Automated system for classifying Hass avocados based on image processing techniques

E. E. Guerrero, G. Benavides
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引用次数: 16

Abstract

Farming of Hass-variety-avocado has become an important economic activity in Colombian agriculture for covering local market requirements but also for exporting high quality fruits to foreign markets. Many processes still need to be improved in different regions of Colombia where Hass variety is cultivated in order to increase the efficiency during harvesting, transportation and storage. Human-performed classification of avocados takes time that could be used by farm's personnel to perform other activities aimed to achieve higher quality standards and production efficiency. Product price and target market depends to a large extent on classification stage. We propose a system based on image processing of avocados' pictures for their classification after they have been picked off the tree. The classifying algorithm runs on a computer which receives fruit's images wirelessly from a camera, the result is transmitted using IEEE 802.15.4 packets and avocados are placed in conveyor belt rails according to their categories. Matching percentage of the image processing algorithm for selecting avocados was of 88% compared to the test set classified by expert farmers. Confusion matrix showed 82.22% accuracy when classifying avocados.
基于图像处理技术的哈斯鳄梨自动分类系统
种植哈斯品种鳄梨已成为哥伦比亚农业的一项重要经济活动,不仅满足了当地市场的需求,而且还向国外市场出口高质量的水果。在种植哈斯品种的哥伦比亚不同地区,许多工艺仍需改进,以提高收获、运输和储存期间的效率。人工对牛油果进行分类需要时间,农场人员可以利用这些时间进行其他活动,以达到更高的质量标准和生产效率。产品价格和目标市场在很大程度上取决于分类阶段。我们提出了一个基于图像处理的系统,用于牛油果摘下来后的分类。分类算法在一台计算机上运行,该计算机通过摄像头无线接收水果图像,结果通过IEEE 802.15.4数据包传输,鳄梨根据其类别被放置在传送带轨道上。与专家农民分类的测试集相比,图像处理算法选择鳄梨的匹配率为88%。混淆矩阵对牛油果的分类准确率为82.22%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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