Abstract:In order to improve the low recognition rate and long training time of radial basis neural network in laser image identification and classification, a new method based on rough set and neural network is applied, which uses the feature simplified by rough set as pre-input of neural network. Firstly, the laser active imaging three-dimensional simulation images of the different viewpoints are established. And then 17 target features are extracted, and 5 characteristic attributes that affect decisions are selected using rough sets algorithm from 17 features. Finally,the 4 layer RBF neural network is used as the basic network structure and is combined with the rough set method to identify the target on each layer nodes. The simulation results show that correct recognition rate of this method reaches more 80%,which is comparable to neural network without combining rough set, but the training and recognition time is shortened by more than 10 times.