Planar Object Recognition Based on Characteristic Ratio

Pattern recognition is an important research field in artificial intelligence. The stability of recognition under projection and affine transformation, especially under sever deformation has long been recognized as an important and difficult problem. In this paper, a novel geometry invariant named characteristic ratio(CHR) resistant to affine deformation is proposed. A new feature descriptor is also constructed based on this, which presents an image as the relationship of collinear points by a series of straight lines cross the image. Then, characteristic ratio is calculated by the position of collinear points, and the image is represented by a sequence of characteristic ratio spectra(CHRS). Finally, dynamic time warping (DTW) algorithm is employed to compare the similarity of spectra and to find the pixel level correspondence between two planar objects. It shows that the proposed method has not only good resistance to severe affine deformation, but also good discriminating ability to similar images.