Modern manufacturing industry has a strong measurement demand of specular surfaces. Fringe reflection method has the advantages of simple structure, low cost, high accuracy, and is becoming more and more popular for 3D measurement of these surfaces. Most of previous methods achieve the fringe reflection measurement using a single camera, and suffer the problem of gradient-height ambiguity. Here, a binocular fringe reflectometry method is proposed with the surface normal is obtained through normal vector consistency of the measured surface. To enhance the computation efficiency, a polar constraint and bisection method are also developed to get the matching points on the two camera images. After that the normal vector and the gradient distribution can be calculated. The 3D measurement result can be obtained according to integral reconstruction algorithm subsequently. To verify the effectiveness of the method, measurements were performed on a spherical mirror. Compared with the result from interferometer, the deviation of peak to valley value is 314.3 nm, and the root mean square value is 52.8 nm, which indicates high accuracy of the method.
Achieving high accuracy and fine-grained three-dimensional (3D) results has been an important research direction in visual measurement. Line Structured Light Sensor (LSLS) has the advantage of high accuracy but lacks clarity. Conversely, Photometric Stereo (PS) provides higher clarity but lower measurement accuracy. To address this issue, a novel method is proposed which fuses the point clouds from both LSLS and PS by use of two-dimensional wavelet transformation. The object is firstly measured by use of the LSLS and PS methods separately to obtain point cloud data. The surface points are then matched, and the measurement results are decomposed using wavelet transformation. The corresponding low-frequency and high-frequency information can be obtained. Subsequently, the low-frequency information from LSLS and the high-frequency information from PS, at suitable scales, are selected for reconstruction. Fused result through this process ensures high measurement accuracy and clarity. Experiments also validate the effectiveness of this method.
Line structured light (LSL) measurement systems have gained more and more applications in industry. An interested profile can be easily obtained through the analysis of laser-object intersection stripe. However, all stripe center extraction methods have extraction errors which will lead to profile deviation from the ideal one. In order to reduce this error, the law of uncertainty generation and propagation for the LSL measurement system is analyzed, and a filtering procedure is carried out on this basis. The uncertainty of stripe center extraction is computed in real time by adaptive BP neural network (ABPNN). According to the measurement model and the uncertainty propagation law, the uncertainty value of the each measurement point is obtained. Then, a point cloud filtering method based on uncertainty is proposed. The surface equation is obtained by segmenting and weighting the original point cloud, and the new point cloud data is obtained by interpolation calculation. Finally, the filtered point cloud data is verified by experiments, which proves that the filtering method can improve the measurement accuracy.
Handheld line structured light scanning system (SLSS) is a convenient choice to get the three-dimensional data of the objects. However, its accuracy is dominated by the calibration process and the extrinsic parameters of the handheld device. The extrinsic parameters are computed in real-time manner and connect the sensor coordinate system and the world coordinate system. However, significant noises can be observed due to the ambient light. To improve the accuracy, Kalman filter method is adopted and smoother extrinsic results of the handheld device can be achieved. This would also benefit for the final measurement results. The simulation and the experimental results further validate the effectiveness of the proposed method.
Fringe reflectometry is a favorite method for 3D measurement of specular surfaces with the advantages of simple structure, low cost and high precision. The traditional reflectometry method is based on the telecentric optical path assumption. When the surface has a large diameter or curvature, this assumption is hard to be guaranteed. In addition, the non-sinusoidal distortion of fringes will also introduce significant phase errors and degrade the measurement accuracy. To avoid these problems, a high precision monoscopic fringe reflection measurement model is proposed based on a reference plane. The relative phase change between the measured surface and the reference plane is used to get the accurate corresponding screen points for each point on camera imaging plane. With these correspondence point pairs, the normal vectors and the 3D geometry can be obtained. To validate the effectiveness of the proposed method, a concave spherical mirror was measured. The peak to valley value of the residue error can reach 0.784μm which demonstrates high accuracy of the method.
Line structured light sensors (LSLSs) have gained more and more applications in industry. An interested profile can be easily obtained through the analysis of laser-object intersection stripe. But one sensor is inadequate to get a closed crosssection profile due to the obstacle of the laser light. Thus, multiple LSLSs were integrated as a whole for profile inspection and a numerical calibration method was also proposed. Firstly, the laser planes from all laser projectors were adjusted to coincide with the target plane by adjusting the fixtures of the laser projector. For each sensor, origin of the world coordinate system (WCS) was fixed at the center of a corner calibration dot with its X and Y axis coincide with the row and column direction of target dots. Each sensor camera captured one image of the same target. The relationship between the pixel coordinate system (PCS) and the WCS was established using an interpolation method via the world coordinates of target dot centers and their corresponding pixel coordinates. Then the measurement points from all the sensors were transformed into the global WCS, and a closed cross-section profile can be achieved. This proposed method neither need to establish the intrinsic, the extrinsic and the distortion models of the camera, nor need to solve the complex optimization equations to determine the model coefficients. Finally, a workpeice with stairs and a rectangular block were inspected. The comparison with the measuring results from the coordinate measuring machine further validates the high accuracy of the proposed method.
With the advantages of easy data processing and fast measuring speed, line structured light sensors (LSLSs) have gained more and more applications. CCD camera is a core component of the sensor. The distortion of its lens will severely degrades the measuring accuracy. To enhance the measuring quality, a numerical calibration method is brought out that is based on linear transformation over triangular domain. Based on the pinhole imaging principle, a linear transformation model was established which is easy to compute the profile’s world coordinates according to its pixel coordinates over each triangular domain. The triangle domains are achieved using Delaunary triangulation via the centers of target dots. The triangle number that each center point of the laser stripe locates is determined by T-search method. A linear approximation error model to the lens distortion is also established and the approximation errors are getting larger when the interval spacing of the calibration dots increases. Measuring results show that the relative error of this proposed method in horizontal and vertical direction can reach 0.0630% and 0.0802%, respectively. The calibration error grows with the increasing of the target’s dot interval that corresponds with the trends of the linear approximation error. This further validates the proposed calibration method.
As a non-contact measuring apparatus, line structured light sensor (LSLS) can only get one profile of an object without the combination with other motional axes. To achieve the complete 3D measurement, a rotation-translation platform was integrated with the LSLS, and a cylinder based calibration method was also brought out. Firstly, the calibration model was proposed to determine the transformation matrix between the measuring coordinate frame (MCF) and the sensor coordinate frame (SCF). This model relies on the fact that the projection of an arbitrary intersection profile between the laser plane and the cylinder in its axis direction lies on a circle with a radius equal to the cylinder. Then, for a specified rotated angle and translated position of the object, the measured data from the SCF could all be transformed into the MCF, and the complete surface data could be obtained. Finally, a cylinder and a rectangular block were inspected by the proposed method. The surface data was successfully obtained and their intersection profiles indicate a high measuring accuracy of the proposed method. The method was further verified by the measured results of a screw surface.
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