双目体视粒子图像测速系统优化设计

Optimal Design for Stereo Particle Image Velocimetry Based on Binocular Vision

基于视觉原理提出了基于匹配查询的体视粒子图像测速算法。该方法首先使用互相关算法对双目像平面上的粒子像进行匹配,通过相关结果进行同名区域查询;然后通过回归检测对错误的匹配点进行剔除。该算法不仅可以成功的对四个像平面上的兴趣区域进行同名域的判断,而且具有较高的信噪比。最后,使用人工合成的粒子图进行了算法验证及误差分析。结果表明:所提算法可以有效地对空间流场进行运动信息的提取。

An optimal matching method for stereo particle image velocimetry （SMPIV） was proposed based on computer vision theory. In the proposed algorithm, firstly, cross-correlation method was used to evaluate interrogation region and to find the same space region in different images. Secondly, the number of false matching points was reduced by regression detection. Using the proposed SMPIV method, the corresponding region of four images could be found with higher SNR. Synthetic particle images were tested and the errors were analyzed. The experimental results show that the proposed method is an effective and robust algorithm for extracting motion information in fluid field.