Pavement Distress Detection Based on Historical Information

Abstract:

In order to solve the problem that the accuracy and speed of the existing methods are not high in recognition of pavement distress image， a recognition method of pavement distress image based on historical information is proposed by using historical detection results. First， an algorithm framework for the application of historical information is built， and the mechanism of using historical information to create initial constraints for distress detection is introduced. Next， the VGG-16 network is trained to extract damage features. Finally， the initial population is established， and the feature parameters are designed by using historical information to improve the genetic algorithm. The experimental results show that this method can significantly improve the recognition speed without reducing the recognition accuracy compared with the recognition method without using historical information， and the fastest speed can be 141.71 times higher than the algorithm without historical information.