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Measuring the movement of raster by the method of moiré fringe has the
advantage of high sensitivity, high resolution and non-contacted measurement. The
characteristic of moiré fringe is that the image is white alternate with black, the angle
of the stripes is uniform, the width of the stripes is uniform, the terminators of the
stripes aren't clear. A fast method that can figure out the width and angle of the moiré
fringe precisely is put forward in this paper. It calculates the angle the stripes firstly.
According to the principle of the minimum mean squared error (MMSE), the closer a
series of data is, the smaller the value of the MMSE will be. The method is described
as follows: It takes the image's center as the origin, 180 beelines pass through the
origin with the same angle interval. it calculates the value of the minimum mean
squared error of the 180 beelines and find out the least one among those, then the
angle of the moiré fringe α comes out primarily. In order to improving the calculating
precision of moiré fringe, 60 equal angles are divided in the neighborhood of the
angle α, then a precise angle β of moiré fringe is calculated according to the principle of the MMSE. After getting out the angle of the moiré fringe, we begin to calculate the width of moiré fringe. A line vertical with the moiré fringe is drawn, and we can get the width of the moiré fringe by the vertical line. In order to get over the influence of the noise, an effective area with the shape of diamond is selected in the image. The data of area is accumulated and projected according to the direction of moiré fringe, and a sine curve come out. The width of moiré fringe can be obtained by getting the position of the first wave crest, the position of the last wave crest and the number of wave crest. Experiments prove that the precision of the method put forward in this paper is enhanced in comparison with the traditional frequency method, the precision of width calculation achieves to 99.6% according to the evaluation indicators of width detection error. The computing speed is boosted largely compared with traditional method, and it can achieve with 15 ms, that satisfying the demand of real time.
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