Measurement of three-dimensional pavement morphology using binocular reconstruction improved by second-order fusion algorithm

Complex illumination interference poses a practical challenge in achieving robust and accurate measurement of three-dimensional (3D) pavement morphology using traditional binocular reconstruction technology. To enhance the measurement effect, the dual constraints of bi-spectral and structured light are introduced. The theoretical model of improved binocular vision algorithm based on second-order fusion is established. A test system with accuracy self-evaluation is also manufactured. The measurement accuracy, anti-light interference ability and measurement effect in real scenarios are further evaluated. The results show that the improved algorithm can achieve the dual functions: 3D morphology measurement and accuracy self-evaluation. By incorporating dual constraints, the improved algorithm enhances both overall and single point measurement accuracy. Meanwhile, the proposed algorithm can maintain measurement stability in the illumination range of 100-1250 Lux and obtain satisfactory test results in real scenarios. This method exhibits potential for effectively detecting 3D morphology in complex scenarios.