Measuring objects with high dynamic range (HDR) reflectivity by coded structured-light, captured stripes are usually seriously distorted by reflectivity, causing inaccurate measurement results. A stripe enhancement method is proposed to deal with the problem. The method is based on the correspondence between phase and intensity of the stripe. First, the phase map of the captured stripe pattern is retrieved by phase-shift algorithm and multiexposure method, where saturation and low contrast of the stripe are eliminated; then, the modulation of stripes is normalized to eliminate the influence of reflectivity; finally, the enhanced stripe is obtained by assembling the modulation and the phase map. Experimental results demonstrate that the method is efficient for objects with HDR reflectivity and achieves high accuracy.
A method for improving the measuring accuracy of structured light measurement system, which adopts projecting stripe pattern to measure the three-dimensional profile, is presented. Based on the evaluation of the reliability of center extraction results, the improvement of accuracy is achieved by identifying and rejecting the stripe center extraction results with large error. Two parameters are used to evaluate the reliability of center extraction results. The first parameter is the average energy of the stripe, which is used to analyze and establish the relationship between the extraction accuracy and the signal-to-noise ratio through a statistical method. The second parameter is the asymmetric degree of the stripe gray distribution which introduces error into the center extraction, and a new method is proposed for measuring the asymmetric degree. Then, the criteria of the data rejection defined by the thresholds are presented, and large error data with low reliability are identified according to the thresholds. Higher measuring accuracy is achieved by rejecting the identified data. The validity of the method has been proved by experiments.
In the structured light three-dimensional measurement system, calibration is the key to the measurement accuracy; however, conventional calibration methods for the projector are either too complex or inaccurate. Therefore, we propose a simple and accurate method to calibrate the projector. In this method, the calibration points in the camera image plane can be mapped to the projector according the homography of the planar projection. In addition, an error surface compensation method is developed to minimize mapping errors caused by lens distortion of the camera and projector. As a result, the projector can be calibrated with the same method as the camera. Experiments are conducted to verify the effectiveness of the proposed method.
In the calibration process of structured light three-dimensional (3D) measurement system, the accuracy of the calibration
points' image coordinates directly influences the system's measurement accuracy. Based on the analysis of errors in
calibration points' image coordinates, mathematical models are built. A solution to eliminate errors in those image
coordinates is proposed according to the further analysis of the models, and calibration points are designed to be circle
for high-precision and steady extraction. The solution contains procedures as following: 1) A novel and real-time
algorithm is proposed, which is used for the correction of the non-uniform intensity in image caused by non-uniform
illumination and the camera's parameters. Taking preliminary extracted elliptical center coordinates and average gray
value of the ellipses as known information, the intensity distribution of calibration images can be obtained by
interpolation. Then the non-uniform intensity of calibration images is corrected in accordance with the interpolation
results. 2) High frequency noise in the images is filtered. 3) At last, error of asymmetric perspective projection is also
compensated based on its model. Simulation and experiment results indicate that this solution can efficiently reduce the