Image analysis – Histogram processing – For setting a threshold
Patent
1991-03-19
1993-09-28
Razavi, Michael T.
Image analysis
Histogram processing
For setting a threshold
382 42, 7386106, G06K 900
Patent
active
052492389
DESCRIPTION:
BRIEF SUMMARY
e domain of greatest practical interest.
BRIEF DESCRIPTION OF THE DRAWINGS
In the drawings, related figures have the same number but different alphabetic suffixes.
FIGS. 1(a)-1(b): Two digitized images of the random motion of air in a room, illuminated by a copper vapor laser sheet. The image in FIG. 1b was taken 0.5 second after that in FIG. 1a.
FIGS. 2(a)-2(b): a) Subimages of a pair of digitized image arrays b) Spatial cross-correlation function for a sub-image pair, showing shift of the peak from (0,0). This function was computed from two arrays of random numbers, the second generated by shifting the first. After shifting, uncorrelated random numbers were added to each array to simulate noise.
FIG. 3: Flow Chart of the Spatial Cross-Correlation Velocimeter method.
FIGS. 4(a)-4(b): Creation of light sheet from (a) a laser source and (b) from a non-laser source.
FIG. 5: The effect of noise on the determination of the correlation peak between two shifted arrays of a random number set. The ordinate is the amplitude of the second-highest peak in the correlation, as a percentage of the highest. The abcissa is the amplitude of uncorrelated noise as a percentage of the amplitude of the shifted random set.
FIG. 6: Arrangement used in implementation of the SCV method to measure the displacement of a solid surface with sandpaper attached to it.
FIG. 7: 7.times.5 vector plot showing the displacement of the solid surface.
FIG. 8: Measured versus actual values of displacement of the solid surface.
FIG. 9: Arrangement used to implement the SCV method to measure the surface velocity of water around an airfoil placed at high angle of attack.
FIG. 10: Vector plot of separated flow over the airfoil.
FIG. 11: Vector plot of instantaneous water surface velocity behind a circular cylinder.
FIG. 12: Arrangement for SCV around a wing in a 2.14 m.times.2.74 m wind tunnel.
FIGS. 13(a)-13(c): Sequence of instantaneous velocity plots around the wing in plunging motion.
FIG. 14: Spatial cross-correlation between sub-images with quasi-periodic intensity distributions.
DESCRIPTION OF THE PREFERRED EMBODIMENT
Transfer of momentum in fluids occurs primarily through large, coherent flow structures. These structures have finite lifetimes, so that there must be some degree of correlation between the features of two images taken within a time interval which is shorter than the integral time scale of the local motion. The desired end result is an accurate, quantitative representation of the velocity vector at as many points as possible in the area of interest. The differences between the two images would be caused by the following:
a) convection of features by the mean fluid motion,
b) exchange of fluid across the illuminated region,
c) distortion of the flow structures by shear and dilatation,
d) noise in the image acquisition and processing.
The problem is to determine the direction and magnitude of (a), and the detailed velocity distribution from (c), despite the errors and noise caused by (b) and (d). If (a) overwhelms the other effects, the displacements of given features of the image can be easily measured at a few points, averaged, and converted to velocity using the known time difference between the two images. When effects (b), (c), and (d) are present, this must be performed statistically, using information from every element of the two images. This is achieved by spatial cross-correlation.
To obtain an image, the flow is "seeded" with particles which scatter light. Alternatively, in some flows, the motion of density gradients or concentration gradients can be detected. As seen from FIG. 1, one needs to distinguish only the patterns formed by large numbers of particles, not the individual particles themselves, to discern fluid motion. Also, the patterns can be statistically random. In fact, the more random they are, the easier it is to obtain and interpret the results.
Consider a cross-section A of a flowfield, shown in FIG. 1(a), illuminated with intensity I.sub.1 (x,y) of light or other electromagnetic radiation. We assum
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Fawcett Philip A.
Komerath Narayanan M.
Jung Yon
Razavi Michael T.
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