首页|基于机器视觉的小工件尺寸测量技术的研究

基于机器视觉的小工件尺寸测量技术的研究

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针对小工件尺寸测量的两个难点:测量效率低和测量精度差的问题,提出了一种基于机器视觉的小工件尺寸快速测量方法.首先采用双边滤波、灰度处理等对原始图像进行预处理,提高了被测工件的边缘定位精度;其次,对获取到边缘信息的图像提取所有轮廓信息,并通过计算图像轮廓的长度、面积等信息剔除因噪声及背景等引入的无效轮廓;最后,计算有效轮廓的质心坐标和最小外接矩形,根据质心坐标获得校准工件位置并对比校准工件与被测工件轮廓的最小外接矩形尺寸求得被测工件尺寸.试验结果表明:被测工件尺寸的绝对误差和相对误差小,能够较为准确、高效地测量出工件的尺寸.
Research on Small Workpiece Size Measurement Technology Based on Machine Vision
Two difficulties in measuring the size of small workpieces:the problems of low measurement efficiency and poor measurement accuracy,a fast measurement method for small workpiece size based on machine vision has been proposed.Firstly,bilateral filtering and grayscale processing were used to preprocess the original image,which improved the edge localization accuracy of the measured workpiece;Secondly,extract all contour information from the image that has obtained edge information,and eliminate invalid contours introduced by noise and background by calculating the length,area,and other information of the image contour;Finally,calculate the centroid coordinates and minimum bounding rectangle of the effective contour,obtain the position of the calibration workpiece based on the centroid coordinates,and compare the minimum bounding rectangle size of the calibration workpiece with the measured workpiece contour to obtain the measured workpiece size.The experimental results show that the absolute and relative errors of the measured workpiece size are small,and the size of the workpiece can be measured accurately and efficiently.

Machine visionSmall workpiecesMeasurementContour extraction

陈向梅

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福州职业技术学院,福建福州 350108

机器视觉 小工件 测量 轮廓提取

福州职业技术学院校级科研项目(2022)

FZYKJJJYB202203

2024

福建农机
福建省机械科学研究院  福建省农机管理局  福建省农业机械学会

福建农机

影响因子:0.229
ISSN:1004-3969
年,卷(期):2024.(1)
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