A novel line-scan camera calibration method in close-range photogrammetry is proposed. Since the line-scan camera is only sensing in one dimension, it's hard to recognize the space points from the linear data captured in static state. To address this problem, the camera is fixed to a programmable linear stage. With the help of the linear stage, a scan image of the pattern is grabbed by the line-scan camera in uniform rectilinear motion state. Therefore, the image points are definitely matched with the space points on the pattern. A pair of projective equations is established to describe this dynamic imaging model, which is determined by six extrinsic camera parameters, five intrinsic camera parameters and three other motion parameters. All the fourteen parameters are estimated approximately by using the direct linear transformation of a reasonably simplified camera model firstly, and then the results are further refined by non-linear least square mean (LSM). Both computer simulated data and real data are used to test our calibration method. The robustness and accuracy are verified by lots of simulated experiments, and for the real data, the root mean square error of re-projected points is less than 0.3 pixels.