A displacement measurement method of micro/nano scale based on neighbor principal feature matching

A new sub-pixel displacement measurement method is proposed based on the neighbor principal feature matching. The improved main features extraction process enhances the accuracy and stability of the algorithm by reconstructing divergence correction matrix and maximizing the distance of adjacent image blocks. The overall micro/nano scale measurement method is designed based on the neighbor principal feature matching by off-line training process, and the simulation verifies the accuracy of the method which is used for the image blocks with different sizes and positions. The high-precision nano platform, the high power microscope and the standard grid are used together to validate the measurement. The accuracy of the algorithm is increased by nearly 10 times compared with the conventional blocks matching method. Further, the algorithm has higher robustness in selecting the position and size of the image blocks.