Focusing on the issue that high resolution Synthetic Aperture Radar (SAR) image is influenced by speckle noise and road environment is complex, an automatic road extraction method based on fuzzy connectedness was proposed. Firstly, a speckle filtering process was employed to SAR images to reduce the influence of speckle noise. Then seed points were extracted automatically by combining the results of Ratio of Exponentially Weighted Averages (ROEWA) detector and Fuzzy C-Means (FCM) clustering method. Finally, the roads were extracted by using fuzzy connectedness method which characterized by gray level and the edge intensity, and a morphology operation was done to optimize the final result. Comparison experiments between FCM based road extraction method and the proposed method were performed on two SAR images, the detection completeness, correctness and quality of the proposed method were better than those of FCM based road extraction method. The experimental results show that the proposed approach can effectively extract roads from high resolution SAR images without inputting seed points manually.