Extrinsic calibration of a camera and a LiDAR is necessary to fuse information from each sensor. The real trajectory of the LiDAR is not visible on an image, therefore the accuracy of the extrinsic calibration is usually checked by evaluating residuals of constraints. In this paper, we present an improved extrinsic calibration algorithm of a camera and a 2D LiDAR using an additional dummy camera removing IR cut filter, which make it possible to observe the real trajectory of LiDAR. Some previous algorithms used the real trajectory of LiDAR for the extrinsic calibration. However, they used IR filter directly on the calibrating camera by adjusting exposure time, which can affect the result of the extrinsic calibration. We use an initial solution using the Hu algorithm which makes extrinsic calibration possible by using just one shot of data. The Hu algorithm gives a sensitive result according to pose variation between a system consisted of a camera and a LiDAR and a calibration structure, which is verified using the real trajectory of LiDAR. We cope with this problem by refining the initial solution through nonlinear minimization in a 3D space using the real trajectory of LiDAR. Experimental results show that the proposed algorithm gives an improved solution.