CN109190310A - Interference fringe wave-front reconstruction method based on MATLAB platform - Google Patents

Interference fringe wave-front reconstruction method based on MATLAB platform Download PDF

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CN109190310A
CN109190310A CN201811250671.8A CN201811250671A CN109190310A CN 109190310 A CN109190310 A CN 109190310A CN 201811250671 A CN201811250671 A CN 201811250671A CN 109190310 A CN109190310 A CN 109190310A
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interference fringe
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CN109190310B (en
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梅启升
王敏
梁秀玲
周群
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Fujian Normal University
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Abstract

The interference fringe wave-front reconstruction method based on MATLAB platform that the present invention relates to a kind of pre-processes picture when reading a noise-containing interference fringe picture first, handles to obtain the preferable interference image of quality by image enhancement processing and image filtering；Binary conversion treatment then is carried out to interference image, except striped is deleted with external information, holes filling is carried out to image according to striped binary map characteristic information, interference fringe is then carried out according to complete stripe information and carries out skeletal extraction；According to interference fringe framework information, processing that the problems such as burr and breakpoint in image is deleted and connected respectively；Level calibration is carried out to interference fringe according to complete interference fringe framework characteristic information；The reconstruction of face type finally is carried out according to the interference fringe skeleton of re-calibration to handle out, and is shown the treatment effect picture of wherein each step by MATLAB.

Description

Interference fringe wave-front reconstruction method based on MATLAB platform
Technical field
The present invention relates to interference fringe identifications to rebuild field with face type, and in particular to a kind of dry based on MATLAB platform Relate to striped wave-front reconstruction method.
Background technique
Current optical interference fringe detection algorithm faces the algorithm process effect of the interference fringe containing noise, different shape It is extremely bad, and method is not mature enough, can not carry out accurate wave-front reconstruction.But by feat of the category of itself interference fringe Property, spatial feature play huge breakthrough in bar detection technology.However the complex shape degree of interference fringe is faced, it needs It is proposed that a kind of relatively broad algorithm of applicability differentiates the interference fringe of different shape feature.It is currently based on interference fringe inspection It is the phase information with striped 4 that survey most commonly used algorithm, which be the phase shift method based on four-stepped switching policy, based on interference fringe, Phase Unwrapping Algorithm is carried out in width image, this phase shift method based on 4 width images has higher requirement for instrument, and to dry The quality requirement for relating to striped picture is high, and current algorithm is just bad to noise-containing interference image treatment effect and can not be to corrugated Carry out reconstruction operation.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of interference fringe wave-front reconstruction sides based on MATLAB platform Method solves the interference of a variety of noises, the challenges such as striped form difference.
To achieve the above object, the present invention adopts the following technical scheme:
A kind of interference fringe wave-front reconstruction method based on MATLAB platform, which comprises the following steps:
Step S1: interference fringe image to be reconstructed is read in into MATLAB software；
Step S2: pre-processing interference fringe image, obtains pretreated interference fringe image；
Step S3: differential filtering processing and binary conversion treatment are carried out to pretreated interference fringe image, obtain binaryzation Interference fringe image；
Step S4: empty filling processing is carried out to obtained binaryzation interference fringe image, obtains filled interference item Print image；
Step S5: it is combined by ZhangShi skeletal extraction algorithm and Rosen skeletal extraction algorithm, by the interference item of filling Print image is converted to interference fringe skeleton image；
Step S6: based on interference fringe skeleton image the characteristics of carries out deburring processing respectively and breakpoint joint is handled, and obtains To complete interference fringe skeleton image；
Step S7: judge the striped type of complete interference fringe skeleton image, and grade is re-started according to striped type It is secondary to demarcate sequence side by side；
Step S8: complete interference fringe skeleton image after being demarcated according to level carries out face type using zernike polynomial The reconstruction to interference fringe image is completed in fitting.
Further, the step S2 specifically:
Step S21: pre-processing interference image to be reconstructed using the scheme of single armed swirler blade angle, first establishes before processing 8 convolution kernels, the size and format of convolution kernel K are as follows:
8 directions are decomposed by 180 ° according to clockwise direction and carry out equal part, and each direction is separated by 22.5 °, wherein 45 ° The convolution kernel K in direction2Are as follows:
According to each pixel investigation of interference fringe image, compares variance in each direction, select variance most Small direction, as the tangential direction pointed out；
Step S22: mean filter processing is carried out to the point according to the tangential direction at the point；
Step S23: swirler blade angle carries out figure to interference fringe image using adaptive histogram equalization after processing terminate Image intensifying handles to obtain pretreated interference fringe image.
Further, the step S3 specifically:
Step S31: according to pretreated interference fringe image is obtained, according to interference fringe thickness difference, using different window The filter of mouth size is set as follows using window size g:
Wherein g is window size, and S indicates the similar area of interference fringe at certain point in image；
Differential filtering processing is as follows:
Wherein f is original image, and w is filter template, and Δ is difference processing.
Step S32: threshold binarization treatment is carried out according to the image obtained after difference processing, obtains binaryzation interference fringe Image.
Further, the step S4 carries out empty filling using the imfill function of MATLAB software.
Further, the step S7 specifically:
Step S71: judge the striped type of interference fringe skeleton image, including closo and non-closed type；
Step S72: it is re-scaled according to striped type；
Step S73: it is combined according to non-closed striped with the sequence level of closure striped.
Further, the step S72 specifically:
If the striped type of the interference fringe skeleton image is closo, steps are as follows for re-calibration:
A: four, the upper and lower, left and right boundary point for being closed striped is marked；
B: scanning per each and every one boundary point toward eight directions, excludes the interference fringe skeleton that scanning arrives itself；
C: according to from inside to outside, closure striped is ranked up；
If the striped type of the interference fringe skeleton image is non-closed type, steps are as follows for re-calibration:
D: judging the form of each interference fringe skeleton, including " c " type, " s " type, " l " type bending state,
E: different shape is recorded to preservation respectively using MATLAB program；
F: after the striped skeleton for determining the first level, according to the striped matrix morphology of different shape, at the same to skeleton into Row again demarcate by level.
Further, told step f specifically:
F1: if striped to be calibrated is " c " type curve and " c " type curve identical with upper level time, the level of the curve Number determines that mode is constant by the mode of upper striped curve, if " c " the type curve secondary with upper level is on the contrary, mode change, is somebody's turn to do The grade number of curve is identical by the level of upper striped curve；
F2: if the curve that striped to be calibrated is the upper level time of " c " type curve is " l " type curve, it is somebody's turn to do " c " type curve Grade number determines that mode is constant by the mode of upper striped curve；
F3: if the curve that striped to be calibrated is the upper level time of " l " type curve is " c " type curve, it is somebody's turn to do " c " type curve Grade number is determined that mode changes by the mode of upper striped curve；
F4: if the curve that striped to be calibrated is the upper level time of " l " type curve is " l " type curve, it is somebody's turn to do " l " type curve Grade number determines that mode is constant by the mode of upper striped curve；
The mode of f5: the first level is increment mode, and the grade number of the first level striped is 1；
F6: if striped to be calibrated be the non-closed striped bending direction judgment method of " s " type: by certain interference fringe skeleton into Row joins end to end, and according to the area that skeleton curve and line surround, takes the area of positive direction to be positive, the area of opposite direction is then It is negative, it accurately calculates to obtain the area of curve and line by MATLAB, which is judged by the numerical value of area, judge It finishes and then calculates level by " c " type curve decision level time scheme.
Further, the zernike polynomial equation under the rectangular coordinate system is as follows:
Wherein,For radial polynomial, Θm(θ) is angular multinomial.
Zernike polynomial is fitted as follows:
Compared with the prior art, the invention has the following beneficial effects:
The present invention is based on Digital Image Processing and interference fringe feature identification technique to carry out interference fringe detection, entire to be Most important part is differential threshold processing, level calibration processing and face type reconstruction processing in module of uniting, and differential threshold processing is not The noise information being merely capable of in removal interference fringe can also be for the rebasing mostly important basis of image binaryzation, at level calibration Interference fringe skeleton is carried out phase-detection by reason, interference fringe information most effective can be extracted, at wave-front reconstruction Reason can be handled again the surface face type shape of optical element
Detailed description of the invention
Fig. 1 is the method for the present invention flow chart；
Fig. 2 is pretreated image in one embodiment of the invention；
Fig. 3 is the image in one embodiment of the invention after binary conversion treatment；
Fig. 4 is interference fringe skeleton image in one embodiment of the invention；
Fig. 5 is complete interference fringe skeleton image in one embodiment of the invention；
Fig. 6 is one embodiment of the invention middle rank time calibration treated image；
Fig. 7 is the image after one embodiment of the invention mesoprosopy is rebuild；
Fig. 8 is that self-adapting window size is arranged in one embodiment of the invention
Fig. 9 is non-closed interference fringe image in one embodiment of the invention.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and embodiments.
Fig. 1 is please referred to, the present invention provides a kind of interference fringe wave-front reconstruction method based on MATLAB platform, including following Step
Step S1: reading in MATLAB software for interference fringe image,
Step S2: and the scheme based on single armed swirler blade angle pre-processes interference image, needs first to establish 8 before processing Convolution kernel, the size and format of convolution kernel K are as follows:
Single armed swirler blade angle processing scheme is decomposed into 8 directions for 180 ° according to clockwise direction and carries out equal part, each direction It is separated by 22.5 °, this part is with 45 ° of directions as an example by its convolution kernel column K2It is below:
According to each pixel investigation of interference fringe image, compares variance in each direction, select variance most Small direction, the tangential direction pointed out as certain.Mean filter processing is carried out to the point according to the tangential direction at the point.Rotation filter Processing terminate for wave later using adaptive histogram equalization (adapthisteq function) to interference fringe image progress image increasing It manages to obtain Fig. 2 in strength.Step S2 is the interference in order to reduce noise, promotes fringe contrast；
Step S3: it is different according to interference fringe thickness according to pretreated effect picture, using the filtering of different windows size Device, as schemed the point that the stain shown in (8), in figure is Current Scan, red point is the size of certain stripe, and the present invention, which uses, to be worked as The interference fringe area of preceding point is as filter window size.
It is k1 according to left width is scanned, right width is k2, and upper width is k3, lower width from the point toward left and right, upper and lower scanning Degree is k4, according to the area currently surrounded:
S=(k1+k2+1) × (k3+k4+1) (3)
Using the interference fringe size of certain point as the selection g benchmark such as following formula of window:
G is window size in above formula, and S indicates the similar area of interference fringe at certain point in image.The present invention is for thick, big Interference fringe using big window mean filter processing, tiny interference fringe using wicket carry out mean filter processing, reach Binary image can be accurately obtained to the striped to different shape.
The principle of differential filtering processing is as follows:
F is original image in above formula, and w is filter template, and Δ is difference processing.The principle of the processing of differential filtering with emphasis on In, carry out difference processing will be filtered twice, it is obtaining as a result, we are setting a fixed threshold value, at difference It manages obtained image progress threshold binarization treatment and obtains Fig. 3.
Step S4:, empty filling (imfill function) is carried out to picture according to interference fringe binary map and obtains result figure 4.
Step S5, according to complete interference fringe binary map, at ZhangShi thinning algorithm and Rosen thinning algorithm Reason obtains the skeleton drawing 5 of interference fringe.
Step S6 refines the flaws problems such as burr and the breakpoint in figure according to interference fringe and exists, after first deburring The processing for connecting breakpoint, finally obtains Fig. 6.
Step S7: it according to complete interference fringe skeleton drawing, carries out again level and demarcates.Patent interferes item according to the present invention Line is simply divided into two kinds: closo and non-closed type, non-closed type have comprising three kinds: " c " type, " s " type and " l " type, here " s " Type refers to that interference fringe skeleton is winding but a kind of inc situation, " c " type refer to that interference fringe skeleton is a kind of Simple class circular arc type, " l " type refer to linear type interference fringe.Closo interference fringe skeleton refers to that interference fringe is to close Close the shape of curve.
The present invention first carries out non-closed striped calibration step using the scheme for first handling non-closed striped post-processing closure striped Rapid as follows: according to MATLAB program, the first step first judges the form of each interference fringe skeleton, according to " c " type, " s " type, Different shape is recorded preservation using MATLAB program by the bending state of " l " type, second step respectively.Third step determines After the striped skeleton of one level, according to the striped matrix morphology of different shape, while level is carried out again to skeleton and is demarcated.
Closure striped scaling scheme: the first step is then carried out, four, the upper and lower, left and right boundary point label of striped will be closed Out.Second step, four boundary points exclude the interference fringe skeleton that scanning arrives itself toward eight (360 °) of direction scannings.Third Step is ranked up closure striped then according to from inside to outside.Finally according to the sequence level of non-closed striped and closure striped It combines.
There are two ways to non-closed striped striped skeleton curve level is demarcated mode: increment mode, decline mode.It is incremented by Mode, the striped to be measured referred to for upper level striped be increase by one level, decline mode again refer to striped to be measured for A upper striped is the level for reducing one.
Situation 1: if " c " type curve identical of certain " c " type curve and upper level time, the grade number of the curve is by upper The mode of one striped curve determines that mode is constant, if with " c " the type curve of upper level time on the contrary, mode changes, the curve Grade number is identical by the level of upper striped curve.
Situation 2: if the curve of the upper level time of certain " c " type curve is " l " type curve, it is somebody's turn to do the grade of " c " type curve Number determines that mode is constant by the mode of upper striped curve.
Situation 3: if the curve of the upper level time of certain " l " type curve is " c " type curve, it is somebody's turn to do the grade of " c " type curve Number is determined that mode changes by the mode of upper striped curve.
Situation 4: if the curve of the upper level time of certain " l " type curve is " l " type curve, it is somebody's turn to do the grade of " l " type curve Number determines that mode is constant by the mode of upper striped curve.
The mode of 5: the first level of situation is increment mode, and the grade number of the first level striped is 1.
The non-closed striped bending direction judgment method of " s " type: certain interference fringe skeleton is joined end to end, according to bone The area that frame curve and line surround, takes the area of positive direction to be positive, the area of opposite direction is then negative, and accurately counts by MATLAB Calculation obtains the area of curve and line, judges the direction of curve by the numerical value of area, judgement finishes, sentences by " c " type curve Time scheme of defining the level calculates level.
The radiation method of closure striped curve is after finishing based on non-closed striped whole calibration, to choose a certain closure strip Line, left and right to its, upper and lower four endpoints are scanned, and sweeping scheme is that scanning just stops sweeping to a certain striped skeleton curve It retouches.
Situation 1: it is not handled if the striped that first scans is non-closed striped, according to the mould of the non-closed striped Formula carry out level be incremented by, decrement operations.
Situation 2: if it is the same closure striped that each endpoint, which scans, and according to the mould of nearest non-closed striped Formula is demarcated.
Situation 3: if the closure striped that each endpoint scans is different from, all closures scanned are all same Level.
Situation 4: if the closure striped that certain endpoints scan is identical, the closure striped that certain endpoints scan not phase Together.It is then split as situation 2 and situation 3 is handled respectively.
The level calibration algorithm of MATLAB software programming interference fringe skeleton drawing is utilized according to all the cases above.
Step S8 demarcates complete skeleton drawing according to level, carries out the fitting of face type, circle domain pool Buddhist nun using zernike polynomial Gram polynomial equation is as follows:
In above formula,For radial polynomial, Θm(θ) is angular multinomial, with the zernfun letter in MATLAB Number, by the interference fringe skeleton drawing that finishes of step 6 middle rank time calibration bring into zernike polynomial be fitted it is as follows:
It is fitted obtained zernike coefficient and the optimal pool of least square method acquisition is carried out by Gram-Schmidt orthogonalization The polynomial coefficient of Buddhist nun gram.The fitting of interference fringe corrugated face type is carried out into linear spline interpolation algorithm is crossed, it is multinomial according to Ze Nike Formula fits final corrugated face type, achievees the purpose that wave-front reconstruction.

Claims (8)

1. a kind of interference fringe wave-front reconstruction method based on MATLAB platform, which comprises the following steps:
Step S1: interference fringe image to be reconstructed is read in into MATLAB software；
Step S2: pre-processing interference fringe image, obtains pretreated interference fringe image；
Step S3: carrying out differential filtering processing and binary conversion treatment to pretreated interference fringe image, obtains binaryzation interference Stripe pattern；
Step S4: empty filling processing is carried out to obtained binaryzation interference fringe image, obtains filled interference fringe picture Picture；
Step S5: it is combined by ZhangShi skeletal extraction algorithm and Rosen skeletal extraction algorithm, by the interference fringe picture of filling As being converted to interference fringe skeleton image；
Step S6: based on interference fringe skeleton image the characteristics of carries out deburring processing respectively and breakpoint joint is handled, and has obtained Whole interference fringe skeleton image；
Step S7: judge the striped type of complete interference fringe skeleton image, and a grade deutero-albumose is re-started according to striped type Determine and sorts；
Step S8: complete interference fringe skeleton image after being demarcated according to level carries out the fitting of face type using zernike polynomial Complete the reconstruction to interference fringe image.
2. the interference fringe wave-front reconstruction method according to claim 1 based on MATLAB platform, it is characterised in that: described Step S2 specifically:
Step S21: pre-processing interference image to be reconstructed using the scheme of single armed swirler blade angle, first establishes 8 before processing Convolution kernel, the size and format of convolution kernel K are as follows:
8 directions, which are decomposed into, by 180 ° according to clockwise direction carries out equal parts, each direction is separated by 22.5 °, wherein 45 ° of directions Convolution kernel K2Are as follows:
According to each pixel investigation of interference fringe image, compares variance in each direction, it is the smallest to select variance Direction, as the tangential direction pointed out；
Step S22: mean filter processing is carried out to the point according to the tangential direction at the point；
Step S23: processing terminate for swirler blade angle later using adaptive histogram equalization to interference fringe image progress image increasing It manages to obtain pretreated interference fringe image in strength.
3. the interference fringe wave-front reconstruction method according to claim 1 based on MATLAB platform, it is characterised in that: described Step S3 specifically:
Step S31: it is different according to interference fringe thickness according to obtaining pretreated interference fringe image, it is big using different windows Small filter is set as follows using window size g:
Wherein g is window size, and S indicates the similar area of interference fringe at certain point in image；
Differential filtering processing is as follows:
Wherein f is original image, and w is filter template, and Δ is difference processing.
Step S32: threshold binarization treatment is carried out according to the image obtained after difference processing, obtains binaryzation interference fringe picture Picture.
4. the interference fringe wave-front reconstruction method according to claim 1 based on MATLAB platform, it is characterised in that: described Step S4 carries out empty filling using the imfill function of MATLAB software.
5. the interference fringe wave-front reconstruction method according to claim 1 based on MATLAB platform, it is characterised in that: described Step S7 specifically:
Step S71: judge the striped type of interference fringe skeleton image, including closo and non-closed type；
Step S72: it is re-scaled according to striped type；
Step S73: it is combined according to non-closed striped with the sequence level of closure striped.
6. the interference fringe wave-front reconstruction method according to claim 5 based on MATLAB platform, it is characterised in that: described Step S72 specifically:
If the striped type of the interference fringe skeleton image is closo, steps are as follows for re-calibration:
A: four, the upper and lower, left and right boundary point for being closed striped is marked；
B: scanning per each and every one boundary point toward eight directions, excludes the interference fringe skeleton that scanning arrives itself；
C: according to from inside to outside, closure striped is ranked up；
If the striped type of the interference fringe skeleton image is non-closed type, steps are as follows for re-calibration:
D: judging the form of each interference fringe skeleton, including " c " type, " s " type, " l " type bending state,
E: different shape is recorded to preservation respectively using MATLAB program；
F: after the striped skeleton for determining the first level, weight is carried out according to the striped matrix morphology of different shape, while to skeleton New level calibration.
7. the interference fringe wave-front reconstruction method according to claim 6 based on MATLAB platform, it is characterised in that: told Step f specifically:
F1: if striped to be calibrated is " c " type curve and " c " type curve identical with upper level time, the grade number of the curve by The mode of upper striped curve determines that mode is constant, if " c " the type curve secondary with upper level is on the contrary, mode change, the curve Grade number it is identical by the level of upper striped curve；
F2: if the curve that striped to be calibrated is the upper level time of " c " type curve is " l " type curve, it is somebody's turn to do the level of " c " type curve Number determines that mode is constant by the mode of upper striped curve；
F3: if the curve that striped to be calibrated is the upper level time of " l " type curve is " c " type curve, it is somebody's turn to do the level of " c " type curve Number is determined that mode changes by the mode of upper striped curve；
F4: if the curve that striped to be calibrated is the upper level time of " l " type curve is " l " type curve, it is somebody's turn to do the level of " l " type curve Number determines that mode is constant by the mode of upper striped curve；
The mode of f5: the first level is increment mode, and the grade number of the first level striped is 1；
F6: if striped to be calibrated is the non-closed striped bending direction judgment method of " s " type: certain interference fringe skeleton being carried out first Tail is connected, and according to the area that skeleton curve and line surround, the area of positive direction is taken to be positive, and the area of opposite direction is then negative, and leads to It crosses MATLAB to accurately calculate to obtain the area of curve and line, which is judged by the numerical value of area, judgement finishes Then level is calculated by " c " type curve decision level time scheme.
8. the interference fringe wave-front reconstruction method according to claim 1 based on MATLAB platform, it is characterised in that: described Zernike polynomial equation under rectangular coordinate system is as follows:
Wherein,For radial polynomial, Θm(θ) is angular multinomial.
Zernike polynomial is fitted as follows:
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109660770A (en) * 2019-01-12 2019-04-19 田华 Intelligent scene monitors system and method
CN110232677A (en) * 2019-05-23 2019-09-13 天津大学 A kind of cell phone application for interference fringe analysis

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2001201326A (en) * 2000-01-18 2001-07-27 Fuji Photo Optical Co Ltd Interference fringe measuring and analyzing method
CN104320598A (en) * 2014-11-06 2015-01-28 中国科学院光电研究院 Aberration-free image reconstruction method based on CCD array pixel response function frequency domain calibration
CN106247980A (en) * 2016-08-22 2016-12-21 天津大学 The multi-wavelength phase shift interference measuring method processed based on white light interference color fringe

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2001201326A (en) * 2000-01-18 2001-07-27 Fuji Photo Optical Co Ltd Interference fringe measuring and analyzing method
CN104320598A (en) * 2014-11-06 2015-01-28 中国科学院光电研究院 Aberration-free image reconstruction method based on CCD array pixel response function frequency domain calibration
CN106247980A (en) * 2016-08-22 2016-12-21 天津大学 The multi-wavelength phase shift interference measuring method processed based on white light interference color fringe

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
M. T. LI 等: "A method of removing interference fringes on spherical subsurface imaging with continuous wave penetrating radar", 《 2016 16TH INTERNATIONAL CONFERENCE ON GROUND PENETRATING RADAR (GPR)》 *
兰明强: "基于波面拟合法面形偏差检测技术研究", 《中国优秀硕士学位论文全文数据库 (工程科技Ⅰ辑)》 *
周群: "基于三维重建的面形检测算法研究", 《中国优秀硕士学位论文全文数据库 (工程科技Ⅱ辑)》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109660770A (en) * 2019-01-12 2019-04-19 田华 Intelligent scene monitors system and method
CN110232677A (en) * 2019-05-23 2019-09-13 天津大学 A kind of cell phone application for interference fringe analysis
CN110232677B (en) * 2019-05-23 2023-04-07 天津大学 Mobile phone APP for interference fringe analysis

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