In many grayscale images, there is usually a significant difference between the gray levels of the focus of the image and the image’s background, this could be caused by the photo taken at a different time or day, or other reasons for different lighting conditions. By using a statistical thresholding method, it is capable to construct a new, binary image, which can enhance the viewing of two distinct classes. By computing an image histogram, it is possible to segment the image into dark and light pixels, to compute an interclass difference. This report examines the difference between two different image thresholding techniques: Otsu’s adaptive thresholding technique, and adaptive progressive thresholding (APT).