title: Automatic morphological characterization of nanobubbles with a novel image segmentation method and its application in the study of nanobubble coalescence.
abstract: Nanobubbles (NBs) on hydrophobic surfaces in aqueous solvents have shown great potential in numerous applications. In this study, the morphological characterization of NBs in AFM images was carried out with the assistance of a novel image segmentation method. The method combines the classical threshold method and a modified, active contour method to achieve optimized image segmentation. The image segmentation results obtained with the classical threshold method and the proposed, modified method were compared. With the modified method, the diameter, contact angle, and radius of curvature were automatically measured for all NBs in AFM images. The influence of the selection of the threshold value on the segmentation result was discussed. Moreover, the morphological change in the NBs was studied in terms of density, covered area, and volume occurring during coalescence under external disturbance.
authors.affiliation: School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, P.R. China.
authors.forename: Yuliang
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Materials Science and Engineering, The Ohio State University, 2041 College Rd., Columbus, OH 43210, USA.
authors.forename: Huimin
authors.initials: H
authors.lastname: Wang
authors.affiliation: School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, P.R. China.
authors.forename: Shusheng
authors.initials: S
authors.lastname: Bi
authors.affiliation: School of Material Science and Engineering, Harbin Institute of Technology, Harbin, 150001, P.R. China.
authors.forename: Bin
authors.initials: B
authors.lastname: Guo
keywords: atomic force microscopy; characterization; coalescence; nanobubbles; segmentation