基于俯视图像的玉米株心快速识别方法研究

Fast Recognition Method of Maize Core Based on Top View Image

摘要:

单株玉米的株心识别是完成按株作业的关键，可用于对单株玉米进行变量施肥，提高施肥利用率。本文首先采用超绿因子增强苗期玉米植株，使玉米植株与土壤、阴影分离，将增强后的图像用Ostu法自动确定图像的最佳阈值，以便于在分割苗期玉米图像时不受阴影的影响，并能分割出苗期玉米植株。然后把分割的苗期玉米植株图像的亮度看作是一维坐标，绘制玉米植株的高程图，玉米植株的中心区域在高程图呈现为集水盆形状。采用水平集确定玉米植株的中心区域并对玉米植株中心进行定位，并结合分治法搜索玉米植株的极小值区域，降低了数据结构的规模。数据验证结果表明，算法识别率可达96%，保证了算法的实时性与可行性。另外，采用分治法与水平集法相结合确定玉米植株的中心区域，使该算法不受天气因素的影响，提高了该算法在田间作业时的鲁棒性。算法时间复杂度计算结果为O(lgn)，能够满足田间作业的实时性。

Abstract:

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.