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In Optics express

In traditional focimeter measurements, the lens cannot completely coincide with the diaphragm owing to the change of radius, resulting in an increase in the power measurement error with an increase in the lens power. We proposed a method, using the SVM machine learning algorithm, to restore the measurement of the focimeter, using a lens power data set obtained from lens features, obtained through an automatic acquisition system. Total up to 83 groups of single focus lenses with refractive indices of 1.56 and 1.60, ranging from -10 m-1 to + 8 m-1 every 0.25 m-1 and -10.5 m-1 to -15 m-1 every 0.5 m-1, were used for lens image acquisition. The experimental results show that the ten-fold average F1 score of the classification under this method is 100%. The test lens power can be accurately identified and the measurement error can be overcome.

Jin Tao, Gao Xuan