The identification of individual plant maize core at seedling stage is the key to complete the operation according to the plant. It can improve the accuracy of variable fertilization for individual corn, and can further improve the utilization rate of fertilizer. A fast recognition method of maize core based on top view image was purposed. Firstly, by using the super green factor to enhance maize plant of seedling stage, the maize plants were separated from soil and shadow. And based on the enhanced images, Otsu method was used to automatically determine the optimal threshold for image segmentation, in effect of avoiding shadow influence and separating the maize plants correctly. Then by using the image brightness of the plants at seedling stage as one-dimensional coordinate, the elevation map of maize was drawn, the central region of each maize plant showed as a shape of water basin. The level set was used to determine and locate the central area of each maize plant. And a method of dividing and conquering was used to reduce the level set scale and search the minimum value area of each maize plant. Through data validation, the results showed that the recognition rate reached 96%. It indicated that the algorithm was feasible in real-time. In addition, since the method and level set method were combined to determine the center area of each maize plant, the algorithm was adaptive and not affected by weather factors, which improved the robustness of the algorithm in the field operation. The time complexity of the algorithm was O(lgn), which could meet the real-time field operation.