Asphalt Roadside Flatness Detection Based on Laser Sensing Image Processing

Smoothness assessment plays a key role in evaluating the quality of asphalt concrete pavements, which has a direct impact on vehicle comfort, safety, and pavement longevity. This study presents a novel approach to asphalt pavement smoothness detection based on laser-sensing image processing. The proposed method uses advanced image processing algorithms to extract relevant features indicative of flatness from high-resolution images acquired using laser sensing technology. Key steps include image pre-processing, laser sensing image processing model construction, and performance evaluation. Experimental results demonstrate the effectiveness of the proposed method, which consistently outperforms existing techniques in detecting flatness with an average accuracy of the 98.89%. Statistical analysis confirms the superiority and consistency of the proposed method, highlighting its potential for real-time road surface monitoring and maintenance.