Experimental studies of multiple shock wave interaction to study transition from regular to irregular reflection rely on the processing of a large amount of schlieren photographs. Here we present an automated algorithm to track individual shock fronts and triple points. First, correction to any optical distortions is applied to the photographs. Next, noise removal and edge detection algorithms are implemented to extract the pixel locations of the shocks. The edge detection algorithm takes advantage of the light intensity feature of the shock waves to distinguish shock fronts from background noise. This algorithm is also capable of separating entangled shock fronts through pattern recognition, which utilizes a discretization method to reduce complex shock geometries to localized linear patterns. Collectively, the algorithms can track shock wave characteristics to sub-pixel precision. This algorithm has been deployed for post processing of shock wave experiments to extract shock wave characteristics including positions and propagation velocities of shock fronts, vertical and horizontal velocities of Mach stems, and triple point trajectories during shock-shock interactions. Results show that the algorithm can process large volumes of data with minimal manual operations, making image processing more precise, efficient and productive while allowing for tracking of Mach stems and triple points.

中文翻译：

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量化冲击波动力学实验的图像处理和边缘检测技术

研究从规则反射到不规则反射的过渡的多重冲击波相互作用的实验研究依赖于对大量纹影照片的处理。在这里，我们提出了一种自动算法来跟踪单个激波前沿和三重点。首先，对照片进行任何光学畸变的校正。接下来，实施噪声去除和边缘检测算法以提取冲击的像素位置。边缘检测算法利用冲击波的光强特征来区分冲击波前沿和背景噪声。该算法还能够通过模式识别分离纠缠的激波前沿，利用离散化方法将复杂的激波几何结构简化为局部线性模式。总的来说，该算法可以将冲击波特性跟踪到亚像素精度。该算法已部署用于激波实验的后处理，以提取激波特征，包括激波前沿的位置和传播速度、马赫杆的垂直和水平速度以及激波相互作用期间的三点轨迹。结果表明，该算法可以以最少的手动操作处理大量数据，使图像处理更加精确、高效和高效，同时允许跟踪马赫干和三点。和冲击-冲击相互作用期间的三点轨迹。结果表明，该算法可以以最少的手动操作处理大量数据，使图像处理更加精确、高效和高效，同时允许跟踪马赫干和三点。和冲击-冲击相互作用期间的三点轨迹。结果表明，该算法可以以最少的手动操作处理大量数据，使图像处理更加精确、高效和高效，同时允许跟踪马赫干和三点。