CN105066904B - Streamline product tri-dimensional facial type detection method based on phase gradient threshold value - Google Patents
Streamline product tri-dimensional facial type detection method based on phase gradient threshold value Download PDFInfo
- Publication number
- CN105066904B CN105066904B CN201510420768.9A CN201510420768A CN105066904B CN 105066904 B CN105066904 B CN 105066904B CN 201510420768 A CN201510420768 A CN 201510420768A CN 105066904 B CN105066904 B CN 105066904B
- Authority
- CN
- China
- Prior art keywords
- mrow
- phase
- msub
- abrupt change
- change region
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Landscapes
- Image Analysis (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention belongs to online tri-dimensional facial type detection field, particularly disclose a kind of streamline product tri-dimensional facial type detection method based on phase gradient threshold value, solve the problem of prior art is present, take into full account that online tri-dimensional facial type detection, to measuring speed and the balance of required precision, proposes the streamline product tri-dimensional facial type real-time detection method based on phase gradient threshold value.The overall phase information of testee is obtained by the method for Fourier transformation, the Grads threshold of phase is participated in into related operation as characteristics of image and obtains phase shift striped, body surface abrupt change region is obtained to the expansion of binaryzation dephasing gradient figure, the phase distribution in abrupt change region is finally iterated to calculate using least square method, precision is obtained to improve phase for correcting FTP result of calculation.
Description
Technical field：
The invention belongs to online tri-dimensional facial type detection field, more particularly to a kind of streamline based on phase gradient threshold value
Product tri-dimensional facial type detection method.
Background technology：
Online tri-dimensional facial type detection belongs to the category of dynamic detection, and dynamic detection need to take into full account the real-time of measuring method
Property.Fringe projection technology of profiling calculates deforming stripe phase to obtain the three of object by projecting sinusoidal light in testee
Tie up information, this method has that contactless, measurement accuracy is considerable, simple to operate, the low advantage of measurement cost, available for streamline production
The on-line checking of product three-dimensional dimension.
In many algorithms of fringe projection technology of profiling, Fourier transform profilometry (Fourier transform
Profilometry, abbreviation FTP) it is usually used in dynamic measurement, it uses the method for Fourier analysis to obtain phase information, with complete
The advantage of field analysis, but due to being related to frequency domain filtering, cause object plane type sudden change region measurement accuracy to be restricted.
Phase measuring profilometer (phase measuring profilometry, abbreviation PMP) uses phase-shifting technique point pair
The method that point calculates phase, the change to background, contrast and noise is insensitive, and measurement accuracy is high.But needed in measurement process
Gather at least three frame deforming stripes to calculate a frame phase information, the motion of object causes thing in different bar graphs in dynamic measurement
The position of body image is changed, and error is brought to PMP phase calculations.Overcome this problem, CCD is not required nothing more than with higher
Filming frequency, also requires that projector equipment has equivalent projection switching frequency, what Iowa state universities of U.S. Zhang Song et al. was proposed
Real-time three-dimensional detecting system can be used for online three-dimensional values, but system hardware is had higher requirements.
Sichuan University Cao Yi equalitys people keeps the movement characteristic of translation according to streamline product, and proposition pixel matching is by thing
The method that displacement body is converted to striped phase shift, solves what the deforming stripe figure object space not photographed in the same time changed
Problem, so as to reduce to projection, the requirement of frequency acquisition.Wherein the online PMP based on Stoilov algorithms uses metrological grating
Sensor produces trigger signal to control CCD to shoot the deforming stripe figure of the equidistant movement of object, by object after pixel matching
Displacement be converted into striped phase in-migration calculate object phase distribution.
In order to reduce the complexity of measuring system control section, at the same improve solution phase precision, they propose again based on
The online PMP of the phase shift algorithms such as full cycle.This method projects multiframe phase shift bar graph, it is desirable to movement direction of object and striped phase shift
Direction is vertical, and object of which movement does not produce equivalent phase shift after pixel matching so that the phase-shift phase of the deforming stripe figure collected is equal to
The phase-shift phase of projected fringe, realizes the purpose of the artificial coding-control of phase-shift phase.But in actual measurement process, it is difficult to accurate control
The shift direction of projected fringe is vertical with the direction of motion of object, and the systematic error of out of plumb will cause it is each after pixel matching
Frame deforming stripe figure produces additional phase shift amount in striped shift direction, and phase is introduced when calculating phase using phase shift algorithms such as full cycles
Shift error, reduces phase calculation precision.
In view of the above-mentioned problems, propose to obtain any phase-shift phase using pixel matching again, iterated to calculate using least square method
The method of phase, not only increases measurement accuracy, also reduces the constraints of system and device locus.But least square method
Iterate to calculate phase time-consuming longer, be unfavorable for the raising of system real time.
From above-mentioned discussion, either still iterated to calculate, do not had using least square method using Fourier transformation
Take into full account tri-dimensional facial type detection to measuring speed and the balance of required precision.Fourier transform profilometry real-time is good, but
Measurement accuracy is not high, and measurement error concentrates on the abrupt change region of the honorable type of measured object.Least square method iteration measurement accuracy is high, but
Iteration time is long, have impact on the real-time of measurement.
The content of the invention：
The present invention overcomes the shortcomings of that prior art is present, and solves the problem of prior art is present, takes into full account online three
The type detection of dimension face proposes the streamline product three-dimensional surface based on phase gradient threshold value to measuring speed and the balance of required precision
Type real-time detection method.The overall phase information of testee is obtained by the method for Fourier transformation, by the gradient threshold of phase
Value participates in related operation as characteristics of image and obtains phase shift striped, and body surface abrupt change is obtained to the expansion of binaryzation dephasing gradient figure
Region, finally iterates to calculate the phase distribution in abrupt change region using least square method, for correcting FTP result of calculation to improve
Phase obtains precision.
In order to solve the above technical problems, the technical solution adopted by the present invention is：Streamline production based on phase gradient threshold value
Product tri-dimensional facial type detection method, detection process is followed the steps below：
Step 1) projector sinusoidal grating picture is in testee, and CCD gathers deforming stripe figure not in the same time；
When on conveyer belt without testee, the bar graph that CCD is not photographed in the same time does not change, its light distribution
It is represented by：I0(x, y)=R (x, y) [A (x, y)+B (x, y) cos φ0(x,y)] (1)
R (x, y) is body surface reflectivity in formula, and A (x, y) is background light intensity, and B (x, y) is fringe contrast；φ0(x,
Y) it is distributed for fringe phase；
When measurement object is moved with conveyer belt, CCD does not collect deforming stripe figure in the same time, and its light distribution can be represented
For：
Ii(x, y)=R (x, y) [A (x, y)+B (x, y) cos φi(x, y)] i=1,2 ... M (2)
φ in formulai(x, y) is the phase distribution of body surface deforming stripe, and object of which movement makes it as in every frame deforming stripe
Position in figure is different, and the distribution of the phase-modulation of generation is also different, is distinguished with subscript i；M represents to shoot frame number；
Step 2) phase obtain and phase only pupil filter：
A, calculated per phase place change φ caused by object height in frame bar line with the method for Fourier transformationi(x,y)：
Fourier transformation is made to formula (2) ,+1 grade of fundamental component is filtered out, remaking inverse Fourier transform can obtain：
Same computing is done to the light distribution (1) obtained of CCD on the plane of reference to obtain：
Therefore the phase place change as caused by object height is：
Wherein lm { } expressions take the imaginary part of plural number, and * represents conjugate operation；
B, the gradient for calculating phase place change, according to graded by object zoning, obtain abrupt change region template；
With △ φiThe gradient of (x, y) is distributed as foundation, the division in measurement object abrupt change region is realized, to △ φi(x's, y)
Gradient carries out threshold value, obtains the phase gradient figure of binaryzation：
Wherein grad [] represents gradient algorithm, and T is system calibrating value, such testee generally under measuring environment
It is a small amount of that the average value of greatest gradient subtracts one.
Then to △ φg i(x, y) is expanded, you can obtain abrupt change region Prototype drawing Maski(x,y)；
C, binaryzation phase diagram, which is carried out related calculation, obtains ohject displacement；
Intercept binaryzation phase gradient figure △ φg iThe characteristic area of (x, y), does with M frame binaryzation phase gradient figures respectively
Related operation, ohject displacement can be obtained by calculating the coordinate difference of maximal correlation point；
D, the phase shift that ohject displacement is converted to striped, obtain phase shift bar graph；According to abrupt change region template using minimum
The phase place change as caused by object height at square law iterative calculation abrupt change region；
The corresponding abrupt change region template of the M frame phase shift bar graphs photographed is multiplied, abrupt change region bar graph is obtained：
I′i(x, y)=Ii(x,y)·Maski(x,y) (7)
Adjacent N frames are divided into one group, and abrupt change region bar graph is grouped, bar graph cut out according to ohject displacement
Cut, realize that the pixel coordinate of object in each group different distortion bar graph is consistent, while ohject displacement is also converted into phase shift striped,
The method of obtained phase shift bar graph least square method iteration is calculated to the phase place change in object abrupt change region；
E, with abrupt change region phase formula (5) is modified, improves phase and obtain precision；
With the phase place change at the abrupt change region in the abrupt change region phase place change alternate form (5) calculated in d, phase is lifted
Position obtains precision；
Step 3) by the X of system calibrating acquisition object, Y-direction information, and phase information is converted into depth information Z.
The present invention has the advantages that compared with prior art.
First, the present invention proposes that the method being combined based on Fourier transformation and least square method iteration obtains testee
Tri-dimensional facial type, the overall phase information of testee is obtained by the method for Fourier transformation, then by phase information
Region segmentation is carried out, is divided into abrupt change region and non-abrupt change region, abrupt change region and phase is iterated to calculate using least square method, is used
Above-mentioned phase replaces the phase at abrupt change region in the overall phase information that Fourier transformation method is obtained.Fourier transformation ensures
Measuring speed, least square method iteration at abrupt change region to being modified, it is ensured that the measurement accuracy in abrupt change region.
Second, for the division of body surface gently with abrupt change region, propose by calculating phase gradient, reasonable threshold value is swollen
Abrupt change region is obtained after swollen.
3rd, for the feature extraction of deforming stripe, propose the side based on phase gradient threshold value searching object abrupt change border
Method, completes pixel matching related operation.
Brief description of the drawings
Fig. 1 is on-line checking schematic diagram.
Fig. 2 is that phase is obtained and phase correction procedure block diagram.
Fig. 3 is testee tri-dimensional facial type distribution map.
Fig. 4 is the wherein two frame deforming stripe figures that CCD is photographed.
Phase place change caused by the corresponding object height that Fig. 5 obtains for calculating.
Fig. 6 is the phase gradient figure of binaryzation.
Fig. 7 is three-dimensional reconstruction structure chart, wherein (a) is FTP three-dimensional reconstruction structures, (b) is three-dimensional reconstruction structure of the present invention.
Fig. 8 is correspondence root-mean-square error distribution.
Embodiment：
As shown in figure 1, the online tri-dimensional facial type detecting system principle based on fringe projection technology of profiling is that testee is with biography
Band uniform motion in X direction is sent, computer control Digital light projector projects sinusoidal grating picture in testee surface, projecting apparatus
Optical axis PO and CCD the O points that meet on the plane of reference of optical axis CO, the height of object can cause striped to deform upon, i.e., phase is sent out
Changing, calculates the phase place change of striped, you can obtain the elevation information Z of object.
Streamline product tri-dimensional facial type detection method of the invention based on phase gradient threshold value, detection process is according to following step
It is rapid to carry out：
Step 1) projector sinusoidal grating picture is in testee, and CCD gathers deforming stripe figure not in the same time；
When on conveyer belt without testee, the bar graph that CCD is not photographed in the same time does not change, its light distribution
It is represented by：I0(x, y)=R (x, y) [A (x, y)+B (x, y) cos φ0(x,y)] (1)
R (x, y) is body surface reflectivity in formula, and A (x, y) is background light intensity, and B (x, y) is fringe contrast；φ0(x,
Y) it is distributed for fringe phase；
When measurement object is moved with conveyer belt, CCD does not collect deforming stripe figure in the same time, and its light distribution can be represented
For：
Ii(x, y)=R (x, y) [A (x, y)+B (x, y) cos φi(x, y)] i=1,2 ... M (2)
φ in formulai(x, y) is the phase distribution of body surface deforming stripe, and object of which movement makes it as in every frame deforming stripe
Position in figure is different, and the distribution of the phase-modulation of generation is also different, is distinguished with subscript i；M represents to shoot frame number.
Step 2) phase obtain and phase only pupil filter：Whole process as shown in Fig. 2
A, calculated per phase place change φ caused by object height in frame bar line with the method for Fourier transformationi(x,y)：
Fourier transformation is made to formula (2) ,+1 grade of fundamental component is filtered out, remaking inverse Fourier transform can obtain：
Same computing is done to the light distribution (1) obtained of CCD on the plane of reference to obtain：
Therefore the phase place change as caused by object height is：
Wherein lm { } expressions take the imaginary part of plural number, and * represents conjugate operation；
Above-mentioned formula (5) is exactly to calculate the overall phase information of obtained testee by Fourier transformation, but is due to
Fourier transformation is related to frequency domain filtering when calculating phase, limits the precision of phase acquisition, and error is concentrated mainly on object
Abrupt change region, therefore abrupt change region phase is modified can effectively improve the overall phase information of object.
The amendment of abrupt change region phase is premised on the division in abrupt change region, because fringe phase caused by object changes △
φi(x, y) has linear approximate relationship with object height.Therefore the present invention is with △ φiThe gradient of (x, y) is distributed as foundation, realizes and surveys
Measure the division in object abrupt change region.Several step emphasis introduce the division in abrupt change region and obtaining for abrupt change region phase below
Take.
B, the gradient for calculating phase place change, according to graded by object zoning, obtain abrupt change region template；
With △ φiThe gradient of (x, y) is distributed as foundation, the division in measurement object abrupt change region is realized, to △ φi(x's, y)
Gradient carries out threshold value, obtains the phase gradient figure of binaryzation：
Wherein grad [] represents gradient algorithm, and T is system calibrating value, such testee generally under measuring environment
The average value of greatest gradient subtracts one in a small amount,
Then to △ φg i(x, y) is expanded, you can obtain abrupt change region Prototype drawing Maski(x,y)；
C, maximal correlation computing is done to binaryzation phase diagram obtain ohject displacement；
Intercept binaryzation phase gradient figure △ φg iThe characteristic area of (x, y), does with M frame binaryzation phase gradient figures respectively
Related operation, ohject displacement can be obtained by calculating the coordinate difference of maximal correlation point；
D, the phase shift that ohject displacement is converted to striped, obtain phase shift bar graph；According to abrupt change region template using minimum
The phase place change as caused by object height at square law iterative calculation abrupt change region；
The corresponding abrupt change region template of the M frame phase shift bar graphs photographed is multiplied, abrupt change region bar graph is obtained：
I′i(x, y)=Ii(x,y)·Maski(x,y) (7)
Adjacent N frames are divided into one group, and abrupt change region bar graph is grouped, bar graph cut out according to ohject displacement
Cut, realize that the pixel coordinate of object in each group different distortion bar graph is consistent, while ohject displacement is also converted into phase shift striped,
The method of obtained phase shift bar graph least square method iteration is calculated to the phase place change in object abrupt change region.
E, with abrupt change region phase formula (5) is modified, improves phase and obtain precision；
With the phase place change at the abrupt change region in the abrupt change region phase place change alternate form (5) calculated in d, phase is lifted
Position obtains precision.
Step 3) by the X of system calibrating acquisition object, Y-direction information, and phase information is converted into depth information Z.
The present invention is used for related operation using the phase of object when obtaining phase shift striped as feature.The feature of image
Extract mostly using the texture or depth information of object in scene as feature, the phase information that fringe projection technology of profiling is obtained with
Highly there is linear approximate relationship, can be with representative image object features.When using Structured Illumination in measurement process, not in the same time
Testee is without obvious textural characteristics in the bar graph photographed, and prior art, which is used, to be placed with mark without fringe area, extracts mark
Remember that texture information, as the method for feature, this method increase the complexity of measurement process；The method for calculating modulation of fringes can
To extract the edge contour of the testee covered by striped as feature, but object edge shade can bring matching error.
The present invention does region segmentation based on phase information in addition, and the overall phase of testee is obtained using Fourier transformation
Information, then using least square method iterated revision object abrupt change region phase value, the phase error that reduction frequency domain filtering is caused,
Compared with Fourier transformation method, measurement accuracy is higher, compared with least square method iteration, and speed is faster.The present invention is fully examined
Consider the balance of measuring speed and measurement accuracy, be more applicable for online tri-dimensional facial type detection.
Illustrate effectiveness of the invention below by Computer Simulation example, be illustrated in figure 3 the three-dimensional of testee
Face type profile diagram, Fig. 4 is the wherein two frame deforming stripe figure I that CCD is photographediThe horizontal displacement of object is 40 under (x, y), striped
Individual pixel.Fig. 5 is that phase place change △ φ caused by obtained corresponding object height are calculated according to the method for the present inventioni(x,y).Figure
6 is calculate after its gradient and threshold value, correspondence binaryzation phase gradient figure.After being carried out related calculation to phase gradient figure, displacement is obtained
For 40 pixels, meet preset value, illustrate that abrupt change region threshold can effectively recognize object abrupt change border.Fig. 6 is expanded
Abrupt tranaition domain template is can obtain, phase is iterated to calculate with least square method to abrupt change region, for correcting FTP phase calculation knots
Really.After Phase-height mapping, as shown in fig. 7, wherein (a) is FTP three-dimensional reconstruction structures, (b) is three-dimensional reconstruction of the present invention
Structure.(a), (b) are correspondence root-mean-square error distribution in Fig. 8, and corresponding RMS is respectively 0.9004mm, 0.2662mm.From Fig. 7
It is higher relative to fourier transform method precision with the method that the present invention is can be seen that in Fig. 8.
The speed of region segmentation phase calculation method is put forward to the present invention again to evaluate, the identical phase shift striped of use,
Under conditions of same computer configuration, the phase calculation time of the invention is 5.26 seconds, if global changed using least square method
In generation, calculates phase and needs 18.28 seconds, illustrates that the FTP based on region segmentation is combined calculating phase with least square method and can improve survey
Measure speed.
Embodiments of the invention are explained in detail above, but the present invention is not limited to above-described embodiment, in ability
In the knowledge that domain those of ordinary skill possesses, various changes can also be made on the premise of present inventive concept is not departed from
Change.
Claims (1)
1. the streamline product tri-dimensional facial type detection method based on phase gradient threshold value, it is characterised in that detection process according to
Lower step is carried out：
Step 1) projector sinusoidal grating picture is in testee, and CCD gathers deforming stripe figure not in the same time；
When on conveyer belt without testee, the bar graph that CCD is not photographed in the same time does not change, and its light distribution can table
It is shown as：I0(x, y)=R (x, y) [A (x, y)+B (x, y) cos φ0(x,y)] (1)
R (x, y) is body surface reflectivity in formula, and A (x, y) is background light intensity, and B (x, y) is fringe contrast, φ0(x, y) is
Fringe phase is distributed；
When testee is moved with conveyer belt, the deforming stripe figure that CCD is not collected in the same time, its light distribution can be represented
For：
Ii(x, y)=R (x, y) [A (x, y)+B (x, y) cos φi(x, y)] i=1,2 ... M (2)
φ in formulai(x, y) is the phase distribution of body surface deforming stripe, and object of which movement makes it as in every frame deforming stripe figure
Position it is different, the distribution of the phase-modulation of generation is also different, is distinguished with subscript i, and M represents to shoot frame number；
Step 2) phase obtain and phase only pupil filter：
A, calculated per phase place change φ caused by object height in frame bar line with the method for Fourier transformationi(x,y)：
Fourier transformation is made to formula (2) ,+1 grade of fundamental component is filtered out, remaking inverse Fourier transform can obtain：
<mrow>
<msub>
<mi>g</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mrow>
<mi>R</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>&CenterDot;</mo>
<mi>B</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
</mrow>
<mn>2</mn>
</mfrac>
<mi>exp</mi>
<mo>&lsqb;</mo>
<mi>j</mi>
<mo>&CenterDot;</mo>
<msub>
<mi>&phi;</mi>
<mi>i</mi>
</msub>
<mo>(</mo>
<mrow>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
</mrow>
<mo>)</mo>
<mo>&rsqb;</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>3</mn>
<mo>)</mo>
</mrow>
</mrow>
Same computing is done to the light distribution (1) obtained of CCD on the plane of reference to obtain：
<mrow>
<msub>
<mi>g</mi>
<mn>0</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfrac>
<mrow>
<mi>R</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>&CenterDot;</mo>
<mi>B</mi>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
</mrow>
<mn>2</mn>
</mfrac>
<mi>exp</mi>
<mo>&lsqb;</mo>
<mi>j</mi>
<mo>&CenterDot;</mo>
<msub>
<mi>&phi;</mi>
<mn>0</mn>
</msub>
<mo>(</mo>
<mrow>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
</mrow>
<mo>)</mo>
<mo>&rsqb;</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>4</mn>
<mo>)</mo>
</mrow>
</mrow>
Therefore the phase place change as caused by object height is：
<mrow>
<msub>
<mi>&Delta;&phi;</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<msub>
<mi>&phi;</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>-</mo>
<msub>
<mi>&phi;</mi>
<mn>0</mn>
</msub>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mi>l</mi>
<mi>m</mi>
<mo>{</mo>
<mi>l</mi>
<mi>n</mi>
<mo>&lsqb;</mo>
<mrow>
<msub>
<mi>g</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mrow>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
</mrow>
<mo>)</mo>
</mrow>
<msubsup>
<mi>g</mi>
<mn>0</mn>
<mo>*</mo>
</msubsup>
<mrow>
<mo>(</mo>
<mrow>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
</mrow>
<mo>)</mo>
</mrow>
</mrow>
<mo>&rsqb;</mo>
<mo>}</mo>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>5</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein lm { } expressions take the imaginary part of plural number, and * represents conjugate operation；
B, the gradient for calculating phase place change, according to graded by object zoning, obtain abrupt change region template；
With Δ φiThe gradient of (x, y) is distributed as foundation, the division in measurement object abrupt change region is realized, to Δ φiThe gradient of (x, y)
Threshold value is carried out, the phase gradient figure of binaryzation is obtained：
<mrow>
<msub>
<msup>
<mi>&Delta;&phi;</mi>
<mi>g</mi>
</msup>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>=</mo>
<mfenced open = "{" close = "">
<mtable>
<mtr>
<mtd>
<mrow>
<mo>=</mo>
<mn>1</mn>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>g</mi>
<mi>r</mi>
<mi>a</mi>
<mi>d</mi>
<mo>&lsqb;</mo>
<msub>
<mi>&Delta;&phi;</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo>&GreaterEqual;</mo>
<mi>T</mi>
</mrow>
</mtd>
</mtr>
<mtr>
<mtd>
<mrow>
<mo>=</mo>
<mn>0</mn>
</mrow>
</mtd>
<mtd>
<mrow>
<mi>g</mi>
<mi>r</mi>
<mi>a</mi>
<mi>d</mi>
<mo>&lsqb;</mo>
<msub>
<mi>&Delta;&phi;</mi>
<mi>i</mi>
</msub>
<mrow>
<mo>(</mo>
<mi>x</mi>
<mo>,</mo>
<mi>y</mi>
<mo>)</mo>
</mrow>
<mo>&rsqb;</mo>
<mo><</mo>
<mi>T</mi>
</mrow>
</mtd>
</mtr>
</mtable>
</mfenced>
<mo>-</mo>
<mo>-</mo>
<mo>-</mo>
<mrow>
<mo>(</mo>
<mn>6</mn>
<mo>)</mo>
</mrow>
</mrow>
Wherein grad [] represents gradient algorithm, and T is to be obtained according to system calibrating,
Then to Δ φg i(x, y) is expanded, you can obtain abrupt change region Prototype drawing Maski(x,y)；
C, binaryzation phase diagram, which is carried out related calculation, obtains ohject displacement；
Intercept binaryzation phase gradient figure Δ φg iThe characteristic area of (x, y), does related to M frame binaryzation phase gradient figures respectively
Computing, ohject displacement can be obtained by calculating the coordinate difference of maximal correlation point；
D, the phase shift that ohject displacement is converted to striped, obtain phase shift bar graph；Least square is used according to abrupt change region template
The phase place change as caused by object height at method iterative calculation abrupt change region；
The corresponding abrupt change region template of the M frame phase shift bar graphs photographed is multiplied, abrupt change region bar graph is obtained：
I′i(x, y)=Ii(x,y)·Maski(x,y) (7)
Adjacent N frames are divided into one group, and abrupt change region bar graph is grouped, bar graph cut according to ohject displacement, real
The pixel coordinate of object is consistent in existing each group different distortion bar graph, while ohject displacement is also converted into phase shift striped, will
The method of the phase shift bar graph least square method iteration arrived calculates the phase place change in object abrupt change region；
E, with abrupt change region phase formula (5) is modified, improves phase and obtain precision；
With the phase place change at the abrupt change region in the abrupt change region phase place change alternate form (5) calculated in d, lifting phase is obtained
Take precision；
Step 3) by the X of system calibrating acquisition object, Y-direction information, and phase information is converted into depth information Z.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510420768.9A CN105066904B (en) | 2015-07-16 | 2015-07-16 | Streamline product tri-dimensional facial type detection method based on phase gradient threshold value |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510420768.9A CN105066904B (en) | 2015-07-16 | 2015-07-16 | Streamline product tri-dimensional facial type detection method based on phase gradient threshold value |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105066904A CN105066904A (en) | 2015-11-18 |
| CN105066904B true CN105066904B (en) | 2017-08-29 |
Family
ID=54496332
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510420768.9A Active CN105066904B (en) | 2015-07-16 | 2015-07-16 | Streamline product tri-dimensional facial type detection method based on phase gradient threshold value |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105066904B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106524917B (en) * | 2016-12-09 | 2019-01-11 | 北京科技大学 | Object volume measurement method on a kind of conveyer belt |
| CN106705897B (en) * | 2016-12-23 | 2021-06-08 | 电子科技大学 | Method for detecting defects of arc-shaped glass panel for curved-surface electronic display screen |
| CN107024488B (en) * | 2017-02-27 | 2019-08-13 | 杭州电子科技大学 | A kind of glass defect detection method |
| CN109141290A (en) * | 2018-08-28 | 2019-01-04 | 西安工业大学 | A kind of detection method of big bias freeform optics surface face shape |
| CN111380485B (en) * | 2020-02-21 | 2021-06-04 | 天津大学 | Camouflage detection method based on composite orthogonal phase shift stripes |
| CN113074634B (en) * | 2021-03-25 | 2022-06-21 | 苏州天准科技股份有限公司 | Rapid phase matching method, storage medium and three-dimensional measurement system |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5669284B2 (en) * | 2012-03-12 | 2015-02-12 | 株式会社積水インテグレーテッドリサーチ | 3D shape measuring device |
| CN103925889B (en) * | 2014-03-31 | 2016-04-20 | 西北工业大学 | A kind of high light body surface phase place quick recovery method based on least square method |
| CN104197860B (en) * | 2014-07-04 | 2017-02-15 | 丽水学院 | Three-dimensional surface topography measuring method for large-size workpiece |
| CN104315996B (en) * | 2014-10-20 | 2018-04-13 | 四川大学 | The method that Fourier transform profilometry is realized with binary coding strategy |
| CN104457614B (en) * | 2014-11-11 | 2017-09-01 | 南昌航空大学 | Streak reflex method for three-dimensional measurement based on binary system striped defocus |
| CN104457615B (en) * | 2014-11-14 | 2017-04-05 | 深圳大学 | Three-dimension digital imaging method based on generalized S-transform |
| CN104655051B (en) * | 2014-12-29 | 2019-11-05 | 四川大学 | A kind of high-speed structures light 3 d shape vertical measurement method |
| CN104567730B (en) * | 2015-01-15 | 2017-11-07 | 四川大学 | A kind of method that space-time binary coding produces sinusoidal light field |
| CN104729430B (en) * | 2015-03-26 | 2017-09-22 | 中国科学院电工研究所 | A kind of tower type solar energy thermal power generation heliostat surface testing method |
-
2015
- 2015-07-16 CN CN201510420768.9A patent/CN105066904B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN105066904A (en) | 2015-11-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105066904B (en) | Streamline product tri-dimensional facial type detection method based on phase gradient threshold value | |
| CN107607060B (en) | A kind of phase error compensation method applied in the measurement of grating tripleplane | |
| CN105783775B (en) | A kind of minute surface and class minute surface object surface appearance measuring device and method | |
| CN106931910B (en) | A kind of efficient acquiring three-dimensional images method based on multi-modal composite coding and epipolar-line constraint | |
| Su et al. | Dynamic 3-D shape measurement method based on FTP | |
| CN106461380B (en) | A kind of projector lens distortion correction method and its system based on adaptive striped | |
| CN103383249B (en) | Gray scale striped projected light strong nonlinearity bearing calibration and method for correcting phase based on the method | |
| CN109141291A (en) | A kind of fast phase unwrapping algorithm | |
| CN109059806B (en) | A kind of mirror article three dimension profile measurement device and method based on infrared stripes | |
| CN108168464A (en) | For the phase error correction approach of fringe projection three-dimension measuring system defocus phenomenon | |
| CN105066906B (en) | A kind of quick high dynamic range method for three-dimensional measurement | |
| CN109506592A (en) | Object dimensional surface shape measurement method and device based on striped light stream | |
| CN106091978B (en) | The joining method of interference fringe image in inclined in type measurements by laser interferometry | |
| Zhang et al. | Full-field phase error analysis and compensation for nonsinusoidal waveforms in phase shifting profilometry with projector defocusing | |
| CN105491315B (en) | A kind of projecting apparatus gamma correction method | |
| Yu et al. | High sensitivity fringe projection profilometry combining optimal fringe frequency and optimal fringe direction | |
| CN109631798A (en) | A kind of 3 d shape vertical measurement method based on π phase shifting method | |
| CN110223384A (en) | A kind of white light interference three-dimensional appearance method for reconstructing, device, system and storage medium | |
| CN108362226A (en) | Improve double four-stepped switching policies of image overexposure region phase measurement accuracy | |
| Yeh et al. | Applying adaptive LS-PIV with dynamically adjusting detection region approach on the surface velocity measurement of river flow | |
| Li et al. | An improved 2+ 1 phase-shifting algorithm | |
| Ma et al. | Real-time 3-D shape measurement based on radial spatial carrier phase shifting from circular fringe pattern | |
| Li et al. | Fast phase-based stereo matching method for 3D shape measurement | |
| Ratnam et al. | Circular fringe projection technique for out-of-plane deformation measurements | |
| CN109506590A (en) | A kind of boundary jump phase error method for rapidly positioning |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20211019 Address after: 030500 Jiaocheng village, Jiaocheng County, Lvliang, Shanxi Patentee after: SHANXI JIAOCHENG HONGXING CHEMICAL Co.,Ltd. Address before: 030024 Shanxi province Taiyuan city Berlin District Wan wa flow Road No. 66 Patentee before: TAIYUAN University OF SCIENCE AND TECHNOLOGY |
|
| TR01 | Transfer of patent right |