最大类间方差法是由日本学者大津(Nobuyuki Otsu)于1979年提出的,是一种自适应的阈值确定的方法,又叫大津法,简称OTSU。它是按图像的灰度特性,将图像分成背景和目标2部分。背景和目标之间的类间方差越大,说明构成图像的2部分的差别越大,当部分目标错分为背景或部分背景错分为目标都会导致2部分差别变小。因此,使类间方差最大的分割意味着错分概率最小。(The largest between-class variance method was proposed by the Japanese scholar Nobuyuki Otsu in 1979. It is an adaptive threshold determination method, also known as the Otsu method, or OTSU for short. It is based on the grayscale characteristics of the image and divides the image into two parts: the background and the target. The larger the variance between the background and the target, the greater the difference between the two parts that make up the image. When the part of the target is wrongly divided into backgrounds or part of the background is mis-divided into goals, the difference between the two parts will be smaller. Therefore, the segmentation that maximizes the variance between classes means that the probability of wrong division is the smallest.)