| 计算机视觉信息处理技术在苹果自动分级中的应用 |
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| 引用本文： | 阙玲丽.计算机视觉信息处理技术在苹果自动分级中的应用[J].农机化研究,2017(5):246-248. |
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| 作者姓名： | 阙玲丽 |
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| 作者单位： | 广西工商职业技术学院 教务科研处,南宁,530008 |
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| 基金项目： | 广西高校科学技术研究项目(KY2015YB454) |
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| 摘 要： | 苹果在水果消耗中占有较大份额,对其进行分级销售可提高经济效益。在以往的苹果分级中,大都采用人工方法进行,只考虑大小、色泽方面的影响,导致分级精度低和人工消耗大。计算机系统现今已被广泛应用在精细农业中,如水果和蔬菜的自动收获及农产品的分级。为此,利用计算机视觉系统采集提取苹果图像,采用边缘检测、图像改善、图像二值化等图像数据处理方法对采集的图像前处理,设定等级区分参数,再依据特征参数对苹果进行自动分级。采用机器视觉进行苹果等级分离,提高了苹果分级的正确率,节省了劳动力,可以广泛地推广应用。
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| 关 键 词： | 计算机视觉 苹果自动分级 图像信息提取 多特征分级 |
Computer Vision Information Processing Technology in Automatic Apple Grading |
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| Abstract: | The fruit as a daily consumables , the purchase is will pick one or two , selling fruit on the market today is a hierarchical sales approach .Apple accounted for the largest share in the fruit consumption , it is graded sales can fully play its value .Before Apple sales are artificial methods of rough grading , when using this method of classification may only consider the size or color of the impact , efficiency classification mode is very low , it is more important difficult to fully consider the situation of each apple , leading to low precision grading and artificial consumption .The computer sys-tem is now widely used in precision agriculture , such as detecting and removing weeds yield grade , automatic harvesting of fruits and vegetables or agricultural products .The working principle of computer vision grading system aapple: apple computer vision Acquisition extract images using edge detection , image improvement , image binarization image data pro-cessing method for pre-acquisition image processing , parameter setting level distinction , according to features required to set multiple parameters , and then based on the characteristic parameters of the apple automatically grade separation .Ap-ple uses machine vision were grade separation , not only improve the accuracy of the apple grade separation , but also greatly save labor , while apple computer vision grading can also get a wide range of application . |
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| Keywords: | computer vision apple automatic grading image information extraction multi-grade features |
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