Cell Segmentation for Quantitative Analysis of Anodized TiO$_2$ Foil

Abstract

We propose a quantitative analysis method using cell segmentation to evaluate the coating quality of anodic oxide. In order to identify each cell in a titania surface, a boundary region is adaptively detected according to the regional intensity distribution, and a boundary distance map is projected onto the scanning electron microscope (SEM) image of the titania surface. Each cell in the projected image is divided via clustering centered on the local maximum point. The uniformities of the cell distribution, size, and thickness are measured using the angle difference, size difference, and brightness difference between adjacent cells to comprehensively evaluate the quantitative alignment of the titania surface. The proposed method demonstrates the best performance in both cell detection and cell segmentation for SEM images of the titania surface compared with the state-of-the-art methods. The quantitative analysis of the anodic oxide film alignment was verified using color coding, histogram, and quantification of uniformity.