FPGA implementation of normalized cross-correlation for real-time template matching in dynamic search windows

Abstract

In computer vision crass-correlation is a standard approach for local feature matching in feature tracking applications. For this Normalized cross-correlation (NCC) is implemented on spatial domain, because it does not have a simple and efficient frequency domain expression. Therefore in applications which demand real-time processing, a dedicated hardware implementation of NCC is essential to meet the computational cost in spatial domain. In this paper we present a Field Programmable Gate Array (FPGA) implementation of NCC based on the multi-port memory controller together with Fast Normalize Cross-correlation. Practical experimentation shows that our system can achieve frame rates closer to 100 for a search window size of 100x100 and template size of 15x15, with only using two dual-port memories.