瓦楞纸板数量的机器视觉计数系统

C. Suppitaksakul, Meena Rattakorn
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引用次数: 5

摘要

本文提出了一种利用机器视觉系统和图像处理技术对瓦楞纸板数量进行计数的方法。纸板边缘图像是条状或切边和凹槽状或切断边进行检测和计数。采用阈值法将线扫描相机得到的边缘图像的灰度值转换为二值图像。然后通过一阶导数和形态学提取分切侧的条形线,然后进行MODE处理进行计数。对于截止边,纸板的凹槽区域被识别和测量使用Blob分析。然后定位检测区域的中心,并将其计算为纸板数。实验中使用MATLAB进行仿真,确定算法,并使用HALCON进行实时实验,观察系统的精度和性能。试验使用的纸板类型为BC、C、B。实验结果表明,在纸板离切纸机和切纸机的相机焦点较远的情况下,该系统提供了正确的计数,误差分别为2 cm和3 cm。
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Machine vision system for counting the number of corrugated cardboard
This paper presents a method for counting the number of corrugated cardboard using machine vision system and image processing techniques. The cardboard edge images that are strip or slitter and fluted or cut-off side were used for detection and counting. The gray level of edge images which obtain from the line scan camera are convert to binary images by threshoding. After that the strip lines of the slitter side are extracted by the first-order derivative and morphology then processed with MODE for counting. For the cut-off side, the fluted areas of cardboard are identified and measured using Blob analysis. Then the centers of the detected area are located and counted as the number of cardboards. MATLAB is applied to simulate in the experiments for determine the algorithms and perform the real-time experiments using HALCON to see the accuracy and performance of the system. The cardboard type BC, C and B were used in the tests. As experimental results, it is shown that the system provided the correct counting with tolerance of 2 cm and 3 cm in the case of the cardboard placed away further the camera focus for the slitter and cut-off side respectively.
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