A Construction Method of Stripe Filter in Optical Measurement

Abstract

The invention discloses a method for constructing a fringe filter in optical measurement. The filter belongs to a spatial filter, and adopts a sine-aided sieving calculation method to directly separate the fringe component from the image by setting a suitable filter size. Come out, first, perform two-dimensional autocorrelation calculation on the stripe image in the air domain, extract the horizontal and vertical central axes of the autocorrelation coefficient, and perform correlation calculation on the two, and the obtained coefficient covers the common periodic information in the horizontal and vertical directions; secondly , extract the period information in the correlation coefficient, and analyze its change and trend, and then estimate the maximum cut-off space period corresponding to the maximum local deformation in the streak component, and use this period as the size of the streak filter; finally, through the sinusoidal auxiliary The sieving calculation of the method directly filters out the fringe components containing important information for subsequent calculation processing. The beneficial effect of the invention lies in that the method is simple, fast and robust, and has great practical potential.

Description

technical field [0001] The invention relates to the technical fields of optics, computer vision and artificial intelligence, in particular to a method for constructing a fringe filter in optical measurement. Background technique [0002] The grating projection three-dimensional measurement technology has achieved effective measurement of static or slow moving objects, but the measurement of dynamic fast objects by this technology is still in the research stage. The most important point of dynamic fast measurement is the processing of a single fringe image, and its calculation method is also affected by the comprehensive influence of calculation accuracy and speed. [0003] The traditional Fourier-based method can achieve effective measurement of single-frame fringe images, but it will be interfered by low-frequency background ambient light, making frequency-domain filtering extremely difficult and inaccurate. In order to improve this The problem is that there are various ti...

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Problems solved by technology

[0006] The background light filtering of fringe images is difficult to be adaptive, fast and robust; the time-frequency analysis method based on Fourier theory is prone to problems such as spectrum aliasing, large amount of calculation, and many parameters need to be preset; The empirical mode decomposition method is easy to be imprisoned by the idea of ​​decomposing first and then classifying, which will generate a large number of iterative calculations. The classification rules need to be set extremely complicated but it is still difficult to guarantee robustness

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