A new camera self-calibration approach is proposed based on the property of the vanishing points and the aspect ratio of the rectangle′s two groups of opposite sides. This method can calibrate the camera′s intrinsic parameters and identify the aspect ratio of the rectangle, whether known or unknown the character of camera′s sensor, according to twice or triple imaging for the same rectangle, respectively. The equations of the camera′s intrinsic parameters are established via three properties: the first one is that the lines which connect finite points and the same infinite points are parallel; the second one is the harmonic division which consists in the complete quadrilateral; the third one is the identity length-width ratio of the rectangle which imaged sometimes. A correction method of the camera distortion, utilizing which the accuracy of self-calibration correspond to the no distortion situation, is proposed via iterative between the optimization of nonlinear distortion parameters and solving of linear intrinsic parameters, based on constructing a cost function of lines′ imaging. Simulations prove that the calibration algorithm can converge sharply, and the results are not sensitive to image noise. Real imaging tests prove that, comparing with traditional calibration by flat surface drone, this method can reduce foreknowledge conditions, as well as promoting both precision and efficiency of the calibration results.