GPU Acceleration of Zernike Moments for Large-scale Images

Zernike moments are trascendental digital image descriptors used in many application areas like biomedical image processing and computer vision due to their good properties of orthogonality and rotation invariance. However, their computation is too expensive and limits its application it? practice, overall when real-time constraints are imposed. This work introduces a novel approach to the high-performance computation of Zernike moments using CUDA on graphics processors. The proposed method is applicable to the computation of an individual Zernike moment as well as a set of Zernike moments of a given order, and it is compared against three of the fastest implementations performed on CPUs over the last decade. Our experimental results on a commodity PC reveal up to 5x faster execution times on a GeForce 8800 GTX against the best existing implementation on a Pentium 4 CPU.