Fast Generalized Fourier Descriptor for object recognition of image using CUDA

In recent later years, we can notice a tremendous increase in computer vision research of the recognition forms domain, such as color object recognition. In this framework, we chose the Fourier Descriptor as a method to compute the feature vector of color image. We took as a tool of recognition and classification the Generalized Fourier Descriptor given by F. Smach and al. [1]. The heaviest part of computing time of Fourier Descriptor is the Fast Fourier Transform. In order to accelerate the compute of Fourier Descriptor vector, we proposed a GPU technology of computing. In fact, the aim of this paper is to bring out the computing rapidity of 2D FFT on GPU for each size of image. This approach returns to accelerate the computation of Fourier Descriptor vector under GPU. To showcase this performance, we compared this study with another traditional implement of FFT and Fourier Descriptor on CPU.