Thresholding is a simple, yet effective method for image partitioning into a foreground and background. The objective of image segmentation is to modify the representation of an image into another representation that is easier to process. For example, image segmentation is commonly used to extract objects from the background based on some properties of the object (for example, color, edges, or histogram). The simplest thresholding methods replace each pixel in the source image with a black pixel if the pixel intensity is less than some predefined constant (the threshold value), or a white pixel, if the pixel intensity is greater than the threshold value.
OpenCV provides the cv2.threshold() function to threshold images. We will see this function in further detail in the next subsections of this chapter.
In the thresholding_introduction.py script...
