基于高频方差熵清晰度评价函数的聚焦三维测量方法

3D profile measurement based on depth from focus method using high-frequency component variance weighted entropy image sharpness evaluation function

  • 摘要: 图像清晰度评价函数是聚焦恢复深度法(Depth from Focus, DFF)实现三维形貌测量的核心,直接决定了深度方向的测量精度。文中提出了一种基于高频方差熵的图像清晰度评价函数,与常用函数对比了清晰度比率、灵敏度因子两个定量指标,结果表明所提函数优于常用函数。通过对所提函数获得的清晰度评价曲线进行高斯曲线拟合,实现了深度方向聚焦位置的精确计算。对文中方法开展了聚焦重复性与标准台阶高度测量测试,重复性聚焦实验的测量标准差为2.82 μm,台阶高度测量标准差为12 μm,验证了文中方法用于高精度非接触三维测量的可行性。

     

    Abstract: Image sharpness evaluation function is the core of Depth from Focus (DFF) method for 3D profile measurement. Crucially, the accuracy of depth measurement is determined by the evaluation function. An image sharpness evaluation function using high-frequency component variance weighted entropy was proposed. The quantitative indicators including the resolution ratio and the sensitivity factor were used to test the proposed function and the common functions. The comparative data showed that the proposed function could achieve better focusing performance than the other functions. The focusing position in depth direction could be precisely confirmed by implementing the Gaussian fitting to the image sharpness curve calculated through the proposed function. Focusing repeatability and standard step height measurement were tested. The standard deviation of the data of the focusing repeatability experiment was 2.82 μm. And the standard deviation of the measurement height of the standard step was 12 μm. The result verifies the feasibility of the proposed method for high precision non-contact 3D measurement.

     

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