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In order to solve the problem of resolution overrun and realize accurate recognition of remote sensing image frame feature objects, a dynamic recognition technology of remote sensing image frame feature based on edge detection and RBF neural network is proposed. Solve the differential operator and OTSU threshold, and determine the value range of the tracking parameters of the edge node based on this, so as to realize the edge detection of the remote sensing image. According to the construction standard of RBF neural network mechanism, the neural activation function is deduced and the RBF neural network recognition model is designed. In the selected remote sensing image, the frame feature segmentation processing is implemented, and then combined with dynamic merging conditions, the super-pixel index and parallel recognition parameters are calculated, and the design of dynamic recognition method of remote sensing image frame feature based on edge detection and RBF neural network is completed. The experimental results show that under the action of edge detection and RBF neural network model, the recognition accuracy of the host component for the remote sensing image frame feature object in the three directions of length, width and height has reached 100%, and the problem of resolution overrun has been well solved, which meets the practical application requirements of accurate recognition of remote sensing image features.