A computer vision method for measuring multiple pointer meters is proposed based on the inverse perspective mapping. First, the measured meter scales are used as the calibration objects to obtain the extrinsic parameters of the meter plane. Second, normal vector of the meter plane can be acquired by the extrinsic parameters, obtaining the rotation transformation matrix of the meter image. Then, the acquired meter image is transformed to a position both parallel to the meter plane and near the main point by the rotation transformation matrix and the extrinsic parameters, eliminating the perspective effect of the acquired image. Finally, the transformed image is tested by the visual detection method to obtain the readings of the pointer meter, improving measurement precision. The results of the measurement verify the effectiveness and accuracy of the method.

Due to the structural constraints of sprockets and the efficiency requirements of on-site measurements, conventional external parameter calibration methods are difficult to apply to the calibration of the sprocket hub end surface. Therefore, this paper proposes a novel external parameter calibration method based on the invariance of quadratic curves. A cylindrical object with concentric circular rings is inserted into the central hole of the sprocket, and the radii of the large and small circles on the rings, along with the radius of the sprocket hub hole, are used to derive the coefficients of the equations corresponding to the three circles. Based on these coefficients, the external parameters of the sprocket hub end surface are determined. According to the contour characteristics of the sprocket teeth, a point selection model is established to identify the highest and lowest points within the tip and root circle regions. The radial runout is then calculated as the difference in radial distances between the highest and lowest points. In the experiments, eleven sprockets of different sizes were selected as test objects, and the results obtained using the proposed method were compared with those measured by a coordinate measuring machine (CMM). The results indicate that the measurement error of the tooth root and tip circles is less than 42 μm.