Abstract: In order to detect the frequency hopping signals at the communication countermeasures, a texture feature based algorithm is proposed. In this algorithm the received signals are represented as time-frequency diagram, and texture features are extracted from the time-frequency diagram by using gray level co-occurrence matrix (GLCM). Then the background noise can be removed through the separation of texture features, and the salt-and-pepper noise after binaryzation is eliminated by morphological filtering. Then labeling all the connected components in the time-frequency diagram to get the location information, and removing the frequency-fixed and burst interference by means of clustering, so the frequency hopping signals can be detected automatically. Simulation results show that the algorithm can separate the background noise from the signals more effectively, and can detect frequency hopping signals even when the Signal Interference Noise Ratio (SINR) is low.