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Multicamera systems are commonly applied in the large field-of-view (FOV) measurements. However, two cameras may have a non-overlapping FOV in some scenes, and traditional binocular camera calibration methods cannot be used to directly calibrate non-overlapping cameras. To solve this problem, our study proposes a calibration method for binocular cameras with non-overlapping FOVs on the basis of planar mirrors. According to the reflection characteristics of an optical planar mirror, the proposed method can use the same target to calibrate non-overlapping cameras. Hence, the method overcomes the limitation of non-overlapping cameras being unable to observe common targets. Experiments results show that the maximum RMS error does not exceed 0.53 mm. Hence, the proposed method is effective, and its measurement technique is simpler and more universal than those of other methods. In addition, it is applicable to a wide range of measurements.

Fringe projection technology is often used for three-dimensional (3D) measurement, but it is difficult to measure highlight surfaces. Polarization systems are usually used to remove highlight surfaces. Polarizing filters can be used to eliminate the highlights of the image, but they may also cause the image to be too dark and affect the measurement accuracy. Otherwise, to ensure measurement accuracy, the complexity of the operation of the polarization system will be increased. A method of polarization-based camera intensity response function for 3D measurement is proposed. The intensity response function of the camera under the polarization system is established. It can avoid the complicated polarized bidirectional reflectance distribution function model and directly and quantitatively calculate the required angle between the transmission axes of the two polarizing filters. Then it is combined with the image fusion algorithm to generate the optimal fringe pattern. Experimental results demonstrate that this method significantly eliminates the effects of highlights in the image. The fuzzy transition area between the black and white fringes is effectively reduced, and the edge information of the fringes is correctly restored. Moreover, the high signal-to-noise ratio and contrast of the image are retained when the polarization filters are added.

In the structured light three-dimensional measurement system, calibration is crucial for measurement accuracy. However, conventional projector calibration methods involve complicated procedures. Therefore, a novel method is developed for projector calibration. The key concept is to establish the relationship between projector coordinates and the world coordinates using the projection checkerboard, which enables the calibration of the projector to be the same as that of a camera. In addition, the edges of the checkerboard form different degrees of high-light regions when the projection checkerboard is collected. These high-light regions affect the extraction of corner points and cause low accuracy of the projector calibration. Therefore, the projection checkerboard is collected by a CCD camera equipped with a polarizer at the optimal polarization angle. Then the subpixel corner extraction algorithm based on the homography matrix mapping is used to extract the subpixel coordinates of the corners. Finally, the projector can be calibrated with the same method as the camera. In the experimental part, the validity of the method is verified by the reprojection system.