We present the design and implementation of a Field-Programmable Gate Array (FPGA) based dense stereo depth measurement system that is capable of handling a very large disparity range. The throughput of the system is 60 frames/second on 640 x 240 images. Image rectification and consistency check improve accuracy of the results. The system is based on the Local Weighted Phase-Correlation algorithm [12] which estimates disparity using a multi-scale and multi-orientation approach. Though FPGAs are ideal devices to exploit the inherent parallelism in many computer vision algorithms, their finite resource capacity poses a challenge when adapting a system to deal with large image sizes or disparity ranges. We utilise the temporal information available in a video sequence to design a novel architecture for the correlation unit to achieve correlation over a large range while keeping the resource utilisation very low as compared to a naive approach.