为消除轮胎表面气泡造成的行驶危险，研究了基于线激光和机器视觉的轮胎表面气泡缺陷检测方法。由于很难通过图像直接识别轮胎表面，因此采用线激光扫描获得轮胎图像。结合滤波方法和形态学方法对这些图像进行预处理。采用灰度质心法提取激光条纹中心，提出了轮胎表面气泡缺陷位置的确定算法。根据轮胎气泡的几何特征，确定起点、终点的坐标和顶点的粗略位置。然后，对气泡顶点附近具有亚像素精度的激光中心坐标进行离散放大。用高斯函数制成的掩模与放大区域进行卷积，得到最大值。此外，可以准确提取气泡顶点的位置。通过实验比较了不同方法对图像的去噪效果，并对气泡的不同位置进行了检测。实验结果表明，该方法的检测准确率高达93%，远高于其他方法。实验验证了所提出的方法对于检测轮胎表面气泡是有效的。实验结果表明，该方法的检测准确率高达93%，远高于其他方法。实验验证了所提出的方法对于检测轮胎表面气泡是有效的。实验结果表明，该方法的检测准确率高达93%，远高于其他方法。实验验证了所提出的方法对于检测轮胎表面气泡是有效的。
In order to eliminate driving dangers caused by tire surface bubbles, the detection method of bubble defects on tire surfaces based on line lasers and machine vision is studied. Since it is difficult to recognize tire surfaces directly through images, line laser scanning is used to obtain tire images. The filtering method and morphology method are combined to preprocess these images. The gray centroid method is adopted to extract the center of the laser stripe, and then the algorithm to determine the positions of bubble defects on tire surfaces is proposed. According to the geometric characteristics of tire bubbles, the coordinates of starting points, ending points, and rough positions of vertices are determined. Then, the ordinates of the laser center with sub-pixel accuracy near bubble vertices are discretely magnified. The mask made of Gaussian function is convoluted with the magnified region, and the maximum value is obtained. Furthermore, the position of bubble vertices can be accurately extracted. The denoising effects of different methods for images are compared through experiments, and different positions of bubbles are detected. Experimental results show that the detection accuracy of this method is up to 93%, which is much higher than other methods. Experiments verify that the proposed method is effective for detecting tire surface bubbles.
