The interior tomography is commonly met in practice, whereas the self-calibration method for geometric parameters remains far from explored. To determine the geometry of interior tomography, a modified interval subdividing based method, which was originally developed by Tan et al., was presented in this paper. For the self-calibration method, it is necessary to obtain the reconstructed image with only geometric artifacts. Therefore, truncation artifacts reduction is a key problem for the self-calibration method of an interior tomography. In the method, an interior reconstruction algorithm instead of the Feldkamp—Davis—Kress (FDK) algorithm was employed for truncation artifact reduction. Moreover, the concept of a minimum interval was defined as the stop criterion of subdividing to ensure the geometric parameters are determined nicely. The results of numerical simulation demonstrated that our method could provide a solution to the self-calibration for interior tomography while the original interval subdividing based method could not. Furthermore, real data experiment results showed that our method could significantly suppress geometric artifacts and obtain high quality images for interior tomography with less imaging cost and faster speed compared with the traditional geometric calibration method with a dedicated calibration phantom.