Thresholding and Otsu's segmentation

Thresholding refers to a family of algorithms that use a pixel value as a threshold to create a binary image (an image with only black-and-white pixels) from a grayscale image. It provides the simplest way to segment objects from a background in an image. The threshold can be chosen manually (by looking at the histogram of pixel values) or automatically using algorithm. In scikit-image, there are two categories of thresholding algorithm implementations, namely histogram-based (a pixel intensity histogram is used with some assumptions of the properties of this histogram, for example bimodal) and local (only the neighboring pixels are used to process a pixel; it makes these algorithms more computationally expensive).

In this section, we shall only discuss a popular histogram-based thresholding method known as Otsu's method (with the assumption of a bimodal histogram). It computes an optimal threshold value by simultaneously maximizing the inter-class variance...