Dot tracking methodology for background-oriented schlieren (BOS)

Abstract

We propose here a dot tracking methodology for processing background-oriented schlieren (BOS) images. The technique improves the accuracy, precision and spatial resolution compared to conventional cross-correlation algorithms. Our methodology utilizes the prior information about the dot pattern such as the location, size and number of dots to provide near 100% yield even for high dot densities (20 dots/32 × 32 pixels) and is robust to image noise. Furthermore, we propose an improvement to the displacement estimation step in the tracking process, especially for noisy images, using a “correlation correction”, whereby we combine the spatial resolution benefit of the tracking method and the smoothing property of the correlation method to increase the dynamic range of the overall measurement process. We evaluate the performance of the method with synthetic BOS images of buoyancy-driven turbulence rendered using ray-tracing simulations, and experimental images of flow in the exit plane of a converging–diverging nozzle. The results show that the improved spatial resolution results in a better accuracy of the tracking method compared to correlation-based methods in regions with sharp displacement gradients, and the correlation correction step reduces the noise floor of the measurement, resulting in a fourfold improvement in the dynamic range.