Abstract: Cotton topping is the key link in cotton field management. The quality of the topping operation will affect the subsequent growth of cotton. Accurately identifying and locating cotton plants has positive significance for mechanized cotton topping. This article briefly summarizes the application research of machine vision technology in the foreign agricultural field and summarizes ＆ compares the positioning technology in the domestic cotton topping field by introducing the research of binocular stereo vision technology, BP（Back Propagation） neural network, and convolutional neural network in cotton plant identification and positioning. It also discussed and analyzed machine vision problems in the cotton topping, such as slow recognition speed, algorithm redundancy, and operating environment constraints. The classification and recognition of cotton top leaves, the improvement and optimization of cotton topping machines, the precise spraying of cotton topping agents, and the realization of multi-functional operations are expected to reference subsequent research on intelligent cotton topping.