In this paper, we present a new algorithm for estimating individual vehicle speed based on two consecutive images captured from a traffic safety camera system. Its principles are first, both images are transformed from the image plane to the 3D world coordinates based on the calibrated camera parameters. Second, the difference of the two transformed images is calculated, resulting in the background being eliminated and vehicles in the two images are mapped onto one image. Finally, a block feature of the vehicle closest to the ground is matched to estimate vehicle travel distance and speed. Experimental results show that the proposed method exhibits good and consistent performance. When compared with speed measurements obtained from speed radar, averaged estimation errors are 3.27% and 8.51% for day-time and night-time test examples respectively, which are better than other previously published results. The proposed algorithm can be easily extended to work on image sequences.