Research on method of feature extraction and recognition of road condition from nighttime video without vehicle segmentation

Acquirement of night traffic information of road net is very important to network comprehensive utilization improvement. Due to interference of vehicle lights at night, it is very difficult to segment vehicles from nighttime traffic video. This paper suggested the average brightness and traffic speed in observing region to characterize traffic states, and analysis the effectiveness of parameters. Meanwhile, the extraction of these parameters do not need to vehicle segmentation. Based on RBF neural network, we achieve automatic road condition recognition, and obtain a higher coincidence rate with manual classification.