consistent with the manual measurements.