Robust and real-time automatic target recognition using partial hausdorff distance measure on reconfigurable hardware

Abstract

This paper presents a high performance FPGA-based automatic target recognition system, which matches TV templates with an image efficiently. Theoretically, image matching algorithms based on partial Hausdorff distance (HD) are more tolerant of perturbations in the locations of pixel points than other algorithms, but they are too computationally expensive to be used in embedded systems. In order to solve this problem, we present a robust and real-time implementation of the image matching algorithm based on partial HD, taking advantage of the hardware resources offered by the FPGA chips. A parallel target recognition algorithm under constraints of limited embedded memory and limited memory bandwidth is proposed first. And then the system is organized as a coarse-grained pipeline containing three stages. Each stage is implemented in highly parallel fashion. The implementation of distance transform and template matching are described in detail. Experimental results show that our work outperforms related proposals. A speedup of almost 50 is achieved while compared with the software solution in PC (Pentium 4 2.8 GHz)