Recognition of bridge over water in remote sensing image using Discrete Hopfield Neural Network

Target recognition in remote sensing image is a complicated pattern recognition task. In this paper we propose a new method of recognition of bridge over water in remote sensing image. Various techniques were applied to the process. Image segmentation and mathematics morphology techniques were used to find out water areas and locate the ROIs(Regions of Interest), and then feature extraction and HNN were utilized to recognize the bridge. During the process, we also introduced a workable method of binary coding specific to Discrete Hopfield Neural Network. The results show that the process we propose is an effective method to fulfil the task. The main contribution of this paper lies in successfully applying Discrete Hopfield Neural Network, which few scholars used before, in recognition of bridge in remote sensing image.