Thresholding is the binarization of an image. We convert a grayscale image to a binary image, where the pixels are either 0 or 255.
A simple thresholding is selecting a pixel value x, and then selecting all pixel intensities less than x to zero, and all pixel values greater than x to 255. In this way, we are able to create a binary representation of the image. We use thresholding to focus on objects or areas in an image.
AS in simple thresholding we have to manually supply our threshold value T, which require a lot of manual experiments and parameter tunings. Just one value of T might not be enough. Adaptive threshold considers a small neighbors of pixels and then finds an optimal threshold value T for each neighbor. This can help in cases where there may be ranges of pixel intensities and the optimal value T may change for different parts of the image.
