针对羟基示踪测速技术在超燃流场应用中测量图像受复杂背景干扰严重的问题, 提出一种提高信号提取能力的方法.该方法通过三个步骤实现信号提取能力的提升：利用霍夫变换进行信号识别; 基于感兴趣区域的大津阈值算法进行图像分割; 结合骨架提取和方向模板方法进行标记线提取.在此基础上, 结合仿真和实验, 验证了该方法可提高超燃复杂背景干扰下的信号提取能力, 解决了提取羟基有效信号精度不够的问题.

A new approaches of Hydroxyl Tagging Velocimetry(HTV) in the application of supersonic combustion flow field signal extraction from images with strong background noise was proposed. These approaches are consisted of three steps: signal recognition through Hough transformation processing, image segmentation using maximum betweenduster variance algorithm based on Region of Interest (ROI), and tagging line extraction using a process combining skeleton extraction and direction template. Based on the above approaches, the image identification ability in the harsh combustion environment with strong background is improved, and the problem of insufficient accuracy in extracting hydroxyl effective signal is solved.