In the image analysis via the general theory of moments, some shortcomings were discovered. The major disadvantages of the method of moments are that although the first few moments convey significant information for simple objects, they fail to do so for more complicated objects. The computed invariant moments are expected not to be strictly invariant in the presence of noise, and the computation of moment invariants is time-consuming. In this paper, an effective image analysis method based on the algebraic method is presented. First, a new coordinate transformation from an object image to an invariant matrix is proposed. The invariant matrix representation is independent of image translation, scaling, and rotation. On the basis of invariant matrix, a robust algebraic recognition method based on the projective image is developed. The projective coordinates of projective image on feature images are used as the feature vectors which represent the inherent attributes of objects. In order to test the efficiency of our method, it is used to solve the recognition problem of two-dimensional aircraft models. Theoretical and experimental results show that our method is very reliable for image analysis and the extracted algebraic features are invariant to image translation, scaling, and rotation.