129 線形アフィン変換による粒子追跡アルゴリズム

Abstract

In Particle Image Velocimetry (PIV), the cross correlation tracking technique is widely used to analyze the particle images. The actual flow fields may have some distorted motion, such as rotation, shear and expansion. When the distortion of the flow field is not negligible, the fluid motion can not be tracked well using the cross correlation technique.The author proposed a new particle tracking technique, based on the particle cluster matching using linear Affine Transformation. The deformation of the cluster pattern is expressed by the linear Affine Transformation. The parameter of the transformation can be determined using the least square technique from the particle positions. The effectiveness of the tracking techniques, including 3D cross correlation, Spring Model and Affine Transform, were evaluated with synthetic data of three-dimensional flow field. The 3D cross correlation technique could be applicable to the small deformation cases. When the deformation of particle pattern between two images are very large, the pattern deformation could not be expressed by the Affine Transformation, i.e., linear transformation, resulting in the miss-tracking. While, the Spring Model technique was found to be more effective even in the larger deformation condition, because the Spring Model does not assume the linear transformation.