Real-time 3-D image analysis via Jacobi moments

Abstract

In this research, we have proposed the parallel GPU-accelerated algorithms to compute the Jacobi moments defined in a rectangular region with substantially improved computational efficiency and highly satisfied accuracy. In our algorithms, the parallel 3-D matrix multiplications are adopted to increase the computational efficiency, while the techniques of coalesced memory access, shared memory and heterogeneous computation are utilized to optimize the computing performance on a GPU platform. Our new GPU-accelerated system can provide any required moment computational accuracy without additional computing time. To verify the performance of our new parallel GPU-accelerated algorithms, we conducted a series of 2D and 3-D image analysis tests via the Jacobi moments with encouraging outcome, while the computing times for all these experimental tasks are in the level of milliseconds. It is expected that our new parallel GPU-accelerated algorithms will expedite the research in 3-D image analysis via the moment methods in the real-time range.