In this paper, we discuss the design and implementation of a Field-Programmable Gate Array (FPGA) based stereo depth measurement system that is capable of handling a very large disparity range. The system performs rectification of the input video stream and a left-right consistency check to improve the accuracy of the results and generates subpixel disparities at 30 frames/second on 480 ? 640 images. The system is based on the Local Weighted Phase- Correlation algorithm [9] 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, they have a finite resource capacity which poses a challenge when adapting a system to deal with large image sizes or disparity ranges. In this work, we take advantage of 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 of designing a correlation unit in hardware.