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An Agave Counting Methodology Based on Mathematical Morphology and Images Acquired through Unmanned Aerial Vehicles

机译:基于无人航空车辆获得数学形态学和图像的龙舌兰计数方法

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摘要

Blue agave is an important commercial crop in Mexico, and it is the main source of the traditional mexican beverage known as tequila. The variety of blue agave crop known as Tequilana Weber is a crucial element for tequila agribusiness and the agricultural economy in Mexico. The number of agave plants in the field is one of the main parameters for estimating production of tequila. In this manuscript, we describe a mathematical morphology-based algorithm that addresses the agave automatic counting task. The proposed methodology was applied to a set of real images collected using an Unmanned Aerial Vehicle equipped with a digital Red-Green-Blue (RGB) camera. The number of plants automatically identified in the collected images was compared to the number of plants counted by hand. Accuracy of the proposed algorithm depended on the size heterogeneity of plants in the field and illumination. Accuracy ranged from 0.8309 to 0.9806, and performance of the proposed algorithm was satisfactory.
机译:蓝龙舌兰是墨西哥的重要商业作物,是传统墨西哥饮料的主要来源,称为龙舌兰酒。称为Tequilana Weber的各种蓝色龙舌兰作物是龙舌兰酒综合企业和墨西哥农业经济的关键因素。该领域的龙舌兰植物的数量是用于估算龙舌兰酒的产生的主要参数之一。在此稿件中,我们描述了一种基于数学形态的算法,用于解决龙舌兰自动计数任务。所提出的方法应用于使用配备有数字红绿蓝(RGB)相机的无人空中车辆收集的一组真实图像。将收集图像中自动识别的植物数量与手工计算的植物数进行比较。所提出的算法的准确性依赖于场和照明植物的尺寸异质性。精度从0.8309到0.9806,并且所提出的算法的性能令人满意。

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