Invariance is widely used in 3-D object recognition due to its good performance on change of viewpoint. A method of computing 3-D invariants of seven points from two images is presented, which can be used to achieve reliable recognition of a 3-D object and scene. Based on the matrix representation of the projective transformation between 3-D and 2-D points, geometric invariants are derived by the determinant ratios. First, the general ratiocination about invariants is represented. Second, the general method of deriving 3-D invariants from images is proposed. Simulation results on real images show that the derived invariants remain stable and are quite robust and accurate.