Segmentation of scanning electron microscopy images from natural rubber samples with gold nanoparticles using starlet wavelets.
Electronic microscopy has been used for morphology evaluation of different materials structures. However, microscopy results may be affected by several factors. Image processing methods can be used to correct and improve the quality of these results. In this article, we propose an algorithm based on starlets to perform the segmentation of scanning electron microscopy images. An application is presented in order to locate gold nanoparticles in natural rubber membranes. In this application, our method showed accuracy greater than 85% for all test images. Results given by this method will be used in future studies, to computationally estimate the density distribution of gold nanoparticles in natural rubber samples and to predict reduction kinetics of gold nanoparticles at different time periods.
DFQB-Departamento de Física, Química e Biologia, FCT-Faculdade de Ciências e Tecnologia, Univ Estadual Paulista, Rua Roberto Simonsen, 305, 19060-900 Presidente Prudente, São Paulo, Brazil.
Alexandre Fioravante
AF
de Siqueira
Flávio Camargo
FC
Cabrera
Aylton
A
Pagamisse
Aldo Eloizo
AE
Job
D000465:Algorithms; D006046:Gold / Q000737:chemistry*; D007091:Image Processing, Computer-Assisted; D053768:Metal Nanoparticles / Q000648:ultrastructure*; D008855:Microscopy, Electron, Scanning; D012408:Rubber / Q000737:chemistry*
D006046:Gold; D012408:Rubber
gold nanoparticles; image processing; natural rubber; scanning electron microscopy; wavelets