作物叶面图像自动分割方法

Automtic leaf surface region segmentation from crop image

为了能够从作物图像中快速地获得作物长势与病虫害等信息,叶面图像分割是重要基础.提出了大田环境下作物叶面图像的自动分割方法,首先通过颜色分割获得作物图像绿色区域部分,然后采用光滑度分割删除枝、茎和杂草等绿色干扰;在此基础上以腐蚀与区域面积方法去除叶面干扰区域;最后将叶面区域以适度膨胀操作获得完整的作物叶面图像.为了验证方法的有效性进行了一系列田间试验,结果表明:与已有的方法相比,该方法具有从复杂的作物图像中自动获得叶面区域的优点,为作物状态与病虫害的进一步分析提供参考.

Leaf surface region segmentation from crop images is a crucial step for obtaining crop information. The leaf surface region segmentation( LSRS) from crop images was proposed. The color segmentation was used to obtain green region in crop images,and the smoothness segmentation was applied to identify smooth parts in green regions. Using the erosion method and the pixel number of each region,the noises were eliminated by LSRS to separate big noise and leaf regions into different parts by connectivity scheme. The dilation method was finally used to obtain whole leaf surface region. The experiments were conducted with several crop leaf images to verify the proposed method. The results show that compared to existing methods,the proposed system can automatically segment leaf surface region from complicated crop images.