The Novel Method for Moving Frame Using 2D Object Recognition

An Invariant features play a key role in object and pattern recognition studies. Features that are invariant to geometrical transformations offer succinct representations of underlying objects so that they can be reliably identified. In this paper, an invariant features is introduced based on Cartan’s, theory of moving frames. These new features are called summation invariants. Compared to existing invariant features, summations invariants are inherently numerically stable, and do not require computationally complex numerical integrations or analytical representations of underlying data. The new invariant features are applied to 2D object recognition and compared to other methods. A robust method for extracting summation invariants from sampled 2D contours introduced.