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conferenceseries
.com
July 17-19, 2017 Chicago, USA
World Congress and Expo on
Optometry & Vision Science
Volume 2, Issue 1 (Suppl)
Optom Open Access, an open access journal
ISSN:2476-2075
World Optometry 2017
July 17-19, 2017
The application of phase-shifting technique in surface topographic measurement
Yuhe Li
Tsinghua University, China
Statement of theProblem:
Surface topographicmeasurement plays an increasingly significant role inopticalmeasurement, such
as automatic visual inspection, ultra-precision manufacturing and other fields. The latest hard drives and optical instruments
require the chips with ultra-fine surfaces, as well as the corresponding detecting technique to carry out online measurement
and monitor the relevant parameters. The phase-shifting interferometry is one of the most widely applied technique of which
the principle is introducing time modulation into the phase difference of two beams of coherent light. By the photoelectric
detector the phase can be demodulated from the interference pattern via considerable phase-unwrapping algorithms. However,
the inevitable noise leads to the error and distortion of several points in the phase diagram.
Methodology & Theoretical Orientation:
We propose a K-means clustering unwrapping algorithm for the error reduction.
Based on "bad points" to avoid the path integral, our algorithm can complete the three-dimensional morphology online.
Compared with the traditional algorithms which might result in failure to unwrap when the reference points happen to be
noise points, our algorithm is put forward to extract independent noise areas, such as faults, holes, etc. and can separate the
effective phase information by using the clustering analysis. The detailed algorithm is as follows: (1) Giving pixel gray difference
T of each cluster center, and then calculating the clustering parameter K based on the interference pattern; (2) Considering
K and the gray values g of each pixel as variables and analyzing the pixel set G in clustering process; (3) Establish the original
image index matrix, generating new clustering image by replacing the original pixel values with new clustering centroids and
separating independent noise area according to the distance d and weight τ and (4) Completing the unwrapping calculation.
Conclusion & Significance:
We build the surface topographic experiment system and the error has been successfully made
less than 0.004 µm. Therefore, the K-means clustering unwrapping algorithm, of which the result is compared to that of the
calibration equipment, has been valid. Consequently, the relevant online measurement can be more accurate..
Biography
Yuhe Li received his Ph.D. degree in 2001 from Tsinghua University, now he is associated professor in Tsinghua University. His main research interests include
micro and Nano measurement and machine vision.
liyuhe@mail.tsinghual.edu.cnYuhe Li, Optom Open Access 2017, 2:1 (Suppl)
DOI: 10.4172/2476-2075-C1-003