基于双目立体视觉的连铸坯缺陷定位研究
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武汉科技大学信息科学与工程学院 武汉 430081

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TN29;TP391

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国家自然科学基金(62173261)项目资助


Research on defect localization of continuous casting billet based on binocular stereo vision
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School of Information Science and Engineering, Wuhan University of Science and Technology,Wuhan 430081, China

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    摘要:

    为获取因去毛刺机故障产生的连铸坯缺陷位置,提出一种基于双目视觉的缺陷定位方法。首先针对AD-Census算法在铸坯图像匹配效果不佳问题,提出一种窗口中心像素噪声检测方法,将邻域像素信息替代噪声像素点,并在代价函数计算中融入多方向梯度代价,提高初始代价的可靠性;其次设计一种基于梯度阈值的自适应窗口代价聚合,提高算法在弱纹理区和边缘区域的匹配效果;最后将铸坯视差图进行三维坐标转换,完成对连铸坯缺陷定位。实验表明,本文提出的双目视觉缺陷定位方法,视差图匹配精度高,且铸坯缺陷深度的平均定位误差在1 mm以内,可为后续缺陷处理装置提供可靠的位置信息。

    Abstract:

    In order to obtain the defect location of the continuous casting billet caused by the failure of the deburring machine, a defect location method based on binocular vision was proposed. Firstly, aiming at the poor matching effect of AD-Census algorithm in casting blank images, a noise detection method of window center pixels is proposed, which replaces noise pixels with neighborhood pixel information, and integrates multi-directional gradient cost into the calculation of cost function to improve the reliability of initial cost; Secondly, an adaptive window cost aggregation based on gradient threshold is designed to improve the matching effect of the algorithm in weak texture region and edge region; Finally, the parallax map of casting billet is converted by three-dimensional coordinate to complete the defect location of continuous casting billet. Experiments show that the binocular vision defect location method proposed in this paper has high parallax map matching accuracy, and the average location error of the casting blank defect depth is less than 1 mm, which can provide reliable location information for the subsequent defect processing device.

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刘光举,刘琼,杜荣谦.基于双目立体视觉的连铸坯缺陷定位研究[J].电子测量技术,2024,47(20):24-31

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  • 在线发布日期: 2025-01-06
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