CN110375672B - Real-time phase measurement profilometry based on simulated annealing algorithm - Google Patents
Real-time phase measurement profilometry based on simulated annealing algorithm Download PDFInfo
- Publication number
- CN110375672B CN110375672B CN201910472262.0A CN201910472262A CN110375672B CN 110375672 B CN110375672 B CN 110375672B CN 201910472262 A CN201910472262 A CN 201910472262A CN 110375672 B CN110375672 B CN 110375672B
- Authority
- CN
- China
- Prior art keywords
- area
- correlation
- matching
- region
- measured object
- 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.)
- Expired - Fee Related
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/2441—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures using interferometry
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
- G01B11/2513—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object with several lines being projected in more than one direction, e.g. grids, patterns
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/004—Artificial life, i.e. computing arrangements simulating life
- G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/752—Contour matching
Abstract
The invention discloses a real-time phase measurement profilometry based on a simulated annealing algorithm, which comprises the steps of projecting a fringe pattern onto a measured object moving on a reference plane, collecting a multi-frame deformation fringe pattern, carrying out pixel matching through the simulated annealing algorithm to obtain an approximate region fringe pattern, delineating a moving region by taking the central point of the approximate region fringe pattern as a reference, carrying out pixel matching in the moving region to obtain an optimal region fringe pattern, calculating phase information and phase change of height modulation of the measured object according to the optimal region fringe pattern, and determining the surface shape height distribution of the three-dimensional object of the measured object according to the corresponding relation of the phase and the height. According to the invention, a relatively accurate global optimal solution is obtained by utilizing the characteristics of small calculated amount and relatively accuracy of the simulated annealing algorithm, and the field of the solution is traversed, so that the process of traversing the whole matching region in the traditional method is omitted, the calculated amount required by pixel matching is reduced, and the efficiency of real-time phase measurement profilometry is improved on the premise of ensuring the accuracy.
Description
Technical Field
The invention belongs to the technical field of three-dimensional measurement of objects, and particularly relates to a real-time phase measurement profilometry based on a simulated annealing algorithm.
Background
With the development of manufacturing, medical imaging, virtual reality, and computer graphics, phase measurement profilometry, which obtains accurate and high-resolution three-dimensional profiles using a plurality of fringe pattern algorithms with phase shifts, is receiving increasing attention. The real-time Phase Measurement Profilometry (PMP) has the characteristics of large data acquisition amount, high precision, non-contact and the like, and the three-dimensional surface type of a measured object can be recovered by projecting and acquiring multi-frame fringe patterns, so that the PMP is a method widely researched and used in an optical three-dimensional measurement means.
Due to the development of industry and the increase of application occasions, the requirement for measuring the three-dimensional shape is increasingly vigorous, and a measured object also extends from a static object to a dynamic object, and can be divided into online three-dimensional measurement and real-time three-dimensional measurement according to the motion characteristics of the dynamic object. The online three-dimensional measurement mainly aims at objects moving on a straight line on a production line, the requirement on the external condition of the measurement is high, the real-time three-dimensional measurement can be taken as the measurement of different objects at all times, and the real-time measurement does not require the objects to move on the straight line, so that the application range is wider, and the development direction of the three-dimensional measurement of dynamic objects is provided. At present, after images are collected by adopting a projector for projection and a CCD (charge coupled device) in real-time measurement, the change of a measured object in a collected multi-frame deformed fringe pattern can be smaller than one pixel point only by traversing the collected whole images when the pixels are matched, so that the surface type of the measured object is restored in real time.
Disclosure of Invention
The invention aims to solve the defects of the background technology and provide a real-time phase measurement profilometry based on a simulated annealing algorithm, which has a simple method and high efficiency.
The technical scheme adopted by the invention is as follows: a real-time phase measurement profilometry based on a simulated annealing algorithm projects a fringe pattern onto a measured object moving on a reference plane, collects multiple frames of deformed fringe patterns, carries out pixel matching through the simulated annealing algorithm to obtain approximate region fringe patterns corresponding to pixels of a certain point on the measured object in each frame of deformed fringe patterns one by one, defines a region as a moving region by taking the center point of the approximate region fringe patterns as a reference, carries out pixel matching in the moving region to obtain optimal region fringe patterns corresponding to pixels of a certain point on the measured object in each frame of deformed fringe patterns one by one, calculates phase information modulated by the height of the measured object and phase change caused by the height of the measured object according to the optimal region fringe patterns, and determines the surface shape height distribution of the three-dimensional object according to the corresponding relation of the phase and the height.
Further, the process of performing pixel matching by the simulated annealing algorithm is as follows: selecting a matching template, randomly selecting a matching area capable of carrying out correlation calculation with the matching template in each frame of image, comparing the correlation of the corresponding matching areas, selecting an area stripe image by keeping the matching area corresponding to larger correlation and receiving the matching area corresponding to smaller correlation with a certain probability as a reference, and repeating the process of selecting the area stripe image until a termination condition is met, thereby obtaining an approximate area stripe image corresponding to a pixel at a certain point on a measured object in the deformed stripe image.
Further, the process of pixel matching by simulated annealing algorithm comprises the following steps
Step 1: setting initial parameters and termination parameters, and selecting a matching template by taking the acquired first frame of deformed fringe pattern as a reference;
step 2: randomly selecting an area capable of carrying out correlation calculation with the matching template from one frame of deformed fringe image as a current area, and calculating a first correlation between the current area and the matching template;
and step 3: randomly selecting another area capable of carrying out correlation calculation with the matching template from the same frame of deformed fringe image as a next area, calculating a second correlation between the next area and the matching template, and comparing the first correlation with the second correlation;
and 4, step 4: when the second degree of correlation is greater than or equal to the first degree of correlation, taking the next area as a new current area, and taking the degree of correlation corresponding to the new current area as a new first degree of correlation, and continuing to step 6;
and 5: when the second correlation degree is smaller than the first correlation degree, calculating the probability of acceptance of the next region, if the probability is larger than a set value, taking the next region as a new current region, and simultaneously taking the correlation degree corresponding to the new current region as a new first correlation degree, and continuing to step 6; if the probability is not greater than the set value, taking the current area as a new current area, and simultaneously taking the correlation degree corresponding to the new current area as a new first correlation degree, and continuing to the step 6;
step 6: calculating the current parameter, and if the current parameter is not less than the termination parameter, returning to the step 3; if the current parameter is less than the termination parameter, taking the new current area as an approximate area stripe image corresponding to the pixel of a certain point on the measured object in the deformed stripe image, and continuing to step 7;
and 7: and (5) repeating the steps 2-6 until obtaining the similar area fringe patterns corresponding to the pixels of a certain point on the measured object in all the deformed fringe patterns one by one.
Further, the current parameter is K × last parameter, and K is a setting coefficient.
Further, the process of performing pixel matching in the motion region is as follows: selecting a matching area capable of carrying out correlation calculation with a matching template in each frame of deformed fringe image, wherein the center point of the matching area is positioned in a motion area, calculating the correlation between all the selected matching areas and the matching template respectively, comparing the magnitudes of all the correlations, and taking the matching area corresponding to the maximum correlation as the optimal area fringe image corresponding to the pixel of a certain point on a measured object in the deformed fringe image.
Furthermore, the size of the defined region is a set region size, and the central point of the approximate region stripe graph is located in the defined region.
According to the invention, correlation calculation is carried out in the whole range of the deformed fringe pattern through a simulated annealing algorithm to generate an approximately optimal region, traversal is carried out in a certain region around the approximately optimal region, so that coordinate information required by pixel matching is obtained, and finally the surface shape height distribution of the three-dimensional object of the measured object is determined. Compared with the prior art, the invention has the following advantages:
1. the invention completes the pretreatment of the pixel matching area in the early stage by the simulated annealing algorithm, saves the process of traversing the whole matching area in the traditional method, and has the characteristics of higher precision and higher speed.
2. Due to the fact that the matching area is preprocessed, the range of traversing pixel points in the later period is reduced, and the efficiency of real-time phase measurement profilometry is improved on the premise that the precision is guaranteed.
3. The method has strong practicability, can flexibly adjust parameters according to the measured object to achieve the optimal matching efficiency, has wide applicability and does not need to increase hardware equipment.
Drawings
FIG. 1 is a schematic diagram of a system for performing the real-time phase profilometry of the present invention.
Fig. 2 is a schematic view of a subject under test.
FIG. 3 is a schematic flow chart of a simulated annealing algorithm according to the present invention.
FIG. 4 is a schematic diagram of the center point of a random region generated in a frame of deformed fringe pattern by using the simulated annealing algorithm of the present invention.
Fig. 5 is an image of the final restored three-dimensional structure using the present invention.
Detailed Description
The following further describes embodiments of the present invention with reference to the drawings. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 1-5, the present invention provides a real-time phase profilometry based on a simulated annealing algorithm, which comprises projecting a fringe pattern onto a measured object moving on a reference plane by using a projection device, acquiring a multi-frame deformed fringe pattern by using an image acquisition system, performing pixel matching by using the simulated annealing algorithm to obtain approximate region fringe patterns corresponding to pixels at a certain point on the measured object in each frame of deformed fringe pattern one by one, and circling a square or circular region or other shape region as a motion region by using a central point of the approximate region fringe patterns as a reference, wherein the size of the motion region is a set region size, and the central point of the approximate region fringe patterns is located in the motion region and can be located at the center or other positions of the motion region; and performing pixel matching in the motion region to obtain an optimal region fringe pattern which corresponds to a pixel at a certain point on the measured object in each frame of deformed fringe pattern one to one, calculating phase information modulated by the height of the measured object and phase change caused by the height of the measured object according to the optimal region fringe pattern, and determining the surface shape height distribution of the three-dimensional object of the measured object according to the corresponding relation of the phase and the height.
In the above scheme, the process of pixel matching by the simulated annealing algorithm is as follows: selecting a matching template, randomly selecting a matching area capable of carrying out correlation calculation with the matching template in each frame of image, comparing the correlation of the corresponding matching areas, selecting an area stripe image by keeping the matching area corresponding to larger correlation and receiving the matching area corresponding to smaller correlation with a certain probability as a reference, and repeating the process of selecting the area stripe image until a termination condition is met, thereby obtaining an approximate area stripe image corresponding to a pixel at a certain point on a measured object in the deformed stripe image.
In the above scheme, the process of performing pixel matching in the motion region is as follows: selecting a matching area capable of carrying out correlation calculation with a matching template in each frame of deformed fringe image, wherein the center point of the matching area is positioned in a motion area, calculating the correlation between all the selected matching areas and the matching template respectively, comparing the magnitudes of all the correlations, and taking the matching area corresponding to the maximum correlation as the optimal area fringe image corresponding to the pixel of a certain point on a measured object in the deformed fringe image.
The projection apparatus of the present invention uses a Digital Light Projector (DLP), the image capturing system uses a Charge-coupled Device (CCD), and the projected planar structured Light usually uses a sinusoidal grating pattern.
When the measured object is not placed on the reference surface, the DLP projected sinusoidal grating stripe is only modulated by the height of the reference surface, and the phase shift quantity of the projected first frame sinusoidal stripe image relative to the nth frame sinusoidal stripe image is set to be deltanAt this time, the acquired deformed fringe pattern is:
wherein (x, y) is the coordinate of pixel point in CCD system, A (x, y) is the background light intensity, B (x, y) represents the contrast of sine stripe, R0(x, y) is the reference plane reflectivity distribution, (2) is the phase information of the reference plane deformed fringes,
is the phase information modulated by the reference plane. f. of0The frequency of the sinusoidal fringes.
When the DLP projects the sinusoidal grating fringe pattern onto the measured object, the height of the measured object can modulate the phase of the sinusoidal grating, and meanwhile, due to the fact that the materials of the reference plane and the surface of the object are different under different measuring conditions, the reflectivity of the reference plane and the surface of the object can also change the gray level of the acquired deformed fringe. Therefore, the light intensity distribution I (x, y) of the deformed streaks is as shown in formula (3):
wherein R (x, y) represents the reflectivity distribution of the reference plane and the object surface, (4) is the phase distribution of the deformed fringes when the measured object is placed on the reference plane,
is the phase information modulated by the height of the object plane.
When the measured object moves on the working platform, taking the CCD to collect five frames of deformed fringe patterns as an example, the coordinates (x, y) of the pixel points corresponding to a certain point on the measured object in the five frames of deformed fringe patterns are (x) respectively1y1)，(x2，y2)，(x3，y3)，(x4，y4)，(x5，y5) The coordinate values of the five pixels are different from each other, but in order to satisfy the characteristic of point-to-point when PMP (real time phase measurement profilometry) calculates the phase, the five pixels must be matched by pixel matching.
The pixel matching process is that a binary matching template T is selected after calculation through Otsu method in the first frame deformed stripe image1(x, y) and a matching region M 'defined in another deformed stripe diagram'nAnd (X, y) performing correlation calculation, wherein the value of the correlation (RL) is shown as a formula (5), and when the value of the RL is the maximum, the two images can be regarded as the same, namely the distance X between the positions of the objects when the two adjacent images are shot can be obtained. Will IN(X, Y) (n is 1, 2, 3, 4, 5) (the region stripe map after pixel matching) moves nXpixel (n is 1, 2, 3, 4, 5) in the opposite direction of the object motion to obtain INp(X, Y) (n ═ 1, 2, 3, 4, 5), and a portion of the same region with object height information is cut out to obtain a deformed stripe pattern I 'with pixels in one-to-one correspondence'n(X, Y) (n ═ 1, 2, 3, 4, 5) complete pixel matching:
after the pixel matching is completed, assuming that a total of N deformed fringe patterns are used in the phase calculation process, the phase shift amount of the nth fringe pattern relative to the first fringe pattern is:
based on the orthogonality of the trigonometric function, the phase information modulated by the height of the object can be calculated by the N frames of deformed fringe patterns
Similarly, the phase information on the reference plane can be obtained by calculating by using the formula (7) after being collected by the CCD
Further, the phase change caused by the height of the measured object can be calculated
And then the corresponding relation between the phase and the height is utilized to recover the surface shape height distribution of the three-dimensional object surface of the object.
In the above scheme, the process of pixel matching by the simulated annealing algorithm specifically includes the following steps:
step 1: setting an initial parameter T0A termination parameter TΔSelecting a matching template by taking the collected first frame deformed fringe pattern as a reference;
step 2: randomly selecting an area capable of carrying out correlation calculation with the matching template from one frame of deformed fringe image as a current area, and calculating a first correlation between the current area and the matching template;
and step 3: randomly selecting another area capable of carrying out correlation calculation with the matching template from the same frame of deformed fringe image as a next area, calculating a second correlation between the next area and the matching template, and comparing the first correlation with the second correlation;
and 4, step 4: when the second degree of correlation is greater than or equal to the first degree of correlation, taking the next area as a new current area, and taking the degree of correlation corresponding to the new current area as a new first degree of correlation, and continuing to step 6;
and 5: when the second correlation degree is smaller than the first correlation degree, calculating the probability of acceptance of the next region, if the probability is larger than a set value, taking the next region as a new current region, and simultaneously taking the correlation degree corresponding to the new current region as a new first correlation degree, and continuing to step 6; if the probability is not greater than the set value, taking the current area as a new current area, and simultaneously taking the correlation degree corresponding to the new current area as a new first correlation degree, and continuing to the step 6;
step 6: calculating the current parameter TnThe current parameter, K, last parameter, i.e. Tn＝K*tn-1And K is a set coefficient. If the current parameter is not less than the termination parameter, returning to the step 3; if the current parameter is less than the termination parameter, taking the new current area as an approximate area stripe image corresponding to the pixel of a certain point on the measured object in the deformed stripe image, and continuing to step 7;
and 7: and (5) repeating the steps 2-6 until obtaining the similar area fringe patterns corresponding to the pixels of a certain point on the measured object in all the deformed fringe patterns one by one.
The invention takes the correlation RL as a target function, obtains an approximate optimal solution in a matching region by utilizing a simulated annealing algorithm, namely an approximate maximum value of the RL and a region corresponding to the RL, further demarcates a moving region around the approximate optimal solution according to the size of a matching pattern, traverses the moving region and calculates the correlation, and takes a point corresponding to the maximum value of the correlation, thus completing pixel matching. As shown in fig. 4, by using the scheme of the present invention, the correlation calculation is performed only in a small range shown in the figure, and the entire region is not traversed.
Those not described in detail in this specification are within the skill of the art.
Claims (5)
1. A real-time phase measurement profilometry based on simulated annealing algorithm, characterized by: projecting the fringe pattern onto a measured object moving on a reference plane, collecting multiple frames of deformed fringe patterns, carrying out pixel matching through a simulated annealing algorithm to obtain approximate region fringe patterns corresponding to pixels of a certain point on the measured object in each frame of deformed fringe patterns one by one, using the central point of the approximate region fringe patterns as a reference to define a region as a moving region, carrying out pixel matching in the moving region to obtain optimal region fringe patterns corresponding to the pixels of the certain point on the measured object in each frame of deformed fringe patterns one by one, calculating phase information modulated by the height of the measured object and phase change caused by the height of the measured object according to the optimal region fringe patterns, and determining the surface shape height distribution of the three-dimensional object according to the corresponding relation of the phase and the height;
the process of pixel matching through the simulated annealing algorithm comprises the following steps: selecting a matching template, randomly selecting a matching area capable of carrying out correlation calculation with the matching template in each frame of image, comparing the correlation of the corresponding matching areas, selecting an area stripe image by keeping the matching area corresponding to larger correlation and receiving the matching area corresponding to smaller correlation with a certain probability as a reference, and repeating the process of selecting the area stripe image until a termination condition is met, thereby obtaining an approximate area stripe image corresponding to a pixel at a certain point on a measured object in the deformed stripe image.
2. The simulated annealing algorithm-based real-time phase measurement profilometry according to claim 1, wherein: the process of pixel matching by simulated annealing algorithm comprises the following steps:
step 1: setting initial parameters and termination parameters, and selecting a matching template by taking the acquired first frame of deformed fringe pattern as a reference;
step 2: randomly selecting an area capable of carrying out correlation calculation with the matching template from one frame of deformed fringe image as a current area, and calculating a first correlation between the current area and the matching template;
and step 3: randomly selecting another area capable of carrying out correlation calculation with the matching template from the same frame of deformed fringe image as a next area, calculating a second correlation between the next area and the matching template, and comparing the first correlation with the second correlation;
and 4, step 4: when the second degree of correlation is greater than or equal to the first degree of correlation, taking the next area as a new current area, and taking the degree of correlation corresponding to the new current area as a new first degree of correlation, and continuing to step 6;
and 5: when the second correlation degree is smaller than the first correlation degree, calculating the probability of acceptance of the next region, if the probability is larger than a set value, taking the next region as a new current region, and simultaneously taking the correlation degree corresponding to the new current region as a new first correlation degree, and continuing to step 6; if the probability is not greater than the set value, taking the current area as a new current area, and simultaneously taking the correlation degree corresponding to the new current area as a new first correlation degree, and continuing to the step 6;
step 6: calculating the current parameter, and if the current parameter is not less than the termination parameter, returning to the step 3; if the current parameter is less than the termination parameter, taking the new current area as an approximate area stripe image corresponding to the pixel of a certain point on the measured object in the deformed stripe image, and continuing to step 7;
and 7: and (5) repeating the steps 2-6 until obtaining the similar area fringe patterns corresponding to the pixels of a certain point on the measured object in all the deformed fringe patterns one by one.
3. The simulated annealing algorithm-based real-time phase measurement profilometry according to claim 2, wherein: and the current parameter is K, the last parameter, and K is a set coefficient.
4. The simulated annealing algorithm-based real-time phase measurement profilometry according to claim 1, wherein: the process of pixel matching in the motion area is as follows: selecting a matching area capable of carrying out correlation calculation with a matching template in each frame of deformed fringe image, wherein the center point of the matching area is positioned in a motion area, calculating the correlation between all the selected matching areas and the matching template respectively, comparing the magnitudes of all the correlations, and taking the matching area corresponding to the maximum correlation as the optimal area fringe image corresponding to the pixel of a certain point on a measured object in the deformed fringe image.
5. The simulated annealing algorithm-based real-time phase measurement profilometry according to claim 1, wherein: the size of the defined region is the set region size, and the central point of the approximate region stripe graph is located in the defined region.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910472262.0A CN110375672B (en) | 2019-05-31 | 2019-05-31 | Real-time phase measurement profilometry based on simulated annealing algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910472262.0A CN110375672B (en) | 2019-05-31 | 2019-05-31 | Real-time phase measurement profilometry based on simulated annealing algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110375672A CN110375672A (en) | 2019-10-25 |
| CN110375672B true CN110375672B (en) | 2021-03-30 |
Family
ID=68249614
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910472262.0A Expired - Fee Related CN110375672B (en) | 2019-05-31 | 2019-05-31 | Real-time phase measurement profilometry based on simulated annealing algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110375672B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111476788B (en) * | 2020-04-27 | 2023-08-25 | 武汉精立电子技术有限公司 | Display screen interlayer defect detection method and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103997386A (en) * | 2014-06-03 | 2014-08-20 | 北京邮电大学 | Method for accurately converting arbitrary modes based on simulated annealing algorithm |
| CN106251302A (en) * | 2016-07-27 | 2016-12-21 | 合肥高晶光电科技有限公司 | A kind of image processing method based on simulated annealing |
| WO2017202823A1 (en) * | 2016-05-24 | 2017-11-30 | Université Du Luxembourg | Data transmission method and device using non-uniform apsk constellations |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10327159B2 (en) * | 2014-12-09 | 2019-06-18 | Futurewei Technologies, Inc. | Autonomous, closed-loop and adaptive simulated annealing based machine learning approach for intelligent analytics-assisted self-organizing-networks (SONs) |
-
2019
- 2019-05-31 CN CN201910472262.0A patent/CN110375672B/en not_active Expired - Fee Related
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103997386A (en) * | 2014-06-03 | 2014-08-20 | 北京邮电大学 | Method for accurately converting arbitrary modes based on simulated annealing algorithm |
| WO2017202823A1 (en) * | 2016-05-24 | 2017-11-30 | Université Du Luxembourg | Data transmission method and device using non-uniform apsk constellations |
| CN106251302A (en) * | 2016-07-27 | 2016-12-21 | 合肥高晶光电科技有限公司 | A kind of image processing method based on simulated annealing |
Non-Patent Citations (2)
| Title |
|---|
| 基于低调制度特征的在线三维测量方法;彭旷等;《中国激光》;20130731;第40卷(第7期);第1-6页 * |
| 基于模拟退火的相位测量轮廓术随机相移误差校正;任旭虎等;《中国石油大学学报(自然科学版)》;20100331;第34卷(第3期);第162-169页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110375672A (en) | 2019-10-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Tsai et al. | Development of a high-precision surface metrology system using structured light projection | |
| CN101986098B (en) | Tricolor projection-based Fourier transform three-dimensional measuring method | |
| CN103400366B (en) | Based on the dynamic scene depth acquisition methods of fringe structure light | |
| CN104061879B (en) | A kind of structural light three-dimensional face shape vertical survey method continuously scanned | |
| CN108955571B (en) | The method for three-dimensional measurement that double frequency heterodyne is combined with phase-shift coding | |
| CN113237435B (en) | High-light-reflection surface three-dimensional vision measurement system and method | |
| CN109945802B (en) | Structured light three-dimensional measurement method | |
| CN110174079B (en) | Three-dimensional reconstruction method based on four-step phase-shift coding type surface structured light | |
| CN110207620B (en) | Three-dimensional reconstruction method for determining optical series of digital grating projection structure through different frequencies | |
| CN107014313B (en) | Method and system for weighted least square phase unwrapping based on S-transform ridge value | |
| CN111932632A (en) | Phase correction method in three-dimensional reconstruction of mechanical part | |
| WO2013012054A1 (en) | Image processing method and apparatus | |
| CN113763540A (en) | Three-dimensional reconstruction method and equipment based on speckle fringe hybrid modulation | |
| CN110375672B (en) | Real-time phase measurement profilometry based on simulated annealing algorithm | |
| CN114152203A (en) | Bearing inner and outer diameter size measuring method based on phase coding structured light | |
| CN110243308A (en) | Real-time phase based on zone location measures technology of profiling | |
| CN116385653A (en) | Three-dimensional imaging self-supervision method and device based on single-view high-frequency stripes | |
| CN111640084A (en) | High-speed pixel matching method based on LK optical flow | |
| Wang et al. | A fast and precise three-dimensional measurement system based on multiple parallel line lasers | |
| CN115839677A (en) | Method and system for measuring three-dimensional topography of surface of object with high dynamic range | |
| CN113137939B (en) | Unpacking method based on binary characteristic pattern matching | |
| CN110057321B (en) | Three-dimensional object surface shape measuring method for rapidly realizing frequency domain dephasing based on x-f-k transformation | |
| CN116824069B (en) | Self-adaptive stripe method for detecting saturation point by using high-frequency signal | |
| CN114858094B (en) | Learning type single-frame Moire profile measurement method for dynamic object | |
| Peng et al. | Using triangle-based cubic interpolation in generation of object-adaptive fringe pattern |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210330 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |