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基于机器视觉水果分拣系统研究

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为解决市面上水果分拣设备体积庞大、效率低等问题,文中给出的水果分拣系统以苹果为测试样本,将相机拍摄的RGB图像转换为HSV图像,并根据H分量分布情况计算苹果表面的色泽度,同时用Canny边缘检测算法提取苹果边缘的轮廓,用最小外接圆法计算苹果果径的大小,结合苹果色泽度和果径大小对苹果进行等级分级.系统试验表明,样本颜色与大小均与苹果的特征相符,分拣设备和人工分拣果径大小误差在±1.35 mm以内.该系统可实现精确分拣、自动化运行等目标,提高了分拣精度及效率.
Research on fruit sorting system based on machine vision
In view of the huge volume and low efficiency of the fruit sorting equipment in the market,a novel fruit sorting system is designed in this paper.In the designed system,the apples are taken as the testing samples.The RGB(red,green,blue)images taken by camera are converted into HSV(hue,saturation,value)images.The grades of the apple colors are calculated according to the H component distribution.The Canny edge detection algorithm is used to extract the apple contours.The minimum circumferential circle method is used to calculate the apple diameters.The apples are graded by the parameters of their color grades and diameters.The system testing shows that the colors and sizes of the samples are consistent with those of the apples,and the error between the fruit diameter obtained by sorting equipment and that by manual sorting is within±1.35 mm.In conclusion,the system can realize the goals of precise sorting and automatic operation,so it can improve the sorting accuracy and efficiency.

machine visionfruit sortingHSV color modelCanny edge detection algorithmcontour extractionminimum circumferential circle method

许虎、惠宇龙、万宏强

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西安国信物联技术有限公司,陕西 西安 710065

西安工业大学 机电工程学院,陕西 西安 710021

机器视觉 水果分拣 HSV颜色模型 Canny边缘检测算法 轮廓提取 最小外接圆法

西安市科技计划(2022)碑林区科技计划(2022)

22NYYF063GX2218

2024

现代电子技术
陕西电子杂志社

现代电子技术

CSTPCD北大核心
影响因子:0.417
ISSN:1004-373X
年,卷(期):2024.47(17)
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