利用遗传算法检测咖啡叶锈病

A. Marcos, Natan Luis Silva Rodovalho, A. Backes
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引用次数: 10

摘要

在巴西,大多数多产的咖啡树都易患锈病,这是一种由致病真菌引起的严重疾病,它会攻击咖啡树的叶子,从而导致咖啡产量下降高达45%。为了解决这一问题,本文提出了一种基于遗传算法的方法来识别咖啡叶中的锈病,从而有助于更好地对抗其真菌和减少农药的使用。利用遗传算法计算出一个最优卷积核掩码,该掩码强调真菌侵染叶片的颜色和纹理特征。与专家提供的数据对比表明,本文提出的方法是一种可行的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Coffee Leaf Rust Detection Using Genetic Algorithm
In Brazil, most of the productive coffee plants is susceptible to rust, a severe disease caused by a pathogenic fungi which attacks the leaves of coffee plants, thus causing a drop in coffee production of up to 45%. To address this problem this paper proposes a genetic algorithm-based solution to identify rust in coffee leaves, thus contributing to a better combat of its fungus and less use of pesticides. We use the genetic algorithm to compute an optimal convolutional kernel mask that emphasizing color and texture features of the fungus infection in the leaf. Comparison with data provided by experts indicated that our approach represents and feasible solution for the problem of identifying rust.
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