AN EXPERIMENTAL COMPARISON OF AUTOREGRESSIVE AND FOURIER-BASED DESCRIPTORS IN 2D SHAPE CLASSIFICATION

An experimental comparison of shape classification methods based on au toregressive modeling and Fourier descriptors of closed contours is ca rried out. The performance is evaluated using two independent sets of data: images of Letters and airplanes. Silhouette contours are extract ed from non-occluded 2D objects rotated, scaled, and translated in 3D space. Several versions of both types of methods are implemented and t ested systematically. The comparison clearly shows better performance of Fourier-based methods, especially for images containing noise.