Abstract: According to the structure of 220 kV single split transmission line,an intelligent visual method of obstacle recognition based on wavelet moments is put forward.It binarizes obstacle images by Ostu algorithm and detects the edges of the images by wavelet modulus maximum algorithm.Then,a set of locally optimum wavelet moment features are selected by calculating the wavelet moments of the edge images.Based on these features,a wavelet network is presented for obstacle image recognition and classification.The experiment results show that the obstacles such as counterweight,strain clamp and suspension on high voltage transmission line can be effectively recognized by the proposed method,and the proposed wavelet network method has higher precision and quicker convergence rate than the common three-layer BP(backpropagation) neural networks.