Having learnt about binary images, let's now focus our attention on one of the processes that generate binary images: image thresholding. In the generic sense of the term, a threshold is some sort of a benchmark against which values are compared. Extending the same definition into our realm of computer vision, we use a threshold to compare pixel values. Let's try to understand how this happens.
The input to the thresholding functions are grayscale images, which means that every pixel has an intensity value in the range of 0 to 255 (inclusive). First, we predefine a threshold value for the operation. As expected, the threshold that we select is passed on to the function that implements the thresholding operation as a parameter. Now, what a thresholding operation essentially does is that it traverses the image pixel by pixel. At every pixel, it compares the intensity value with the threshold and decides on the corresponding output intensity value based on the result...