In this paper, we present a novel approach for real-time object identification on a mobile platform. First, our system detects keypoints within a scaled pyramid-based FAST detector and then descriptors of the object of interest are computed using an Analytical Fourier-Mellin transform. The Fourier-Mellin is used in similarity studies due to its invariance property and discrimination power. In this approach, we exploited information from the phase of Fourier Transform instead of magnitude applied on patches. The phase carries more information and handle, particularly, rotation and light changes. Finally, experiments are conducted to evaluate the system performances in terms of accuracy, robustness and computational efficiency as well