Paper
15 November 2007 3D profilometry reconstructs based on two-frequency projecting grating method
Yanjun Fu, Wendong Zou, Huirong Xiao, Minggang Chai
Author Affiliations +
Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 67880E (2007) https://doi.org/10.1117/12.744690
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China
Abstract
In the industry, the three dimension of the object is often measured. But the method is usually the contact measurement. And the speed is slowly. The measurement is needed both high precision and fast speed, so the non-contact measurement is required. The grating projecting is the non-contact measurement with prospects. But there are some difficulties in the method. Firstly, when the object has the steps shape or there are shadows in the grating stripes, the disconnected phase can't be correctly unwrapped. Secondly, it is very difficulty to realize the real time digital filter. Now the digital filter is man-machine conversation, so the speed is slowly. Thirdly, in order to measurement the different object, the adaptive grating is needed. In order to resolve the above problems, the grating program is created on the computer. The program has many functions, including the phase shift, the two-frequency grating and the grating frequency is easy to adjust. So the adaptive grating is realized. The two-frequency grating is programmed by the computer. And it is projected to the measured object. The measurement object is placed on the exact rotary platform. The deformed grating is collected in the Charge Coupled Device (CCD). After getting two images, the two images are mosaiced. Then the clear object image modulated by the grating is got. The problem of the steps shape or there are shadows in the grating stripe is worked out. Then the fourier transform is used to process the image. In the traditional fourier transform profilometry, the phase is worked out as follows: After fourier transform, the zero frequency spectra is shifted to the origin of frequency, then filter the needed signal. Then the needed signal is shifted to the center of frequency, and then the zero frequency is shifted to both sides. After inverse fourier transform, the imaginary part is getting, so the phase is getting. But it has a difficult in the above method, because of three times frequency shift, and the center frequency is difficult to confirm, the frequency shift can't be correct and the filter can't be designed correctly, and the error can be transferred, so the result of filter is not well, it has bad effect to the later measurement. The result of measurement is also not well. In order to conquer the difficult, after the fourier transform, filtering the needed signal without frequency shifting, then inverse fourier transform. So the phase relational with the frequency and coordinate is getting. The phase of the reference surface is getting by the same method. Then the difference phase is getting. The real difference phase of low frequency is easy to got, then the real difference phase of high-frequency is work out based on it. At last, according to the relation of difference phase and the height, the three dimensional profilometry of the object is reconstructed. An example of step shape object is done. The three dimensional profilometry is reconstructed successfully. It takes 3 second to reconstruct the three dimensional profilometry. The precision is 0.5mm. The result indicates that the method has conquered the above problems. The result indicates that the method is simple, with fast speed and high precision. Three dimension profilometry measurement of the objected that have the step shape or the shadow in the projecting can be successfully resolved.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yanjun Fu, Wendong Zou, Huirong Xiao, and Minggang Chai "3D profilometry reconstructs based on two-frequency projecting grating method", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 67880E (15 November 2007); https://doi.org/10.1117/12.744690
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KEYWORDS
Fourier transforms

3D metrology

Image processing

Electronic filtering

Modulation

Charge-coupled devices

Digital filtering

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