Digital speckle image correlation method base on particle swarm optimization algorithm
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摘要: 为了能够通过一步搜索同时得到数字散斑图像中所测点的整像素和亚像素位移信息，采用灰度插值的方法构造了亚像素子区，改进了基于微粒子群算法的数字图像散斑相关方法。对含有平移信息的模拟散斑图和具有应变的模拟散斑图进行相关计算，验证了该方法的适用性；在对具有微小面内位移转动的试件进行测量时，比较了整像素的微粒子群算法和不同量级的灰度插值下的亚像素微粒子群算法。结果表明，基于微粒子群算法的亚像素数字散斑图像相关方法在测量小位移方面具有一定的优越性。Abstract: In order to get the integer pixel displacement information and the sub-pixel displacement information simultaneously at one time, the sub-pixel subarea was constructed by using the method of gray interpolation and the digital image correlation method based on particle swarm optimization algorithm was proposed. The applicability of the method was verified by measuring both the simulated speckle pattern with the translational information and with the strain information. And then, the integer pixel particle swarm algorithm and the sub-pixel of different magnitude interpolation gray particle swarm algorithm were compared by measuring the specimen with tiny rotational displacement. The results show that the particle swarm algorithm based on sub-pixel digital scattered spot image correlation method has advantages for small displacement measurement.
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