CN116824069B - Self-adaptive stripe method for detecting saturation point by using high-frequency signal - Google Patents
Self-adaptive stripe method for detecting saturation point by using high-frequency signal Download PDFInfo
- Publication number
- CN116824069B CN116824069B CN202311108961.XA CN202311108961A CN116824069B CN 116824069 B CN116824069 B CN 116824069B CN 202311108961 A CN202311108961 A CN 202311108961A CN 116824069 B CN116824069 B CN 116824069B
- Authority
- CN
- China
- Prior art keywords
- frequency
- light intensity
- camera
- projector
- saturation point
- 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
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000002310 reflectometry Methods 0.000 claims abstract description 15
- 238000013507 mapping Methods 0.000 claims abstract description 14
- 230000010363 phase shift Effects 0.000 claims description 11
- 238000013139 quantization Methods 0.000 claims description 8
- 229920006395 saturated elastomer Polymers 0.000 claims description 8
- 230000003044 adaptive effect Effects 0.000 claims description 7
- 238000007500 overflow downdraw method Methods 0.000 claims description 6
- 230000004927 fusion Effects 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 238000001514 detection method Methods 0.000 abstract description 8
- 230000000694 effects Effects 0.000 abstract description 6
- 229910001220 stainless steel Inorganic materials 0.000 description 5
- 239000010935 stainless steel Substances 0.000 description 5
- 238000002474 experimental method Methods 0.000 description 4
- 238000003384 imaging method Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 238000005286 illumination Methods 0.000 description 2
- 239000012212 insulator Substances 0.000 description 2
- 238000001314 profilometry Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000002457 bidirectional effect Effects 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Abstract
The invention discloses a self-adaptive stripe method for detecting a saturation point by utilizing a high-frequency signal, which solves the problems that the influence of a multipath effect on the saturation point is ignored by the traditional saturation point detection method, the signal-to-noise ratio is large and the reconstruction result is inaccurate. The invention adopts a projection high-frequency stripe pattern instead of a uniform gray pattern as a detection saturation point, solves the reflectivity of the surface of a detected object and the ambient light based on the detection saturation point simultaneously, calculates an optimal projection light intensity value, and then changes the projection light intensity value pixel by combining the coordinate mapping relation of a camera and a projector to generate a group of self-adaptive projection stripes. The self-adaptive stripe generated by the invention is utilized to reconstruct the three-dimensional object, thereby improving the accuracy of three-dimensional reconstruction and having higher signal to noise ratio.
Description
Technical Field
The invention belongs to the technical field of three-dimensional reconstruction, and particularly relates to a self-adaptive stripe method for detecting saturation points by using high-frequency signals.
Background
The structured light three-dimensional imaging technology is an active non-contact optical three-dimensional imaging technology, and the phase measurement profilometry (Phase Measuring Profilometry, PMP) is one of the commonly used structured light three-dimensional imaging technologies, and is widely applied to various industries due to the advantages of imaging precision, speed, cost and the like.
The PMP three-dimensional reconstruction system mainly comprises a camera, a projector and a computer, wherein the projector projects a preset sinusoidal deformation stripe pattern onto the surface of a measured object, the camera is responsible for capturing the deformation stripe back, and finally the computer generates a three-dimensional point cloud through a solution phase to reconstruct the surface profile of the measured object. If the light intensity value of the collected deformed stripe light intensity exceeds the quantization range of the camera, the light intensity is saturated, saturation errors are generated, and the point where the saturation errors are generated is called a saturation point. Therefore, the saturation point is accurately detected, and the occurrence of light intensity saturation is avoided, so that the three-dimensional reconstruction precision of the highly reflective object can be effectively improved. In the self-adaptive stripe method, a uniform gray pattern is projected onto a measured high-reflection object, a pattern captured by a camera is used as a reference pattern for detecting a saturation point, and when the illumination intensity of the reference pattern reaches a set saturation threshold value, the reference pattern is judged to be the saturation point. The conventional saturation point detection method ignores the influence of the light-dark change area in the stripe pattern on the saturation point in the actual situation, which is called multipath effect, i.e. the light intensity information of each pixel point can be included in the fieldMN-1Light intensity information of individual pixels. Therefore, when three-dimensional reconstruction is performed on a mirror-like object with high surface reflectivity, saturation errors are caused by light intensity saturation, and the reconstruction accuracy is low.
Therefore, the present invention proposes an adaptive stripe method for detecting saturation points by using high frequency signals, so as to at least solve the above-mentioned part of technical problems.
Disclosure of Invention
The invention aims to solve the technical problems that: an adaptive stripe method for detecting saturation points by using high-frequency signals is provided to solve at least some of the above technical problems.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
an adaptive striping method for detecting saturation points using high frequency signals, comprising:
step 1, projector generates and projectsKA set of deformed high frequency fringe patterns, each set of deformed high frequency fringe patterns comprisingNA plurality of deformed high frequency fringes;
step 2, projection-basedKGroup deformation high-frequency fringe pattern, and camera acquisition to obtain corresponding imageKA set of acquisition high frequency fringe patterns, each set of acquisition high frequency fringe patterns comprisingNCollecting high frequency stripes, combining each groupNIntegrating the acquired high-frequency stripes into a fused high-frequency stripe, and combining each groupNThe deformation high-frequency stripes are integrated into one deformation high-frequency stripe;
step 3, detecting saturation points of the fusion high-frequency stripes to obtain saturation points;
step 4, calculating the environment light intensity and the reflectivity of the surface of the measured object based on the saturation point;
step 5, obtaining an optimal projection light intensity value of the projector pixel point according to the environment light intensity and the reflectivity of the surface of the measured object;
step 6, determining a coordinate mapping relation between the camera and the projector;
and 7, replacing the projection light intensity of the saturated point with the optimal projection light intensity according to the coordinate mapping relation between the camera and the projector, and generating the self-adaptive projection stripes by the projector.
Further, in the step 1, a coding method is adopted to generate K groups of deformed high-frequency fringe patterns, and the coding method of the light intensity value of each deformed high-frequency fringe pattern is as follows:wherein:for projecting the height of the picture +.>Is the ordinate of the projector, T isMaximum quantization value of camera,/>Group number for deforming high-frequency stripe group, < >>，nFor the phase shift index,Nfor the total number of phase shifts,n=0,1,2,3,...,N-1，/>is the light intensity difference between two adjacent groups of deformed high-frequency fringe patterns, +.>Is the highest frequency of the deformed high frequency streak.
Further, in the step 2, each group is fused by using an image fusion methodNLight intensity values of the high-frequency stripes are acquiredLight intensity value integrated as a fused high-frequency stripe +.>The image fusion method comprises the following steps: />Wherein:representing the collection +.>Is a maximum value of (a).
Further, in the step 2, the light intensity values of each set of N deformed high-frequency fringes are calculatedLight intensity value integrated as a deformed high-frequency stripe +.>，/>。
Further, in the step 3, the light intensity value of the high-frequency stripe is fusedDetecting a line saturation point to obtain a saturation point, wherein the method for detecting the saturation point comprises the following steps: />Wherein: />Equal to 1 indicates saturation, ">An equal to 0 represents unsaturation, and T is the maximum quantization value of the camera.
Further, in the step 4, a simultaneous equation set is constructed by using the saturation point, and the environmental light intensity is calculatedAnd the reflectivity of the surface of the object to be measured>The simultaneous equations are: />Wherein: />Needs to meet->And->Are all 0->1.
Further, in said step 5, an optimal projection light intensity valueThe calculation method of (1) is as follows:wherein: 249 is the set light intensity saturation threshold.
Further, in the step 6, a coordinate mapping relationship between the camera and the projector is established by projecting a bi-directional phase shift stripe with low light intensity onto the surface of the measured object, where the coordinate mapping relationship between the camera and the projector is:wherein: />For projector abscissa, +.>For the projector ordinate, +.>For the absolute phase in the vertical direction of the camera, +.>For the absolute phase of the camera in the horizontal direction, +.>For camera abscissa, +.>For the ordinate of the camera, +.>For projecting the height of the picture +.>Is the width of the projected picture.
Compared with the prior art, the invention has the following beneficial effects:
the invention adopts a projection high-frequency stripe pattern instead of a uniform gray pattern as a detection saturation point, solves the reflectivity of the surface of a detected object and the ambient light based on the detection saturation point simultaneously, calculates an optimal projection light intensity value, and then changes the projection light intensity value pixel by combining the coordinate mapping relation of a camera and a projector to generate a group of self-adaptive projection stripes. The self-adaptive stripe generated by the invention is utilized to perform the phase resolution and the three-dimensional reconstruction of the object, thereby improving the three-dimensional reconstruction precision and having higher signal to noise ratio.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings, in order to make the objects, technical solutions and advantages of the present invention more apparent. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the self-adaptive stripe method, a uniform gray pattern is projected onto a measured high-reflection object, a pattern captured by a camera is used as a reference pattern for detecting a saturation point, and when the illumination intensity of the reference pattern reaches a set saturation threshold, the reference pattern is judged to be the saturation point. The saturation point detection method ignores the influence of the light and shade change area in the stripe pattern on the saturation point under the actual condition, which is called multipath effect, i.e. the light intensity information of each pixel point can be contained in the fieldMN-1The smaller the gray value of other pixels in the field, the smaller the light intensity information of each pixel, and the light intensity value of the captured pattern by the camera. Because of the existence of black stripes in the sinusoidal fringe pattern of the gray scale pattern, the multipath effect in the sinusoidal fringe pattern has a relatively obvious influence on the light intensity value of the camera capturing pattern, and under the influence of the multipath effect, some saturated points detected by the uniform gray scale pattern are not saturated points in the actual sinusoidal fringe pattern.
In view of the above problems, the present invention provides an adaptive fringe method for detecting saturation points using a high frequency signal, as shown in fig. 1. The invention adopts the coding method to generate K groups of deformation high-frequency fringe patterns, and the light intensity value of each deformation high-frequency fringe patternThe coding method comprises the following steps:wherein->For projecting the height of the picture +.>For the projector ordinate, T is the maximum quantization value of the camera, < >>To distort the group number of the high frequency stripe group,，nfor the phase shift index,Nfor the total number of phase shifts,n=0,1,2,3,...,N-1，/>is the light intensity difference between two adjacent groups of deformed high-frequency fringe patterns, +.>Generally taking a fixed constant, +.>For deforming the highest frequency of the high frequency stripe, < >>Also a fixed constant.
Then adopting an image fusion method to integrate each groupNLight intensity values of the high-frequency stripes are acquiredLight intensity value integrated as a fused high-frequency stripe +.>The image fusion method comprises the following steps: />Wherein: />Representing a collectionIs a maximum value of (a).
At the same time, the light intensity values of each group of N deformation high-frequency stripesLight intensity value integrated into a deformed high-frequency stripe，/>。
And then the light intensity value of the high-frequency stripes is fusedDetecting a line saturation point to obtain a saturation point, wherein the method for detecting the saturation point comprises the following steps:wherein: />Equal to 1 indicates saturation, ">An equal to 0 represents unsaturation, and T is the maximum quantization value of the camera. The light intensity value of the high-frequency stripes is fused +.>Equal to or exceeding the maximum quantization value of the cameraTIs taken as the saturation point.
The light intensity captured by the camera mainly comprises three parts, namely projection light intensity, light intensity of the environment light intensity reflected by the surface of the measured object and light intensity of the environment light directly entering the camera, wherein the light intensity of the environment light intensity reflected by the surface of the measured object comprises light of the projection light intensity reflected by the surface of the measured object and light of the environment light intensity reflected by the surface of the measured object. In conventional algorithms, the test is performedThe reflectivity of the object surface, the ambient light intensity and the light reflected by the measured object surface are calculated by projecting a Quan Bai chart and a full black chart. According to the invention, the reference pattern for detecting the saturation point is utilized to establish an equation set to respectively solve the reflectivity of the surface of the measured object and the ambient light intensity, and then the ambient light intensity and the light reflected by the surface of the measured object are solved, so that the data can be ensured to be less disturbed by noise by utilizing the higher light intensity pattern for solving, and the result can be more accurate. The system of equations that are associated with the reference pattern of saturation points is:wherein: />Needs to meet->And->Are all 0->1.
Further, the above formula is rewritten as:for this purpose, the ambient light intensity can be solved>And the reflectivity of the surface of the object to be measured>Then the ambient light intensity and the light reflected by the surface of the measured object are obtained>。
Theoretically, when the light intensity captured by the camera is not more than 255, the projected light intensity is the optimal projected light intensity, but in practice, the saturation threshold is properly lowered, the invention sets 249 is the light intensity saturation threshold, so based on the obtained ambient light intensity and the light reflected by the surface of the measured object, the optimal projected light intensity can be expressed as:. In calculating the optimum projection light intensity value +.>Then, the coordinates of the camera and the projector need to be matched to change the projection light intensity pixel by pixel so as to generate the self-adaptive projection stripes. The invention establishes the coordinate mapping relation between the camera and the projector by projecting the low-light-intensity bidirectional phase shift stripes on the surface of the measured object, and the coordinate mapping relation between the camera and the projector is as follows: />Wherein: />For projector abscissa, +.>For the projector ordinate, +.>For the absolute phase in the vertical direction of the camera, +.>For the absolute phase of the camera in the horizontal direction, +.>For camera abscissa, +.>For the ordinate of the camera, +.>For projecting the height of the picture +.>Is the width of the projected picture.
Then, according to the coordinate mapping relation between the camera and the projector, the projected light intensity of the saturated point is replaced by the optimal projected light intensity, and the projector generates self-adaptive projection stripes; and finally, carrying out three-dimensional reconstruction of the object by utilizing the generated self-adaptive stripes.
A three-dimensional reconstruction experiment is performed on a stainless steel plate with a large surface flatness and reflectivity range by using a Prosilicon GC650C camera with a resolution of 640 pixels by 480 pixels, a Casio XJ-A155V projector with a resolution of 800 pixels by 600 pixels and a computer for controlling experimental equipment and data processing.
Firstly, the exposure time of a camera is adjusted to 4791 microseconds by using software on a computer, the highest light intensity of projection is 255, the frequencies are 1, 4, 16 and 32, each frequency is 160-step phase shift, and the total of 800 sine fringe patterns acquire the real phase of a stainless steel plate for subsequent error analysis so as to more obviously distinguish the reconstruction effects of different methods. After the true phase is acquired, the camera exposure time is again adjusted to 8000 microseconds with software, at which time subsequent experiments are performed.
Then using the coding method:in the formula->Set to 32->Is set to be 5 and is set to be a constant value,Tinitially set to 255 and then generate maximum intensityT48 sets of deformed high-frequency fringe patterns sequentially decreasing from 255 to 20; the camera acquires 48 groups of corresponding acquired high-frequency fringe patterns, performs image fusion and then performs saturation point detection; calculating the environment light intensity, the stainless steel plate surface reflectivity and the optimal projection light intensity value of the projector pixel point based on the detected saturation point; according to the objects with different reflectivities, the empirical values of different low gray values can be taken, generally, 100 is taken as the highest light intensity of projection, and then the sinusoidal fringe pattern with the highest light intensity of 100 is projected in the two directionsSolving the absolute phase of the horizontal direction of the camera>Absolute phase in the vertical direction of the camera>The method comprises the steps of carrying out a first treatment on the surface of the And finally, determining a coordinate mapping relation between the camera and the projector, and finally, combining the calculated optimal projection light intensity to generate a group of self-adaptive sine stripes with the highest light intensity of 255 and the frequencies of 1, 4, 16 and 32, wherein the total number of the self-adaptive sine stripes is 32 for three-dimensional reconstruction of the stainless steel plate, and each frequency is 8-step phase shift.
Meanwhile, a traditional PMP method is adopted to carry out three-dimensional reconstruction experiments on the same stainless steel plate, and the three-dimensional reconstruction experiments are used as comparison. Table 1 compares the Root Mean Square Error (RMSE) and the maximum error (MaxE) of the reconstructed images obtained by the method of the present invention and the PMP method and the number of sets of desired projection images, with the assumption that 48 saturation detected images are recorded as one set.
TABLE 1
Compared with the traditional PMP method, the method has the highest precision, and the root mean square error in the 295 th column, the root mean square error in the saturated region and the maximum error in the saturated region are respectively reduced by 97.88%, 95.71% and 98.49%.
In order to verify the application range of the method, three-dimensional reconstruction is carried out on the insulator workpiece with a more complex shape, meanwhile, the reconstruction result of the PMP method has larger reconstruction error and cannot reconstruct the three-dimensional shape of the insulator workpiece by adopting the PMP method for comparison, and the method can reconstruct the three-dimensional shape, and the reconstruction result has higher signal to noise ratio and smoother signal to noise ratio.
Finally, it should be noted that: the above embodiments are merely preferred embodiments of the present invention for illustrating the technical solution of the present invention, but not limiting the scope of the present invention; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions; that is, even though the main design concept and spirit of the present invention is modified or finished in an insubstantial manner, the technical problem solved by the present invention is still consistent with the present invention, and all the technical problems are included in the protection scope of the present invention; in addition, the technical scheme of the invention is directly or indirectly applied to other related technical fields, and the technical scheme is included in the scope of the invention.
Claims (4)
1. An adaptive fringe method for detecting saturation points using high frequency signals, comprising:
step 1, projector generates and projectsKA set of deformed high frequency fringe patterns, each set of deformed high frequency fringe patterns comprisingNA plurality of deformed high frequency fringes;
step 2, projection-basedKGroup deformation high-frequency fringe pattern, and camera acquisition to obtain corresponding imageKA set of acquisition high frequency fringe patterns, each set of acquisition high frequency fringe patterns comprisingNCollecting high frequency stripes, combining each groupNIntegrating the acquired high-frequency stripes into a fused high-frequency stripe, and combining each groupNThe deformation high-frequency stripes are integrated into one deformation high-frequency stripe;
step 3, detecting saturation points of the fusion high-frequency stripes to obtain saturation points;
step 4, calculating the environment light intensity and the reflectivity of the surface of the measured object based on the saturation point;
step 5, obtaining an optimal projection light intensity value of the projector pixel point according to the environment light intensity and the reflectivity of the surface of the measured object;
step 6, determining a coordinate mapping relation between the camera and the projector;
step 7, replacing the projected light intensity of the saturated point with the optimal projected light intensity according to the coordinate mapping relation between the camera and the projector, and generating self-adaptive projection stripes by the projector;
in the step 1, a coding method is adopted to generate K groups of deformed high-frequency fringe patterns, and the coding method of the light intensity value of each deformed high-frequency fringe pattern is as follows:wherein: />For projecting the height of the picture +.>For the projector ordinate, T is the maximum quantization value of the camera, < >>To distort the group number of the high frequency stripe group,，nfor the phase shift index,Nfor the total number of phase shifts,n=0,1,2,3,...,N-1，/>is the light intensity difference between two adjacent groups of deformed high-frequency fringe patterns, +.>The highest frequency of the deformed high-frequency stripes;
in the step 2, each group is fused by adopting an image fusion methodNLight intensity values of the high-frequency stripes are acquiredLight intensity value integrated as a fused high-frequency stripe +.>The image fusion method comprises the following steps: />In the following：/>Representing the collection +.>Is the maximum value of (2);
in the step 2, the light intensity values of each group of N deformed high-frequency fringesLight intensity value integrated as a deformed high-frequency stripe +.>，/>；
In the step 3, the light intensity value of the fused high-frequency stripesDetecting a line saturation point to obtain a saturation point, wherein the method for detecting the saturation point comprises the following steps: />Wherein: />Equal to 1 indicates saturation, ">An equal to 0 represents unsaturation, and T is the maximum quantization value of the camera.
2. The adaptive fringe method for detecting saturation points utilizing high-frequency signals as recited in claim 1, wherein in said step 4, a simultaneous equation set is constructed utilizing saturation points, and an ambient light intensity is calculatedAnd quiltMeasuring object surface reflectivity +.>The simultaneous equations are: />Wherein: />Needs to meet->And->Are all 0->1.
3. The adaptive fringe method for detecting saturation point utilizing high-frequency signals as recited in claim 2, wherein in said step 5, an optimal projected light intensity valueThe calculation method of (1) is as follows: />Wherein: 249 is the set light intensity saturation threshold.
4. The method of detecting saturation point according to claim 2, wherein in the step 6, a coordinate mapping relationship between the camera and the projector is established by projecting a bi-directional phase-shift stripe with low light intensity onto the surface of the object to be detected, and the coordinate mapping relationship between the camera and the projector is:wherein: />For projector abscissa, +.>For the projector ordinate, +.>For the absolute phase in the vertical direction of the camera, +.>For the absolute phase of the camera in the horizontal direction, +.>For camera abscissa, +.>For the ordinate of the camera, +.>For projecting the height of the picture +.>Is the width of the projected picture.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311108961.XA CN116824069B (en) | 2023-08-31 | 2023-08-31 | Self-adaptive stripe method for detecting saturation point by using high-frequency signal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311108961.XA CN116824069B (en) | 2023-08-31 | 2023-08-31 | Self-adaptive stripe method for detecting saturation point by using high-frequency signal |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116824069A CN116824069A (en) | 2023-09-29 |
| CN116824069B true CN116824069B (en) | 2023-11-10 |
Family
ID=88139599
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311108961.XA Active CN116824069B (en) | 2023-08-31 | 2023-08-31 | Self-adaptive stripe method for detecting saturation point by using high-frequency signal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116824069B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103727898A (en) * | 2014-01-21 | 2014-04-16 | 成都天拓众成科技有限公司 | Rapid three-dimensional measurement system and method for correcting nonlinear distortion through lookup tables |
| CN109631797A (en) * | 2018-12-28 | 2019-04-16 | 广东奥普特科技股份有限公司 | A kind of three-dimensionalreconstruction inactive area method for rapidly positioning based on phase-shifting technique |
| CN110207614A (en) * | 2019-05-28 | 2019-09-06 | 南京理工大学 | One kind being based on the matched high-resolution high precision measuring system of doubly telecentric camera and method |
| CN113108721A (en) * | 2021-04-09 | 2021-07-13 | 四川大学 | High-reflectivity object three-dimensional measurement method based on multi-beam self-adaptive complementary matching |
| CN114509024A (en) * | 2022-04-20 | 2022-05-17 | 广东工业大学 | Large-depth-range three-dimensional measurement method, system and device based on phase fusion |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7469160B2 (en) * | 2003-04-18 | 2008-12-23 | Banks Perry S | Methods and apparatus for evaluating image focus |
| US11317078B2 (en) * | 2019-05-28 | 2022-04-26 | Purdue Research Foundation | Method and system for automatic exposure determination for high- resolution structured light 3D imaging |
| JP2022088887A (en) * | 2020-12-03 | 2022-06-15 | セイコーエプソン株式会社 | Adjustment method, measurement method, projection system, information processing apparatus, and program |
-
2023
- 2023-08-31 CN CN202311108961.XA patent/CN116824069B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103727898A (en) * | 2014-01-21 | 2014-04-16 | 成都天拓众成科技有限公司 | Rapid three-dimensional measurement system and method for correcting nonlinear distortion through lookup tables |
| CN109631797A (en) * | 2018-12-28 | 2019-04-16 | 广东奥普特科技股份有限公司 | A kind of three-dimensionalreconstruction inactive area method for rapidly positioning based on phase-shifting technique |
| CN110207614A (en) * | 2019-05-28 | 2019-09-06 | 南京理工大学 | One kind being based on the matched high-resolution high precision measuring system of doubly telecentric camera and method |
| CN113108721A (en) * | 2021-04-09 | 2021-07-13 | 四川大学 | High-reflectivity object three-dimensional measurement method based on multi-beam self-adaptive complementary matching |
| CN114509024A (en) * | 2022-04-20 | 2022-05-17 | 广东工业大学 | Large-depth-range three-dimensional measurement method, system and device based on phase fusion |
Non-Patent Citations (5)
| Title |
|---|
| Adaptive digital fringe projection technique for high dynamic range three-dimensional shape measurement;Hui Lin 等;Optics Express;第24卷(第7期);7703-7718 * |
| Adaptive projection intensity adjustment for avoiding saturation in three-dimensional shape measurement;Chao Chen 等;Optics Communications;第410卷;694-702 * |
| High-frequency color-encoded fringe-projection profilometry based on geometry constraint for large depth range;Yingying Wan 等;Optics Express;第28卷(第9期);13043-13058 * |
| 用于智能移动设备的条纹反射法检测系统;冀翼 等;中国光学;第10卷(第02期);267-279 * |
| 高反光表面三维形貌测量技术;张宗华 等;红外与激光工程;第49卷(第03期);104-116 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116824069A (en) | 2023-09-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107607060B (en) | A kind of phase error compensation method applied in the measurement of grating tripleplane | |
| CN113237435B (en) | High-light-reflection surface three-dimensional vision measurement system and method | |
| CN107917679B (en) | Dynamic detection and compensation method for highlight and dark regions | |
| Wang et al. | Three-dimensional reconstruction with single-shot structured light dot pattern and analytic solutions | |
| CN108759709A (en) | A kind of white light interference three-dimensional rebuilding method suitable for surface profile measurement | |
| CN108362226B (en) | Double four-step phase shift method for improving phase measurement precision of image overexposure area | |
| CN110864650A (en) | Flatness measuring method based on fringe projection | |
| CN109307483A (en) | A kind of phase developing method based on structured-light system geometrical constraint | |
| Sun et al. | A 3D shape measurement method for high-reflective surface based on accurate adaptive fringe projection | |
| Li et al. | 3D measurement system based on divergent multi-line structured light projection, its accuracy analysis | |
| CN106546193B (en) | Three-dimensional measurement method and system for surface of high-reflection object | |
| CN111256587A (en) | High-reflectivity surface three-dimensional measurement method based on double-line structured light scanning | |
| CN115479557A (en) | High-reflection object surface defect detection based on phase shift deflection technology | |
| Zhang et al. | Improving the extracting precision of stripe center for structured light measurement | |
| Sansoni et al. | A 3D vision system based on one-shot projection and phase demodulation for fast profilometry | |
| CN112082508A (en) | Three-dimensional measurement method and device of reflective object and terminal equipment | |
| CN114459384A (en) | Phase shift profilometry based on multi-angle sine stripe light field fusion | |
| Wang et al. | A new method for high dynamic range 3D measurement combining adaptive fringe projection and original-inverse fringe projection | |
| CN116608794B (en) | Anti-texture 3D structured light imaging method, system, device and storage medium | |
| CN103322944A (en) | Coaxial illumination mirror image Moire measuring device and method | |
| CN116824069B (en) | Self-adaptive stripe method for detecting saturation point by using high-frequency signal | |
| CN104266607A (en) | Mirror plane target contour optical measuring system and method | |
| Sansoni et al. | Fast 3D profilometer based upon the projection of a single fringe pattern and absolute calibration | |
| KR101555027B1 (en) | Appapatus for three-dimensional shape measurment and method the same | |
| Schoenleber et al. | Fast and flexible shape control with adaptive LCD fringe masks |
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 |