Fourier descriptor is an important classification method of object contours. At present, most of researchers use only the amplitude of Fourier descriptor whose accuracy is not enough. Aiming at the problem, we presented three methods of fusion of Fourier descriptor’s phase and amplitude to classification of object contours and compared their results. Experimental results show that pixel-level fusion is the most effective method whose classification accuracy is 10% higher than the method for only using the amplitude of Fourier descriptor, but the pixel-level fusion method is timeconsuming because its number of feature vector’s dimensions is much. Comparing Fourier descriptors of pixel level fusion with curvature scale space descriptors and shape context, it is seen that Fourier descriptors are higher timeliness.