室外多变光照条件下农田绿色作物的图像分割方法

针对室外农田绿色作物图像分割中存在的问题, 提出一种基于绿色作物G\|R颜色特征, 结合最大类间方差Otsu法和面积阈值分割的农田绿色作物图像分割方法, 解决了室外光照不均及复杂土壤背景环境下农田图像中绿色作物与背景不易分割的难题. 实验结果表明, 该方法不仅对作物、 土壤和光照变化不敏感, 且可以消除图像阴影部分的影响, 与颜色索引方法EXG-Otsu和RGB算法（G>R, G>B）相比, 该方法分割效果更理想.

Image Segmentation Method for Farmland Green Crop Plantsunder Outdoor Changeable Illumination Conditions#br#

Aiming at the problem of the image segmentation of farmland green crop plants under outdoor, we proposed an image segmentation method for farmland green crop plants which based on G-R color feature of green cropplants, combined with the Otsu method for the maximum variance between clusters and area threshold segmentation. The algorithm solved the difficult problem of segmentation of farmland green crop plants and background in thefarmland images under the conditions of uneven illumination and complicated soil of outdoor. The experimental results show that the method is not only insensitive to crop, soil and light changes, but also can eliminate the effects of the shadow part of image, compared with the color indexing method EXG Otsu and RGB algorithm (G>R and G>B), the segmentation effect of the method is better.