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Estimation of particle depth from two defocused images using the Fourier transform
Particuology ( IF 3.5 ) Pub Date : 2019-07-09 , DOI: 10.1016/j.partic.2019.04.002
Wu Zhou , Xu Luo , Benting Chen , Yukun Zhang , Xiaoshu Cai

Depth from defocus is one technology for depth estimation. We estimate particle depth information from two defocused images captured simultaneously by two coaxial cameras with different imaging distances. The images are processed with the Fourier transform to obtain the characteristic parameter (i.e., the standard deviation of the relative blur kernel of these two defocused images). First, we theoretically analyze the functional relationship between the object depth and the standard deviation or variation of the relative blur kernel. Then, we verify the relationship experimentally. We analyze the influence of particle size, window size and image noise on the calibration curves using both numerical simulations and experiments. We obtain the depth range and accuracy of this measurement system experimentally. For the verification experiments, we use a sample of glass microbeads and the irregularly-shaped dust particles on a microscope slide. Both of these experiments present a suitable depth measurement result. Finally, we apply the measuring system to the depth estimation of drops from a small anti-fogging spray. The results show that our system and image processing algorithm are robust for different types of particles, facilitating the in-line three-dimensional positioning of particles.



中文翻译:

使用傅立叶变换从两个散焦图像估计粒子深度

离焦深度是一种用于深度估计的技术。我们从具有不同成像距离的两个同轴摄像机同时捕获的两个散焦图像中估计粒子深度信息。使用傅立叶变换对图像进行处理以获得特征参数(即,这两个散焦图像的相对模糊核的标准偏差)。首先,我们从理论上分析对象深度与相对模糊核的标准偏差或变化之间的函数关系。然后,我们通过实验验证该关系。我们使用数值模拟和实验分析了粒径,窗口尺寸和图像噪声对校准曲线的影响。我们通过实验获得了该测量系统的深度范围和精度。对于验证实验,我们在显微镜载玻片上使用玻璃微珠和不规则形状的灰尘颗粒的样本。这两个实验都提供了合适的深度测量结果。最后,我们将测量系统应用于小型防雾喷雾的液滴深度估算。结果表明,我们的系统和图像处理算法对于不同类型的粒子具有鲁棒性,有利于粒子的在线三维定位。

更新日期:2019-07-09
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