Grayscale Image Segmentation based on Topological Data Analysis
Yugo Ogio, Yuki Minami, Masato Ishikawa · Transactions of the Institute of Systems Control and Information Engineers · 2021
In this paper, we applied topological data analysis (TDA) to the segmentation of grayscale images. TDA is a method to extract topological features such as hollows from data. It is expected that we can segment images because we can regard objects in images as hollows. In this paper, we first confirmed that the TDA based method was effective in the segmentation of halftone images by random dithering. Then, we compared the proposed method and the combination of Otsu’s method and TDA. Finally, we evaluated the performance of our method using standard images and CT-images.