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一种基于机器视觉的滴灌带孔位在线检测方法
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An Online Detection Method of Drip Irrigation Tape Drilling Position Based on Machine Vision
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    摘要:

    在内镶迷宫滴头滴灌带生产过程中,为了实现滴孔加工位置的检测和反馈控制,将机器视觉用于滴孔位置检测,提出了一种从图像泛白区域ROI多次深度提取ROI的优化识别算法。首先,通过去背景初步提取ROI,进而通过全局固定阈值分割、膨胀、闭运算和区域生长算法的合理运用,对处于光照泛白区域的滴灌带图片进行ROI提取,然后采用基于直方图的全局阈值分割算法进行边缘强化,通过Hough圆变换进一步提取滴孔位置,并通过Hough线变换以及附加约束条件提取迷宫滴头前沿位置,最后计算得到滴孔到迷宫滴头前沿的相对距离。实验结果表明,使用优化后的算法,滴孔的识别准确率达到了98%以上,滴孔到迷宫滴头前沿的距离测量误差由优化前的10%以上减小到了5%左右。

    Abstract:

    In order to realize the detection and feedback control of the processing position of drip holes in drip irrigation tape with labyrinth emitters inlaid, the machine vision was used to detect the position of drip holes, and a optimized recognition algorithm based on multiple depth extraction of ROI from ROI in the image whitening area was proposed. Firstly, ROI was extracted preliminarily by removing the background. Secondly, ROI of drip irrigation tape image in whitening region was extracted by applying algorithms of global fixed threshold segmentation, dilation, closed operation and region growing. Thirdly, the global threshold segmentation algorithm based on histogram was used to improve the image edges, and the Hough circle transform was used to extract the position of drip hole, and the Hough line transformation and additional constraint conditions were used to detect the position of labyrinth emitter front edge.Finally, the relative distance from the drip hole to the front edge of labyrinth emitter could be calculated. The experiment results show that with the optimized algorithms, the accuracy of drip holes identification is over 98%, and the distance measurement error is reduced from more than 10% before optimization to about 5%.

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潘俊朋,董洁.一种基于机器视觉的滴灌带孔位在线检测方法[J].机床与液压,2019,47(7):67-71.
. An Online Detection Method of Drip Irrigation Tape Drilling Position Based on Machine Vision[J]. Machine Tool & Hydraulics,2019,47(7):67-71

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  • 在线发布日期: 2019-12-04
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