Gamma correction method and system based on structured light three-dimensional measurement

Abstract

The application discloses a Gamma correction method and system based on structured light three-dimensional measurement, and comprises the following steps: determining a gray response range of a three-dimensional measurement system; within the gray response range, a Gamma correction model representing the relationship between the actual collected image output by the three-dimensional measurement system and the gray value of the input gray image is established; the Gamma correction model is solved based on a genetic algorithm fitting; the projected fringe image is pre-encoded and corrected according to the solved Gamma correction model, the pre-encoded and corrected fringe image is projected onto the surface of an object to be measured, and three-dimensional measurement is realized. The application provides a Gamma distortion active correction method, the Gamma correction model is determined by reverse thinking, the problem that the inverse function is not unique is avoided, and the robustness of the correction method is stronger.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of three-dimensional measurement correction, and more particularly relates to a Gamma correction method and system based on structured light three-dimensional measurement. BACKGROUND

[0002] Structured light three-dimensional measurement is realized by projecting a fringe image onto a target surface to be measured and obtaining height information of the object surface according to the collected deformed fringe phase information. In a structured light measurement system, the projector and the camera have the characteristics of nonlinear distortion. The fringe captured by the camera does not have good sinusoidal properties, that is, there is a problem of nonlinear intensity response (Gamma effect), which will cause phase errors and thus affect the accuracy of three-dimensional measurement. Therefore, Gamma correction needs to be performed on the structured light three-dimensional measurement system to compensate for phase errors and improve measurement accuracy. SUMMARY

[0003] In view of the above defects or improvement needs of the prior art, the present application provides a Gamma correction method and system based on structured light three-dimensional measurement, which gives a Gamma distortion active correction method, greatly reduces the calculation amount of unpacking operation, and has a wider application range.

[0004] To achieve the above-mentioned purpose, according to a first aspect of the present application, a Gamma correction method based on structured light three-dimensional measurement is provided, comprising:

[0005] determining a gray scale response range of the three-dimensional measurement system;

[0006] establishing a Gamma correction model representing the relationship between the actual collected image and the input gray scale image in the gray scale response range of the three-dimensional measurement system;

[0007] solving the Gamma correction model based on a genetic algorithm;

[0008] pre-encoding and correcting the fringe image to be projected according to the solved Gamma correction model, projecting the pre-encoding and corrected fringe image onto the surface of the object to be measured, and realizing three-dimensional measurement.

[0009] Further, the determination of the gray scale response range of the three-dimensional measurement system comprises:

[0010] generating a series of gray scale images with the same gray scale value of all pixel points in the range of gray scale values [0, 255];

[0011] projecting the gray scale images onto a non-reflective standard white background to obtain a set of corresponding actual collected images, and determining the gray scale values of the actual collected images;

[0012] establishing an input-output response curve based on the gray scale image and the gray scale value of the corresponding actual acquisition image;

[0013] determining the gray scale response range based on the input-output response curve.

[0014] Further, the method further comprises:

[0015] determining the gray scale value of the actual acquisition image by determining the effective projection area of the actual acquisition image and obtaining the mean value of the gray scale values of all pixel points as the gray scale value of the actual acquisition image.

[0016] Further, the method further comprises:

[0017] obtaining the gray scale response range by discarding the interval of the platform effect in the input-output response curve.

[0018] Further, the method further comprises:

[0019] obtaining the Gamma correction model by inversely processing the gray scale value relationship between the input gray scale image and the output actual acquisition image, solving the mathematical relationship from the output actual acquisition image to the input gray scale image, and obtaining the Gamma correction model.

[0020] Further, the method further comprises:

[0021] determining the objective function according to the Gamma correction model;

[0022] determining the fitness function of the genetic algorithm according to the objective function;

[0023] fitting and solving the Gamma correction model based on the constructed fitness function and the genetic algorithm.

[0024] Further, the objective function is:

[0025]

[0026] wherein, I p is the gray scale value of the input gray scale image; is the predicted value, which can be expressed as:

[0027]

[0028] wherein, is the predicted value obtained by decoding the genetic algorithm.

[0029] According to a second aspect of the present application, a Gamma correction system based on structured light three-dimensional measurement is provided, comprising:

[0030] The first main module is used for determining a gray response range of the three-dimensional measurement system.

[0031] The second main module is used for establishing a Gamma correction model representing a relationship between an actual collected image and an input gray image in the gray response range.

[0032] The third main module is used for solving the Gamma correction model based on a genetic algorithm fitting.

[0033] The fourth main module is used for pre-coding correction on a to-be-projected fringe image according to the solved Gamma correction model, projecting the pre-coding corrected fringe image to a surface of a to-be-measured object, and realizing three-dimensional measurement.

[0034] According to a third aspect of the present application, an electronic device is provided, comprising a processor and a memory, the processor and the memory being connected to each other.

[0035] The memory is used for storing a computer program.

[0036] The processor is configured to execute the Gamma correction method based on structured light three-dimensional measurement when the computer program is invoked.

[0037] According to a fourth aspect of the present application, a computer readable storage medium is provided, the computer readable storage medium storing a computer program, the computer program being executed by a processor to implement the Gamma correction method based on structured light three-dimensional measurement.

[0038] Overall, compared with the prior art, the above technical solutions conceived by the present application can achieve the following beneficial effects:

[0039] 1. The Gamma correction method based on structured light three-dimensional measurement of the present application adopts a Gamma distortion active correction method, which only needs to collect a series of gray images during system calibration to determine the Gamma correction model and parameters, and directly changes the projected fringe image, compared with other passive error compensation methods, greatly reduces the calculation amount of unpacking operation, and has a wider application range.

[0040] 2. The Gamma correction method based on structured light three-dimensional measurement of the present application uses the Gamma correction model determined by reverse thinking, which is more flexible, and also avoids the problem that the inverse function is not unique, so that the robustness of the correction method is stronger.

[0041] 3. The Gamma correction method based on structured light three-dimensional measurement of the present application, which adopts genetic algorithm optimization when solving Gamma correction model parameters, effectively reduces the probability of occurrence of local optimal solution, is more adaptable, and improves correction accuracy and measurement accuracy. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 A schematic diagram of a structured light three-dimensional measurement system of an embodiment of the present application;

[0043] Figure 2 A flowchart of a Gamma correction method based on structured light three-dimensional measurement of an embodiment of the present application;

[0044] Figure 3 A structured light system input-output response curve diagram of an embodiment of the present application;

[0045] Figure 4 An electronic device of an embodiment of the present application. DETAILED DESCRIPTION

[0046] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application. In addition, the technical features involved in each embodiment of the present application described below can be combined with each other as long as they do not conflict with each other.

[0047] In the description of the present application, unless otherwise explicitly specified and limited, the terms "connected", "connected", "fixed" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0048] Those skilled in the art can understand that, unless specifically stated, the singular form "one", "said" and "the" used herein also includes the plural form. It should be further understood that the phrase "comprising" used in the specification of the present application means that the features, integers, steps, operations, elements and / or components exist, but does not exclude the existence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0049] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as in the embodiments of this application.

[0050] The Gamma correction method based on structured light 3D measurement of the present invention can be applied to fields such as computer vision, 3D image acquisition, and image enhancement, and solves the phase error problem caused by nonlinear response in structured light 3D measurement systems.

[0051] The 3D measurement system is fundamental for acquiring 3D data. It comprises hardware and software components. The hardware includes a camera and projector, which, under the control of a host computer, projects and acquires images and transmits the acquired data back to the host computer. The software is used for receiving image data, phase correction, phase matching, 3D reconstruction, etc., to achieve 3D measurement. Figure 1 The diagram shown is a schematic diagram of a structured light three-dimensional measurement system according to an embodiment of the present invention.

[0052] like Figure 2 As shown, this embodiment of the invention provides a Gamma correction method based on structured light three-dimensional measurement, specifically including steps S100 to S400.

[0053] Step S100: Determine the grayscale response range of the three-dimensional measurement system;

[0054] Specifically, step S100 includes steps S101 to S104.

[0055] Step S101: Generate a series of grayscale images with the same grayscale value for all pixels within the grayscale value range [0, 255].

[0056] Specifically, in an embodiment of the present invention, a series of grayscale images are generated using a computer, with grayscale values ​​ranging from [0, 255], and all pixels in each image have the same grayscale value.

[0057] Step S102: Project the grayscale image onto a non-reflective standard white background, capture a set of corresponding actual acquired images, and determine the grayscale value of the actual acquired images;

[0058] The grayscale images are projected onto a non-reflective standard white flat plate using the projector of the 3D measurement system, and the corresponding images are captured by a camera. Based on this, all grayscale images and their corresponding actual acquired images can be obtained.

[0059] There are areas not covered by the projection image on the actually captured image, and the effective projection area of the gray image is selected. The mean value of the gray values of all pixel points is determined as the gray value of the actually captured image.

[0060] Step S103, establishing an input-output response curve based on the gray value of the gray image and the gray value of the corresponding actually captured image.

[0061] As shown in Figure 3 , the input-output response curve of the system is drawn based on the gray value of the gray image and the output gray value actually captured.

[0062] Step S104, determining the gray response range based on the input-output response curve.

[0063] When the gray value generated by the computer is too small or too large, the output changes little with the input, and there is a platform effect, so this part is discarded, and thus the remaining part can be determined as the gray response range of the system, and the gray value of the image in the subsequent steps must be limited in this range, as shown in Figure 3 The input-output response curve diagram of the structured light system of an embodiment of the present application is shown.

[0064] Step S200, establishing a Gamma correction model representing the relationship between the output actually captured image and the input gray image of the three-dimensional measurement system in the gray response range;

[0065] In the ideal case without Gamma distortion, the output fringe image distribution satisfies f(I n )=I n . However, in the actual process, the measurement system has a Gamma nonlinear error, and under this error, the output fringe image distribution can be expressed as:

[0066] f(I n )=(I n ) γ

[0067] Wherein, γ is the Gamma value of the system.

[0068] Considering the factors of Gamma distortion, environmental light source interference, lens influence, etc., the output gray value is selected to be expressed as a polynomial approximation:

[0069]

[0070] Wherein, I p is the gray value of the input projector gray image, and I c is the output gray value actually captured by the camera, and both are normalized gray values.

[0071] According to several groups of input-output corresponding relations in the gray response range, a function f is fitted, and its inverse function f is further obtained -1 The inverse function f -1 is applied to the ideal fringe image to be input, so that the final output image is ensured

[0072] I c = f(f -1 (I p )) = I p

[0073] Thus, the output and input image gray values maintain a linear relationship. However, the above method may not be unique when solving the inverse function f -1 , thereby causing errors in the subsequent correction process.

[0074] To solve the above problem, in the embodiment of the present application, the input-output relationship is processed in reverse, and the mathematical relationship from output to input is solved, that is, the process of solving the inverse function is avoided, and the expression of the mathematical relationship is assumed as:

[0075]

[0076] The Gamma correction model is the corresponding relationship f() between the input gray value I p and the output gray value I c , and a~f is the coefficient to be solved.

[0077] The method of the present application uses the Gamma correction model determined by reverse thinking, which is not limited to the traditional Gamma exponential model, is more flexible, avoids the problem of non-unique solution of inverse function, and makes the robustness of the correction method stronger.

[0078] Step S300, fitting and solving the Gamma correction model based on the genetic algorithm;

[0079] Specifically, step S300 includes steps S301-S303.

[0080] Step S301, determining a target function according to the Gamma correction model;

[0081] In the embodiment of the present application, the Gamma correction model is represented as:

[0082]

[0083] Then the target function is:

[0084]

[0085] Wherein, is a predicted value, which can be represented as:

[0086]

[0087] wherein, is the predicted value obtained by decoding the genetic algorithm.

[0088] Step S302, determining the fitness function of the genetic algorithm according to the objective function;

[0089] Specifically, when solving by using the genetic algorithm optimization, the smaller the objective function value is, the better, and therefore, the derivative of the objective function is used as the fitness function.

[0090] Step S303, fitting and solving the Gamma correction model based on the constructed fitness function and the genetic algorithm.

[0091] In the embodiments of the present application, a~f are the parameters to be optimized, and For the parameters to be optimized a~f, it satisfies

[0092] Design the fitness function. The fitness function is the most critical part in the genetic algorithm, which is used to evaluate the performance of each individual. Usually it reflects the value of the objective function, and the better the individual, the higher the fitness value.

[0093] The genetic algorithm fitting and solving the Gamma correction model includes:

[0094] Initialize the population: create an initial population within the determined parameter range and fitness function; usually this is a random process, such as simulating the creation of genes or chromosomes;

[0095] Evolution of the population: in each generation, use algorithms such as mutation, pairing and selection to manipulate the population to promote evolution; for example, through crossover (Crossover) and mutation (Mutation) operations, a new generation of population is generated;

[0096] Determine the termination condition, the genetic algorithm will continue to evolve the population until the predetermined termination condition is reached, such as the maximum number of iterations, the fitness no longer changes after a fixed number of times, etc.

[0097] Decode the final solution: when the algorithm stops, select the best solution.

[0098] Substitute a~f obtained by solving into Get the final Gamma correction model f().

[0099] When solving the parameters of the Gamma correction model, the genetic algorithm optimization is used, which effectively reduces the probability of occurrence of local optimal solution, has better adaptability, and improves the correction accuracy and measurement accuracy.

[0100] Step S400, pre-encoding correction is performed on the fringe image to be projected according to the Gamma correction model obtained by solving, the pre-encoding corrected fringe image is projected onto the surface of the object to be measured, and three-dimensional measurement is realized.

[0101] According to the Gamma correction model obtained by solving, pre-encoding correction is performed on the fringe image to be projected, specifically:

[0102] In the structured light measurement system, the gray value of the projected ideal fringe can be expressed as:

[0103] I n =I a +I b cos(φ+2nπ / N)

[0104] In the formula, I n is the gray distribution of the nth fringe image (n=1, 2, …, N), N is the number of phase shift steps; I a is the background light intensity, I b is the amplitude modulation parameter, and φ is the phase value.

[0105] According to the Gamma correction model f() obtained by solving, pre-encoding I n ' = f(I n ) is performed on the projected fringe image.

[0106] It should be noted that the pre-encoding corrected fringe image is projected onto the surface of the object to be measured to realize three-dimensional measurement, which is a prior art and not the core of the present application, and will not be described here.

[0107] The camera parameter calibration process is a conventional means, and will not be described here.

[0108] The embodiment of the present application also provides a Gamma correction system based on structured light three-dimensional measurement, which is used to realize the Gamma correction method based on structured light three-dimensional measurement of the embodiment of the present application, and the Gamma correction system based on structured light three-dimensional measurement comprises:

[0109] A first main module determines the gray response range of the three-dimensional measurement system;

[0110] A second main module establishes a Gamma correction model representing the relationship between the output actual collected image and the input gray image of the three-dimensional measurement system within the gray response range;

[0111] A third main module fits and solves the Gamma correction model based on a genetic algorithm;

[0112] The fourth main module pre-encodes and corrects the fringe image to be projected according to the solved Gamma correction model, projects the pre-encoded and corrected fringe image to the surface of the object to be measured, and realizes three-dimensional measurement.

[0113] It should be noted that the Gamma correction system based on structured light three-dimensional measurement provided in the embodiment can also be a computer program (including program code) running in a computer device. For example, the Gamma correction system based on structured light three-dimensional measurement is an application program, which can be used to execute corresponding steps in the above method provided in the embodiment.

[0114] In some possible implementation manners, the Gamma correction system based on structured light three-dimensional measurement provided in the embodiment can be implemented in a combination of software and hardware. For example, the control system provided in the embodiment can be a processor in the form of a hardware decoding processor, which is programmed to execute the Gamma correction method based on structured light three-dimensional measurement provided in the embodiment. For example, the processor in the form of a hardware decoding processor can use one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), or other electronic elements.

[0115] In some possible implementation manners, the Gamma correction system based on structured light three-dimensional measurement provided in the embodiment can be implemented in a software manner. The Gamma correction system based on structured light three-dimensional measurement can be software in the form of a program and a plug-in, and include a series of modules.

[0116] The Gamma correction system based on structured light three-dimensional measurement provided in the embodiment determines a gray response range of a three-dimensional measurement system; establishes a Gamma correction model representing a relationship between an actual collected image output by the three-dimensional measurement system and a gray value of an input gray image in the gray response range; solves the Gamma correction model based on a genetic algorithm; pre-encodes and corrects a fringe image to be projected according to the solved Gamma correction model, projects the pre-encoded and corrected fringe image to the surface of the object to be measured, and realizes three-dimensional measurement.

[0117] The embodiment also provides an electronic device, Figure 4 is a structural schematic diagram of the electronic device of the embodiment, likeFigure 4 As shown, the electronic device 1000 in the embodiment can include a processor 1001, a network interface 1004 and a memory 1005, and in addition, the electronic device 1000 can further include a user interface 1003 and at least one communication bus 1002. The communication bus 1002 is used to realize the connection communication between the components. The user interface 1003 can include a display, a keyboard, and the optional user interface 1003 can further include a standard wired interface, a wireless interface. The network interface 1004 can optionally include a standard wired interface, a wireless interface (such as a WI-FI interface). The memory 1004 can be a high-speed RAM memory, or a non-volatile memory, for example, at least one disk storage. The memory 1005 can also be at least one storage device located away from the aforementioned processor 1001. For example Figure 4 As shown, the memory 1005 as a computer readable storage medium can include an operating system, a network communication module, a user interface module and a device control application.

[0118] As shown in the electronic device 1000, the network interface 1004 can provide network communication functions; the user interface 1003 is mainly used to provide an input interface for the user; and the processor 1001 can be used to call the device control application stored in the memory 1005 to realize: Figure 4

[0119] It should be understood that in some possible embodiments, the aforementioned processor 1001 can be a central processing unit (CPU), and the processor can also be other general-purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The memory can include read-only memory and random access memory, and provide instructions and data for the processor. A part of the memory can also include a non-volatile random access memory. For example, the memory can also store device type information.

[0120] It should be understood that in some possible embodiments, the aforementioned processor 1001 can be a central processing unit (CPU), and the processor can also be other general-purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The memory can include read-only memory and random access memory, and provide instructions and data for the processor. A part of the memory can also include a non-volatile random access memory. For example, the memory can also store device type information. ​

[0121] In a particular implementation, the electronic device 1000 can perform the implementation manners provided by the above steps through various functional modules built therein, and the implementation manners provided by the above steps can be referred to specifically, and will not be repeated here. Figure 2

[0122] The electronic device provided in the embodiment determines a gray response range of a three-dimensional measurement system; within the gray response range, a Gamma correction model representing a relationship between an actual collected image output by the three-dimensional measurement system and a gray value of an input gray image is established; the Gamma correction model is solved based on a genetic algorithm; a to-be-projected fringe image is pre-encoded and corrected according to the solved Gamma correction model; the pre-encoded and corrected fringe image is projected onto a surface of a to-be-measured object, and three-dimensional measurement is implemented.

[0123] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method provided by the above steps, and the implementation manners provided by the above steps can be referred to specifically, and will not be repeated here. Figure 2

[0124] The computer storage medium determines a gray response range of a three-dimensional measurement system; within the gray response range, a Gamma correction model representing a relationship between an actual collected image output by the three-dimensional measurement system and a gray value of an input gray image is established; the Gamma correction model is solved based on a genetic algorithm; a to-be-projected fringe image is pre-encoded and corrected according to the solved Gamma correction model; the pre-encoded and corrected fringe image is projected onto a surface of a to-be-measured object, and three-dimensional measurement is implemented.

[0125] It should be understood that, although each step in the flowchart of the accompanying drawings is displayed in sequence according to the indication of the arrow, these steps are not necessarily executed in sequence according to the indication of the arrow. Unless explicitly stated herein, the execution of these steps is not strictly limited in sequence, and they can be executed in other sequences. Moreover, at least part of the steps in the flowchart of the accompanying drawings can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or sub-steps or stages of other steps.

[0126] Those skilled in the art can easily understand that the above description is only the preferred embodiment of the present application, and is not intended to limit the present application, and any modification, equivalent replacement and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.​​

Claims

1. A method for gamma correction based on structured light three-dimensional measurement, characterized in that, The method comprises the steps of: determining a gray response range of a three-dimensional measurement system; establishing a Gamma correction model representing a relationship between a gray value of an input gray image and an output actual captured image of the three-dimensional measurement system within the gray response range; solving the Gamma correction model based on a genetic algorithm; pre-coding a projected fringe image according to the solved Gamma correction model, and projecting the pre-coded fringe image onto a surface of an object to be measured to realize three-dimensional measurement. The step of establishing the Gamma correction model representing the relationship between the gray value of the input gray image and the output actual captured image within the gray response range comprises the steps of: performing reverse processing on the relationship between the gray values of the input gray image and the output actual captured image to solve a mathematical relationship from the output actual captured image to the input gray image, and obtaining the Gamma correction model. The step of solving the Gamma correction model based on the genetic algorithm comprises the steps of: determining a target function according to the Gamma correction model; determining a fitness function of the genetic algorithm according to the target function; and solving the Gamma correction model based on the constructed fitness function and the genetic algorithm.

2. The method according to claim 1, wherein, The step of determining the gray response range of the three-dimensional measurement system comprises the steps of: generating a series of gray images with all pixel points having the same gray value within a range [0, 255] of gray values; projecting the gray images onto a non-reflective standard white background to obtain a group of corresponding actual captured images, and determining gray values of the actual captured images; establishing an input-output response curve based on the gray values of the gray images and the corresponding actual captured images; and determining the gray response range based on the input-output response curve.

3. The method according to claim 2, wherein, The step of determining the gray values of the actual captured images comprises the steps of: determining an effective projection area of the actual captured images, and obtaining a mean value of the gray values of all pixel points as the gray value of the actual captured images.

4. The method according to claim 2, wherein, The step of determining the gray response range based on the input-output response curve comprises the step of: obtaining the gray response range by removing a platform effect interval of the input-output response curve.

5. The method of claim 1, wherein the method further comprises: The target function is: where I p is the input gray scale image; is the predicted value, which can be represented as: wherein, is the predicted value obtained by the genetic algorithm decoding.

6. A gamma correction system based on structured light three-dimensional measurement, characterized by, The method comprises the steps of: a first main module for determining a gray response range of a three-dimensional measurement system; a second main module for establishing a Gamma correction model representing a relationship between a gray value of an input gray image and an output actual captured image of the three-dimensional measurement system within the gray response range; the step of establishing the Gamma correction model representing the relationship between the gray value of the input gray image and the output actual captured image within the gray response range comprises the steps of: performing reverse processing on the relationship between the gray values of the input gray image and the output actual captured image to solve a mathematical relationship from the output actual captured image to the input gray image, and obtaining the Gamma correction model; a third main module for solving the Gamma correction model based on a genetic algorithm; the step of solving the Gamma correction model based on the genetic algorithm comprises the steps of: determining a target function according to the Gamma correction model; determining a fitness function of the genetic algorithm according to the target function; and solving the Gamma correction model based on the constructed fitness function and the genetic algorithm. A fourth main module is configured to perform pre-encoding correction on the fringe image to be projected according to the Gamma correction model obtained by solving, and project the pre-encoding corrected fringe image onto the surface of the object to be measured to realize three-dimensional measurement.

7. An electronic device, comprising: The device comprises a processor and a memory, and the processor and the memory are connected to each other; The memory is configured to store a computer program; The processor is configured to execute the Gamma correction method for three-dimensional measurement based on structured light according to any one of claims 1 to 5 when the computer program is invoked.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the Gamma correction method for three-dimensional measurement based on structured light according to any one of claims 1 to 5.

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