CN110210359A - Tachometric survey optimization method in space filtering velocity measuring technique - Google Patents
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Abstract
The present invention relates to tachometric survey optimization methods in a kind of space filtering velocity measuring technique to enhance contrast by image preprocessing, and convenient for the extraction of characteristic point, this has good improvement for measuring low-speed motion object in complex environment；By calculus of differences, eliminating part ambient noise bring influences；Suitable grid distance is obtained according to characteristic point size, can be extracted convenient for spectrum peak；Using Welch method, the power Spectral Estimation that available flatness is good, precision is good is convenient for peak extraction.On the basis of existing space filters Computational Method of Velocity Measurement, by the optimization of pretreatment and Power estimation algorithm to sampling picture, more accurate speed is obtained.
Description
Technical field
The present invention relates to a kind of velocity measuring technique, in particular to tachometric survey optimization side in a kind of space filtering velocity measuring technique
Method.
Background technique
Space filtering tests the speed (Spatial Filtering Velocimetry, SFV) technology with its optically and mechanically structure
The optional advantage of simple and stable, light source is more and more paid attention to.When progress space filtering tests the speed, the typical space of use
Filtering device includes rectangular spatial filter, circular space filter and Gauss weighted space filter etc., rectangular filter
It is easier to realize in practical applications, therefore the most commonly used.
Rectangular spatial filter can be simulated by face battle array CMOS camera, the picture of shooting is analyzed and processed,
To obtain rate results.Such as: " non-contact measurement device for measuring and its measurement method of mud-rock flow superficial velocity field distribution " (application is open
Number: CN108344879A) etc., directly ask autocorrelative Fourier transformation to obtain power Spectral Estimation, but obtain in practical application
The pictorial information obtained always contains much noise, and randomness is stronger, and the power Spectral Estimation error obtained using this method is larger, especially
Accurate speed can not be often measured in complex environment.
Summary of the invention
The problem of the present invention be directed to rate accuracy is affected in complex environment proposes a kind of space filtering and tests the speed
Tachometric survey optimization method in technology passes through the pretreatment to sampling picture on the basis of existing space filters Computational Method of Velocity Measurement
And the optimization of Power estimation algorithm, obtain more accurate speed.
The technical solution of the present invention is as follows: tachometric survey optimization method in a kind of space filtering velocity measuring technique, specifically include as
Lower step:
1) under LED white-light illuminating, face battle array CMOS camera acquisition frame rate is set as 1000fps, image model is adopted for gray scale
Collection carries out high speed to region to be measured using face battle array CMOS camera and continuously takes pictures 1 second, and the picture transfer of sampling is entered computer and is waited
Processing, collected picture sample；
2) piecemeal is carried out according to the requirement of user's resolution ratio to acquired image, selects subregion to be measured, it is carried out
Mini-value filtering carries out the binary conversion treatment of image followed by maximum variance between clusters；
3) simulation space-filtering operation is realized using face battle array CMOS camera:
If f (x), f (y) be respectively by camera pixel array it is collected, by ash in step 2) treated picture
Cross, longitudinal gray value function in the matrix of angle value composition；H (x), h (y) are respectively the cross of grating, longitudinal transmission function；
Space filtering theoretical formula is as follows:
s(xr)=∫ f (xr-x)h(x)dx
s(yr)=∫ f (yr-y)h(y)dy
Wherein, xr=vxt+c1,yr=vyt+c2, vxFor the lateral average speed size of subregion to be measured, vyFor sub-district to be measured
Longitudinal average speed size in domain；c1With c2For the dependent constant determined by optical imaging system amplification factor, t is the time for exposure,
R refers to r frame picture；X is the lateral coordinates of the subregion pixel to be measured；Y is the vertical of the subregion pixel to be measured
To coordinate；s(xr) and s (yr) it is that gray value exports；
To the parameter processing of space filtering:
Area to be measured is obtained using picture after enhancing contrast firstly the need of the size of the suitable raster grid spacing of determination
Characteristic point average equivalent area diameter projected is d in domain, then takes raster grid spacing p=2d；
For h (x), h (y), grating simulation is carried out here with the pixel array of face battle array CMOS camera, that is, is obtaining son
In area image, it is sampling interval according to grid distance p, is sampled；
For h (x), the 1st, p+1 ..., np+1 of r frame picture subregion image pixel matrix is classified as by " grating "
Grayscale information after filtering out, and each column extracted are recombinated, it is named as matrix Ar；For h (y), r frame picture subregion figure
As the grayscale information after " grating " filters out of the 1st, p+1 ..., np+1 behavior of picture element matrix, and each row weight that will be extracted
Group is named as matrix Br；Matrix A hereinr、BrThe i.e. visual frame makees the result of product of gray value function and transmission function；
By A obtained in selected framerThe odd column gray value of matrix is added to obtainEven column gray value is added to obtainThen differentiated signal isAll frames are handled by this method, can must export square
Battle array:R=1,2 ..., 1000；
By B obtained in selected framerThe odd-numbered line gray value of matrix is added to obtainEven number line gray value is added
It arrivesThen differentiated signal isAll frames are handled by this method, can must export square
Battle array:R=1,2 ..., 1000；
The two-dimensional matrix that gray value information after simulation grating filters out is constituted；
4) Matrix C that Len got in step 3) is 1000 is divided into K sections, every segment length is N and overlaps each other, to every section
Signal carries out windowing process using Hamming window；I-th section of signal may be expressed as:
Ci(m)=C (m+iE), m=0 ..., N-1；I=0 ..., K-1
M is that number is arranged in signal, and E is the length of overlapping；
Every section of cyclic graph power Spectral Estimation is
W (m) is Hamming window function, and U is the energy of Hamming window function, and f is time-domain signal Ci(m) frequency；
Then it is averaged, finally obtains the power Spectral Estimation of entire C, i.e.,
Frequency from obtaining peak amplitude in entire power Spectral Estimation is denoted as f as maximum frequencyxmax；
Same treatment similarly is made to D, obtains maximum frequency and is denoted as fymax；
5) it is built into scale bar in the plane coplanar with object under test, imaging amplification factor is obtained after comparison, is denoted as M；
6) it seeks the velocity component in all directions: utilizing following formula:
The lateral average speed v of subregion to be measured can be obtainedxSize and longitudinal average speed vySize；
7) velocity composite:
The velocity vector of the available subregion to be measured.
The beneficial effects of the present invention are: tachometric survey optimization method in space filtering velocity measuring technique of the present invention passes through figure
As pretreatment, enhance contrast, convenient for the extraction of characteristic point, this has very well for measuring low-speed motion object in complex environment
Improvement；By calculus of differences, eliminating part ambient noise bring influences；Using Welch method, available flatness is good,
The good power Spectral Estimation of precision is convenient for peak extraction；Suitable grid distance is obtained according to characteristic point size, power spectrum can be convenient for
Peak extraction.
Detailed description of the invention
Fig. 1 is acquired original image；
Fig. 2 is that the present invention carries out pretreated image；
Fig. 3 is the spectrogram directly obtained to the target area of original image using traditional auto-correlation algorithm；
Fig. 4 is that the present invention obtains spectrogram using the algorithm of optimization to pretreated target area.
Specific embodiment
Tachometric survey optimization method in a kind of space filtering velocity measuring technique, comprising the following steps:
Step 1 sets face battle array CMOS camera acquisition frame rate as 1000fps, schemes under the LED white-light illuminating of certain brightness
Picture mode is sampled grey, carries out high speed to region to be measured using face battle array CMOS camera and continuously takes pictures 1 second, by the picture of sampling
It is to be processed to be conveyed into computer etc., collected picture sample；
Step 2 can carry out piecemeal according to the requirement of user's resolution ratio to acquired image, select subregion to be measured,
Mini-value filtering is carried out to it, the binary conversion treatment of image is carried out followed by maximum variance between clusters；
Mini-value filtering is a kind of image processing means, first sequence surrounding pixel sum of the grayscale values center pixel gray value,
Then by center pixel gray value compared with minimum gradation value, if smaller than minimum gradation value, minimum gradation value is substituted for
Heart grey scale pixel value, can eliminate the even bring of uneven illumination using this method influences；
Maximum variance between clusters are a kind of methods that adaptive threshold value determines.It is the gamma characteristic by image, will be schemed
As being divided into two parts of background and target.Inter-class variance between background and target is bigger, illustrates to constitute the two-part of image
Difference is bigger, when partial target mistake is divided into background or part background mistake is divided into target and all two parts difference can be caused to become smaller.Therefore,
The maximum segmentation of inter-class variance is set to mean misclassification probability minimum.It can help to find suitable threshold value using this method, with
Just binary conversion treatment, the picture superposition after binaryzation, convenient for the extraction of characteristic point are carried out；
Step 3 realizes simulation space-filtering operation using face battle array CMOS camera:
If f (x), f (y) be respectively by camera pixel array it is collected, by ash in step 2 treated picture
Cross, longitudinal gray value function in the matrix of angle value composition；H (x), h (y) are respectively the cross of grating, longitudinal transmission function.Space
Filtering theory formula is as follows:
s(xr)=∫ f (xr-x)h(x)dx
s(yr)=∫ f (yr-y)h(y)dy
Wherein, xr=vxt+c1,yr=vyt+c2, vxFor the lateral average speed size of subregion to be measured, vyFor sub-district to be measured
Longitudinal average speed size in domain；c1With c2For the dependent constant determined by optical imaging system amplification factor, t is the time for exposure,
R refers to r frame picture；X is the lateral coordinates of the subregion pixel to be measured；Y is the vertical of the subregion pixel to be measured
To coordinate；s(xr) and s (yr) it is that gray value exports.
To the parameter processing of space filtering:
Area to be measured is obtained using picture after enhancing contrast firstly the need of the size of the suitable raster grid spacing of determination
All characteristic point average equivalent area diameter projecteds are d in domain, then take raster grid spacing p=2d；
For h (x), h (y), grating simulation is carried out here with the pixel array of face battle array CMOS camera, that is, is obtaining son
In area image, it is sampling interval according to grid distance p, is sampled.
For h (x), the 1st, p+1 ..., np+1 of r frame picture subregion image pixel matrix is classified as by " grating "
Grayscale information after filtering out, and each column extracted are recombinated, it is named as matrix Ar；For h (y), r frame picture subregion figure
As the grayscale information after " grating " filters out of the 1st, p+1 ..., np+1 behavior of picture element matrix, and each row weight that will be extracted
Group is named as matrix Br.Matrix A hereinr、BrThe i.e. visual frame makees gray value function and transmission function (i.e. rectangular space filtering
Device) result of product.Due to the introducing of additional light source, need to carry out difference processing to signal, to eliminate part ambient noise.
By A obtained in selected framerThe odd column gray value of matrix is added to obtainEven column gray value is added to obtainThen differentiated signal isAll frames are handled by this method, can must export square
Battle array:R=1,2 ..., 1000.
By B obtained in selected framerThe odd-numbered line gray value of matrix is added to obtainEven number line gray value is added to obtainThen differentiated signal isAll frames are handled by this method, can must export square
Battle array:R=1,2 ..., 1000.
The two-dimensional matrix that gray value information after simulation grating filters out is constituted can be by pixel by above-mentioned difference method
Matrix compression is a gray value, and which greatly enhances Computing efficiency.
Step 4, to output matrix power Power estimation:
The Matrix C that Len got in step 3 is 1000 is divided into K sections, every segment length is N and overlaps each other, and is believed every section
Number utilize Hamming window carry out windowing process.I-th section of signal may be expressed as: Ci(m)=C (m+iE), m=0 ..., N-1；i
=0 ..., K-1
M is that number is arranged in signal, and E is the length of overlapping.E=N/2 indicates that half overlaps each other, and E=N expression does not have
Overlapping.In this way, every section of cyclic graph power Spectral Estimation is
W (m) is Hamming window function, and U is the energy of Hamming window function, and f is time-domain signal Ci(m) frequency:
Then it is averaged, finally obtains the power Spectral Estimation of entire C, i.e.,
Frequency from obtaining peak amplitude in entire power Spectral Estimation is denoted as f as maximum frequencyxmax.Similarly D is made
Same treatment obtains maximum frequency and is denoted as fymax。
Step 5 utilizes the pixel dimension parameter of camera, comparison by measuring pixel size shared by feature object in picture
Feature object actual size, can calculate imaging amplification factor, be denoted as M；
Step 6 seeks the velocity component in all directions:
Utilize formula:
The lateral average speed v of subregion to be measured can be obtainedxSize and longitudinal average speed vySize；
Step 7, velocity composite:
It utilizes
The velocity vector of the available subregion to be measured.
In order to be easy to understand the technical means, the creative features, the aims and the efficiencies achieved by the present invention, lead to below
It crosses embodiment and tachometric survey optimization algorithm provided by the invention is specifically addressed in conjunction with attached drawing.
The picture of acquisition is utilized first and pre-processes enhancing contrast, in picture after treatment, is obtained in region to be measured
Characteristic point average equivalent area diameter projected is d, sets grid distance p=2d.
The size of collected 1000 frame image is 1547*768, and wherein useful area is 1300*600, is utilized
MATLAB divides it, and obtaining size is the subregion for being 135*50.
For subregion to be measured, simulation shading treatment is carried out using MATLAB according to the size of grid distance p, by transmittance section
Each row data divided carry out cumulative summation and obtain the matrix of 1*135.Even number line, odd-numbered line are separately summed, then after will add up
Even number line and odd-numbered line after being added subtract each other the gray scale difference score value for just having obtained the region in this frame image.According to phase Tongfang
Residue frame is made same treatment by method.This method is for acquiring longitudinal velocity vy, seek vxWhen, column are operated.This link is available
Gray value sequence:
Utilize the tachometric survey optimization algorithm of above-mentioned any one, which comprises the following steps:
Step 1 sets face battle array CMOS camera acquisition frame rate as 1000fps, and image model is sampled grey, continuous acquisition
Image；
Step 2 acquires image 1 second, and collected photo is 1000 frames at this time, and preservation is to be processed to computer etc., is adopted
The picture sample collected is as shown in Figure 1；
Step 3, in the plane coplanar with object under test, merging is decorated with the card of 1cm straight line as scale bar scale,
A picture is acquired using face battle array CMOS camera, for measuring imaging amplification factor M；
The size of step 4, collected 1000 frame image is 1547*768, and wherein useful area is 1300*600, benefit
Directly the 1st frame image can be pre-processed from tape function ordfilt2 () and graythresh () with MATLAB, handled
Picture afterwards is as shown in Figure 2.Then it is divided, is divided into the subregion of 135*50.Shown under sub-district domain matrix after division；
Step 5 is sampling interval according to grid distance p, is sampled in obtaining sub-district area image.Sub-district area image
The 1st, p+1 of picture element matrix ..., np+1 is classified as the grayscale information after " grating " filters out, and each column extracted are heavy
Group is named as matrix A1, by A1The odd column gray value of matrix is added to obtainEven column gray value is added to obtain
Then differentiated signal isSimilar processing is carried out to remaining frame by this method, output matrix can be obtained:Similarly by row sampling, can obtain
Step 6, using MATLAB software, carries out power Spectral Estimation, parameter setting using Welch method to it for C, D
Are as follows: window type is Hamming window, and length is 100 points, and FFT points take obtain power convenient for Fast Fourier Transform (FFT) processing at 1024 points
Power estimation figure, (as shown in figure 4, abscissa is frequency f, compared with tradition spectrum estimation method (Fig. 3 institute in obtained power Spectral Estimation figure
Showing) peak value is more obvious, easily facilitate extraction)；
Step 7 obtains the frequency f at peak amplitudexmaxAnd fymax, utilize formula
Obtain the velocity component in both direction；
Step 8 is summed using vector
It can obtain the velocity vector of the subregion；
In the present embodiment tachometric survey optimization algorithm process the following steps are included:
Step S1, setting face battle array CMOS camera parameter；
Step S2, Image Acquisition；
Step S3, merging scale bar obtain amplification factor；
Step S4, picture pretreatment and sub-zone dividing；
Step S5, subregion gray value difference processing；
Step S6 carries out Welch method power Spectral Estimation to result is exported after difference；
Step S7, analyzes power spectrum chart, obtains frequency at peak amplitude, calculates the speed point on different directions
Amount；
Step S8 carries out vector summation to the speed in both direction, obtains velocity vector；
The action and effect of embodiment:
By pretreatment, enhance contrast, convenient for the extraction of characteristic point, this in complex environment for measuring low-speed motion
Object has good improvement；By calculus of differences, eliminating part ambient noise bring influences；It is available using Welch method
The power Spectral Estimation that flatness is good, precision is good is convenient for peak extraction；Suitable grid distance is obtained according to characteristic point size, it can
Convenient for spectrum peak extraction.
Claims (1)
1. tachometric survey optimization method in a kind of space filtering velocity measuring technique, which is characterized in that specifically comprise the following steps:
1) under LED white-light illuminating, face battle array CMOS camera acquisition frame rate is set as 1000fps, image model is sampled grey, benefit
Region to be measured continuously take pictures 1 second at a high speed with face battle array CMOS camera, it is to be processed that the picture transfer of sampling is entered computer etc.,
Collected picture sample；
2) piecemeal is carried out according to the requirement of user's resolution ratio to acquired image, selects subregion to be measured, minimum is carried out to it
Value filtering carries out the binary conversion treatment of image followed by maximum variance between clusters；
3) simulation space-filtering operation is realized using face battle array CMOS camera:
If f (x), f (y) be respectively by camera pixel array it is collected, by gray value in step 2) treated picture
Cross, longitudinal gray value function in the matrix of composition；H (x), h (y) are respectively the cross of grating, longitudinal transmission function；
Space filtering theoretical formula is as follows:
s(xr)=∫ f (xr-x)h(x)dx
s(yr)=∫ f (yr-y)h(y)dy
Wherein, xr=vxt+c1,yr=vyt+c2, vxFor the lateral average speed size of subregion to be measured, vyFor subregion to be measured
Longitudinal average speed size；c1With c2For the dependent constant determined by optical imaging system amplification factor, t is the time for exposure, and r refers to
Generation r frame picture；X is the lateral coordinates of the subregion pixel to be measured；Y is that the longitudinal of the subregion pixel to be measured sits
Mark；s(xr) and s (yr) it is that gray value exports；
To the parameter processing of space filtering:
It is obtained in region to be measured firstly the need of the size of the suitable raster grid spacing of determination using picture after enhancing contrast
Characteristic point average equivalent area diameter projected is d, then takes raster grid spacing p=2d；
For h (x), h (y), grating simulation is carried out here with the pixel array of face battle array CMOS camera, that is, is obtaining subregion
In image, it is sampling interval according to grid distance p, is sampled；
For h (x), the 1st, p+1 ..., np+1 of r frame picture subregion image pixel matrix is classified as to be filtered out by " grating "
Grayscale information afterwards, and each column extracted are recombinated, it is named as matrix Ar；For h (y), r frame picture subregion image slices
Grayscale information of 1st, p+1 ..., the np+1 behavior of prime matrix after " grating " filters out, and each row extracted is recombinated,
It is named as matrix Br；Matrix A hereinr、BrThe i.e. visual frame makees the result of product of gray value function and transmission function；
By A obtained in selected framerThe odd column gray value of matrix is added to obtainEven column gray value is added to obtainThen differentiated signal isAll frames are handled by this method, can must export square
Battle array:
By B obtained in selected framerThe odd-numbered line gray value of matrix is added to obtainEven number line gray value is added to obtainThen differentiated signal isAll frames are handled by this method, can must export square
Battle array:Gray value information after simulation grating filters out is constituted
Two-dimensional matrix；
4) Matrix C that Len got in step 3) is 1000 is divided into K sections, every segment length is N and overlaps each other, to every segment signal
Windowing process is carried out using Hamming window；I-th section of signal may be expressed as:
Ci(m)=C (m+iE), m=0 ..., N-1；I=0 ..., K-1
M is that number is arranged in signal, and E is the length of overlapping；
Every section of cyclic graph power Spectral Estimation is
W (m) is Hamming window function, and U is the energy of Hamming window function, and f is time-domain signal Ci(m) frequency；
Then it is averaged, finally obtains the power Spectral Estimation of entire C, i.e.,
Frequency from obtaining peak amplitude in entire power Spectral Estimation is denoted as f as maximum frequencyxmax；
Same treatment similarly is made to D, obtains maximum frequency and is denoted as fymax；
5) it is built into scale bar in the plane coplanar with object under test, imaging amplification factor is obtained after comparison, is denoted as M；
6) it seeks the velocity component in all directions: utilizing following formula:
The lateral average speed v of subregion to be measured can be obtainedxSize and longitudinal average speed vySize；
7) velocity composite:
The velocity vector of the available subregion to be measured.
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| CN110677582A (en) * | 2019-09-27 | 2020-01-10 | 中国科学院长春光学精密机械与物理研究所 | Filtering speed measurement focus detection method and system and terminal equipment |
| CN111931127A (en) * | 2020-06-29 | 2020-11-13 | 电子科技大学 | Efficient implementation method for power spectral density estimation |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110677582A (en) * | 2019-09-27 | 2020-01-10 | 中国科学院长春光学精密机械与物理研究所 | Filtering speed measurement focus detection method and system and terminal equipment |
| CN110677582B (en) * | 2019-09-27 | 2020-11-24 | 中国科学院长春光学精密机械与物理研究所 | Filtering speed measurement focus detection method and system and terminal equipment |
| CN111931127A (en) * | 2020-06-29 | 2020-11-13 | 电子科技大学 | Efficient implementation method for power spectral density estimation |
| CN111931127B (en) * | 2020-06-29 | 2023-03-14 | 电子科技大学 | Method for realizing power spectral density estimation |
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