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Classification of Rice Leaf using Fuzzy Logic and Hue Saturation Value (HSV) to Determine Fertilizer Dosage

机译:使用模糊逻辑和色调饱和值(HSV)进行稻叶的分类来测定肥料剂量

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Rice is one of the food commodities that is most needed by the Indonesian people. Its condition requires farmers to maximize rice harvest as a rice-producing plant which one of them by providing fertilizer with the right dose. One of the methods used by rice farmers is to use a Leaf Color Chart to compare the color of rice leaves manually which might cause an error. Several research topics of classification based on plant image processing have been done to help the agriculture sector including rice. In this paper, the classification of rice leaves to determine the fertilizer dose by processing the rice leaf image using the HSV method is proposed. Results of rice leaf image processing are classified using fuzzy logic to calculate the right dose of fertilizer and developed as a mobile-based application. The proposed method achieved an accuracy value of 90% for the color of rice leaf and an accuracy value of 82.5% for the determination of fertilizer dose.
机译:米饭是印度尼西亚人民最需要的食品商品之一。其状况要求农民将大米收获最大化为水稻生产植物,通过提供肥料的肥料。米农使用的方法之一是使用叶子颜色图表手动比较稻壳的颜色可能导致错误。已经完成了基于植物图像处理的分类的几个研究主题,以帮助在包括米饭的农业部门。本文提出了利用HSV方法加工稻壳测量稻叶的分类,以确定稻壳剂量。使用模糊逻辑分类稻叶片图像处理的结果,以计算肥料的右剂量,作为基于移动的应用。所提出的方法达到米叶颜色的精度为90%,测定肥料剂量的精度值为82.5%。

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