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Veins feature extraction for LED plant growth cabinet

机译:静脉特征提取用于LED植物生长柜

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The state of crop growth can be reflected truly from prominent morphological characteristics of leaf vegetables' veins. Meanwhile, computer image processing technology enables these features to be extracted, which provide a significant method to master the vegetables growing and allows the environment of plant growth cabinet to be controlled in intelligent way. This paper analyzes the histogram distribution of each channel firstly, and then combining the color channel combination operation with threshold segmentation to get the veins and blade profile images. After that, the blade edge is extracted through mathematical morphology. Lastly, this paper compares the absolute value between the profile images and the blade edge images to achieve precise segmentation and extraction of the veins. The results of experiments show that it is a better method to extract veins by means of the difference between mesophyll and the leaf color, allowing the manager to measure the crop growth and making it possible for intelligent monitoring used in plant growth cabinet.
机译:从蔬菜叶脉的突出形态特征可以真实地反映出农作物的生长状态。同时,计算机图像处理技术能够提取这些特征,为掌握蔬菜生长提供了一种重要的方法,并可以智能方式控制植物生长柜的环境。本文首先分析了每个通道的直方图分布,然后将彩色通道组合操作与阈值分割相结合,以获得静脉和叶片轮廓图像。之后,通过数学形态学提取叶片边缘。最后,本文比较了轮廓图像和叶片边缘图像之间的绝对值,以实现静脉的精确分割和提取。实验结果表明,利用叶肉和叶色之间的差异提取叶脉是一种更好的方法,管理者可以测量作物的生长,并有可能对植物生长柜中的植物进行智能监测。

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