Improvement of Binocular Reconstruction Algorithm for Measuring 3D Pavement Texture Using a Single Laser Line Scanning Constraint

Abstract

The dense and accurate measurement of 3D texture is helpful in evaluating the pavement function. To form dense mandatory constraints and improve matching accuracy, the traditional binocular reconstruction technology was improved threefold. First, a single moving laser line was introduced to carry out global scanning constraints on the target, which would well overcome the difficulty of installing and recognizing excessive laser lines. Second, four kinds of improved algorithms, namely, disparity replacement, superposition synthesis, subregion segmentation, and subregion segmentation centroid enhancement, were established based on different constraint mechanism. Last, the improved binocular reconstruction test device was developed to realize the dual functions of 3D texture measurement and precision self-evaluation. Results show that compared with traditional algorithms, the introduction of a single laser line scanning constraint is helpful in improving the measurement's accuracy. Among various improved algorithms, the improvement effect of the subregion segmentation centroid enhancement method is the best. It has a good effect on both overall measurement and single point measurement, which can be considered to be used in pavement function evaluation.