Otsu’s method is an adaptive thresholding way for binarization in image processing. By going through all possible threshold values (from 0 to 255), it can find the optimal threshold value of input image.
In image process and analysis, we sometimes need a method to separate two related data, for example, background and foreground, land and river. Here, I’ll introduce a data-driven way which can adaptively find the optimal threshold to distinguish two-class data — Otsu thresholding. This method can be applied in image segmentation and image binarization, and the latter is the main topic in this article.
This project does not need any advanced python knowledge. You only need to know python base syntax. To understand how the algorithm works you need to know what is Otsu algorithm.