CN115479556A - A binary defocus three-dimensional measurement method and device for subtracting the mean value of phase error - Google Patents

Abstract

The invention relates to the field of optical three-dimensional measurement, in particular to a binary defocusing three-dimensional measurement method and device for reducing a phase error mean value. Firstly, carrying out binary coding on a sine stripe image by adopting an error diffusion algorithm to obtain a coding stripe group; then, calculating to obtain a phase error mean value; the coding fringe group is projected to the position of an object to be measured in an out-of-focus mode, fringe images returned by the object to be measured are collected, and a measuring phase is obtained by adopting the multi-step phase shift method; and subtracting the phase error mean value from the measured phase to obtain an actual phase, and reconstructing through a phase diagram to obtain the three-dimensional data of the object to be measured. The invention reduces the root mean square error of the final phase result by subtracting the phase error mean value from the original phase result, thereby effectively improving the final measurement precision and effectively improving the accuracy of the detection result of the invention.

Description

A binary defocus three-dimensional measurement method and device for subtracting the mean value of phase error

technical field

The invention relates to the field of optical three-dimensional measurement, in particular to a method and device for binary defocus three-dimensional measurement by subtracting the mean value of phase error.

Background technique

Three-dimensional measurement based on striped structured light is a non-contact measurement method, which has many advantages, such as high precision and high speed. It is widely used in automatic processing, high-speed online detection, aerospace, physical profiling and other fields.

Usually, commercial digital optical projectors have certain nonlinear problems, which will lead to large errors in the final three-dimensional measurement results. In order to solve this problem, many methods have been proposed in the industry, among which binary defocus technology is A commonly used method to overcome the nonlinearity of projectors. This type of method usually first performs binary encoding on the standard sinusoidal fringe image (that is, uses 0 and 1 to represent each pixel value of the image), and then projects a fringe image close to the standard sine through defocus projection for subsequent Striped structured light measurement. In addition to solving the non-linear problem of the projector, the binary defocus technology can also make full use of the characteristics of the digital projector to increase the speed of fringe projection, and then improve the speed of three-dimensional measurement.

However, due to the phase error between the fringe after defocus projection and the standard sinusoidal fringe of binary defocus technology, and then after phase reconstruction, it will lead to a large error in the three-dimensional measurement results. Therefore, there is a need for a three-dimensional measurement method for out-of-focus projection that can reduce the phase error between the out-of-focus projected fringes and the standard sinusoidal fringes, thereby reducing the error in three-dimensional measurement.

Contents of the invention

The purpose of the present invention is to overcome the problem in the prior art that the large phase error between the defocused projected fringe and the standard sinusoidal fringe leads to a large error in the three-dimensional measurement result, and to provide a binary method for subtracting the mean value of the phase error Three-dimensional out-of-focus measurement method and device.

In order to realize the above-mentioned purpose of the invention, the present invention provides the following technical solutions:

A binary defocus three-dimensional measurement method for subtracting phase error mean, comprising the following steps:

S1: Use the error diffusion algorithm to binary code the sinusoidal fringe image to obtain the coded fringe group;

S2: performing Gaussian blur on the coded stripe group, using a multi-step phase shift method to obtain a predicted phase, and making a difference between the predicted phase and the ideal phase, and calculating the average value of the phase errors of all pixels to obtain the average value of the phase error; The ideal phase is the phase calculated by the multi-step phase shift method for the sinusoidal fringe image;

S3: defocusing the coded fringe group to the object to be measured, collecting the fringe image returned by the object to be measured, and obtaining the measurement phase by using the multi-step phase shift method;

S4: Subtracting the average value of the phase error from the measured phase to obtain an actual phase, then obtaining an unfolded phase through spatial phase unfolding, and finally reconstructing the three-dimensional data of the object to be measured through unfolding a phase map. The present invention reduces the root mean square error of the final phase result by subtracting the mean value of the phase error from the original phase result, thereby effectively improving the final measurement accuracy and the accuracy of the detection result of the present invention.

As a preferred solution of the present invention, the step S2 and the step S3 can be executed at the same time or the order of execution can be exchanged.

As a preferred solution of the present invention, the formula for calculating the phase using the multi-step phase shift method is:

Among them, N represents the number of steps of multi-step phase shift, (x, y) is the pixel coordinate, I _n (x, y) is the pixel value of (x, y), φ(x, y) is the value of (x, y) phase value.

As a preferred solution of the present invention, the formula for calculating the mean value of the phase error is:

Wherein M represents the number of pixels, (x, y) is the pixel coordinates, φ _bi (x, y) is the predicted phase calculated by the encoded stripe group after Gaussian blur, and φ _ideal (x, y) is the sine The ideal phase calculated from the fringe image, Mean is the mean value of the phase error.

As a preferred solution of the present invention, computer simulation is used to perform Gaussian blur in the step S2 to simulate the defocus effect.

As a preferred solution of the present invention, the step S3 uses a digital projector for out-of-focus projection.

A three-dimensional measurement device, comprising at least one processor, at least one projection device for performing focal projection, at least one acquisition camera for collecting returned images of an object to be measured, and a memory connected in communication with the at least one processor; the projection device And the collection camera is respectively connected to the processor in communication; the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can Perform any of the methods described above.

Compared with prior art, the beneficial effect of the present invention:

The present invention reduces the root mean square error of the final phase result by subtracting the mean value of the phase error from the original phase result, thereby effectively improving the final measurement accuracy and the accuracy of the detection result of the present invention.

Description of drawings

FIG. 1 is a schematic flow chart of a binary defocus three-dimensional measurement method for subtracting the mean value of the phase error described in Embodiment 1 of the present invention;

FIG. 2 is a schematic diagram of a coded fringe group generated in step S1 in a binary defocus three-dimensional measurement method for subtracting the mean value of phase error described in Embodiment 2 of the present invention;

Fig. 3 is a fringe diagram of the simulated defocus projection generated in step S2 in a binary defocus three-dimensional measurement method for subtracting the mean value of the phase error described in Embodiment 2 of the present invention;

Fig. 4 is a fringe pattern actually taken in step S3 in a binary defocus three-dimensional measurement method for subtracting the mean value of the phase error described in Embodiment 2 of the present invention;

Fig. 5 shows the phase results obtained by the implementation method of the present invention and the traditional method under the conditions of small defocus amount and different fringe periods in a binary defocus three-dimensional measurement method of subtracting the mean value of the phase error described in Embodiment 2 of the present invention comparison chart;

FIG. 6 is a schematic structural diagram of a three-dimensional measurement device according to Embodiment 3 of the present invention, which utilizes the binary defocus three-dimensional measurement method described in Embodiment 1 by subtracting the mean value of the phase error.

detailed description

The present invention will be further described in detail below in conjunction with test examples and specific embodiments. However, it should not be understood that the scope of the above subject matter of the present invention is limited to the following embodiments, and all technologies realized based on the content of the present invention belong to the scope of the present invention.

Among the sinusoidal fringe binary coding methods proposed by many scholars, the "error diffusion algorithm" is a commonly used and effective sinusoidal fringe binary coding method. Its basic idea is to weight the quantization error of the processed elements to the unprocessed elements, thereby reducing the quantization error of the entire coding surface.

After careful study, it is found that after binary encoding of a certain sinusoidal fringe pattern by using the error diffusion algorithm of a certain error diffusion kernel, the defocus projection is performed under different defocus amounts, and any multi-step phase shift is adopted The phase is calculated by the method, and the final obtained phase errors all have the same mean value.

The evaluation index of phase error in the industry generally adopts the root mean square error (RMS), and its expression is as follows:

Further, it can be found that the root mean square error can be expressed by the variance of the error and the mean value of the error, as follows:

Among them, V is the variance of the error, and E is the mean value of the error.

It can be clearly seen that if the influence of the error mean value on the root mean square error (RMS) is subtracted, the final root mean square error value (RMS) can be reduced in this way.

Therefore, combined with our research findings, we can calculate the corresponding mean value of the phase error through computer simulation in advance, and then subtract the mean value of the phase error from the actually measured phase result to reduce the final phase mean square Root error value (RMS).

However, an important condition for the establishment of this technical solution is that the change of the defocus amount will not affect the mean value of the finally acquired phase error. Here, the present invention particularly uses mathematical analysis to prove that the change of the defocus amount will not affect the mean value of the finally obtained phase error.

和条纹的强度误差ΔA_n有如下关系：When using the four-step phase shift method, the phase error of the fringe

It has the following relationship with the intensity error ΔA _n of the stripes:

为第n帧图的强度误差，n∈[0,3]，

为相位，B为所述条纹图像中条纹的调制度。in,

is the intensity error of the nth frame image, n∈[0,3],

is the phase, and B is the modulation degree of the fringe in the fringe image.

Assuming that the Gaussian kernel g represents a certain amount of defocus and acts on the projected fringe pattern, then both ΔA _n and B will change:

B'=t ₁ B

表示离焦后的第n帧的强度误差，*表示卷积运算符，t₁表示在高斯核g作用下，标准正弦函数的调制度会有一个固定系数的变化。in,

Indicates the intensity error of the nth frame after defocusing, * indicates the convolution operator, and t ₁ indicates that under the action of the Gaussian kernel g, the modulation degree of the standard sine function will have a fixed coefficient change.

Therefore, the phase error of the changed fringes can be expressed as:

Due to the symmetric nature of the Gaussian kernel, it is possible to have:

Therefore, the mean value of the phase error can be derived as follows:

So obviously there is:

Therefore, the change of the defocus amount will not affect the average value of the phase error obtained last. As shown in Table 1, when the fringe period is 60 pixels, the average value of the phase error obtained by different defocus amounts is basically unchanged (that is, 0.0228±0.0003, and the error is less than 0.0003, which can be ignored).

Table 1

small defocus Medium defocus large defocus Average value of phase error 0.0227 0.0231 0.0225

Example 1

As shown in Figure 1, a binary defocus three-dimensional measurement method for subtracting the mean value of the phase error comprises the following steps:

S1: Use the error diffusion algorithm to binary code the sinusoidal fringe image to obtain the coded fringe group;

S2: Perform Gaussian blur on the coded fringe group, use a multi-step phase shift method to obtain a predicted phase, and make a difference between the predicted phase and the ideal phase to obtain the average value of the phase error; the ideal phase is the sinusoidal fringe image The phase calculated by the multi-step phase shift method;

S3: defocusing the coded fringe group to the object to be measured, collecting the fringe image returned by the object to be measured, and obtaining the measurement phase by using the multi-step phase shift method;

S4: Subtracting the average value of the phase error from the measured phase to obtain an actual phase, then obtaining an unfolded phase through spatial phase unfolding, and finally reconstructing the three-dimensional data of the object to be measured through unfolding a phase map.

Wherein, step S2 and step S3 may be executed in exchange order or executed simultaneously.

The formula for calculating the phase using the multi-step phase shift method is:

Among them, N represents the step number of multi-step phase shift, (x, y) is the pixel coordinate, I _n (x, y) is the pixel value of (x, y), φ (x, y) is (x, y) phase value.

The formula for calculating the mean value of the phase error is:

Wherein M represents the number of pixels, φ _bi (x, y) is the predicted phase calculated by the encoded fringe group after Gaussian blur, and φ _ideal (x, y) is the ideal phase calculated by the sinusoidal fringe image, Mean is the mean value of the phase error.

Example 2

S1: Use the Floyd-Steinberg error diffusion algorithm to perform binary encoding on the sinusoidal fringe pattern with a resolution of 912*1140 and a period of 60 pixels to obtain a coded fringe group, as shown in Figure 2.

S2: Using computer simulation, use a Gaussian kernel with a window size of 9*9 and a standard deviation of 3 to perform Gaussian blur on the binarized fringe image generated in step S1 to simulate defocused projection, and use the four-step phase shift method to calculate The predicted phase is compared with the ideal phase to calculate the average value of the phase error, and the average value of the phase error is 0.0207. Figure 3 shows the fringe pattern of the simulated out-of-focus projection.

S3: Utilize a digital projector to defocus project the coded fringe group generated in step S1 to the object to be measured, collect the fringe image returned by the object to be measured, and use a four-step phase shift method to measure the corresponding phase result, and then Subtract the phase error mean value calculated in step S2 from the phase result to obtain a final more accurate phase result. The phase result error RMS is reduced from 0.035 to 0.027. Figure 4 shows the actual fringe image taken.

S4: Subtract the mean value of the phase error from the measured phase to obtain the actual phase, and then obtain the unfolded phase through spatial phase unfolding, use the system parameters calibrated in advance, and finally obtain the three-dimensional image of the object to be measured by reconstructing the unfolded phase map data.

The system parameters calibrated in advance here are obtained through the calibration process of the monocular structured light system. These parameters include the internal reference matrix Kc of the camera and the internal reference matrix Kp of the projector, as well as the external parameter matrix between the camera and the projector: the rotation matrix R and the translation matrix T. And the distortion coefficients dc and dp of the camera and projector.

Figure 5 is a comparison of the phase results obtained by the patented method and the traditional method under the conditions of small defocus and different fringe periods (mean subtraction and no mean subtraction). From the results, it can be seen that the patented method can effectively reduce the root mean square error (RMS) of the phase error compared with the traditional method.

Example 3

As shown in FIG. 6, a three-dimensional measurement device includes at least one processor, at least one projection device for performing focal projection, at least one collection camera for collecting returned images of the object to be measured, and a communication device connected to the at least one processor. memory; the projection device and the acquisition camera are respectively connected in communication with the processor; the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor, so that all The at least one processor is capable of executing the binary defocus three-dimensional measurement method of subtracting the mean value of the phase error described in the foregoing embodiments. The input and output interfaces may include a display, a keyboard, a mouse, and a USB interface for inputting and outputting data; the power supply is used for providing electric energy for the three-dimensional measuring device.

Those skilled in the art can understand that all or part of the steps for implementing the above-mentioned method embodiments can be completed by hardware related to program instructions, and the aforementioned programs can be stored in computer-readable storage media. The steps of the method embodiment; and the foregoing storage medium includes: a removable storage device, a read only memory (Read Only Memory, ROM), a magnetic disk or an optical disk, and other various media that can store program codes.

When the above-mentioned integrated units of the present invention are realized in the form of software function units and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention can be embodied in the form of software products in essence or the part that contributes to the prior art. The computer software products are stored in a storage medium and include several instructions for Make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the methods described in various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program codes such as removable storage devices, ROMs, magnetic disks or optical disks.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention should be included in the protection of the present invention. within range.

Claims (7)

1. A binary out-of-focus three-dimensional measurement method for subtracting a phase error mean value is characterized by comprising the following steps:

s1: carrying out binary coding on the sinusoidal fringe image by adopting an error diffusion algorithm to obtain a coding fringe group;

s2: carrying out Gaussian blur on the coding stripe group, obtaining a predicted phase by adopting a multi-step phase shift method, carrying out difference on the predicted phase and an ideal phase, and calculating the average value of phase errors of all pixels to obtain a phase error average value; the ideal phase is calculated by the multi-step phase shift method on the sine stripe image;

s3: the coding fringe group is projected to the position of an object to be measured in an out-of-focus mode, fringe images returned by the object to be measured are collected, and a measuring phase is obtained by adopting the multi-step phase shift method;

s4: and subtracting the phase error mean value from the measured phase to obtain an actual phase, then obtaining an unfolded phase through space phase unfolding, and finally obtaining three-dimensional data of the object to be measured through unfolding phase diagram reconstruction.

2. The method for binary defocus three-dimensional measurement of phase error mean value according to claim 1, wherein the steps S2 and S3 can be executed simultaneously or in an alternative order.

3. The method for binary defocus three-dimensional measurement of the mean value of the phase error according to claim 1, wherein the calculation formula for calculating the phase by adopting the multi-step phase shift method is as follows:

where N represents the number of steps in the multi-step phase shift, (x, y) is the pixel coordinate, I _n (x, y) is the pixel value of (x, y), and φ (x, y) is the phase value of (x, y).

4. The method for binary out-of-focus three-dimensional measurement of phase error mean value according to claim 1, wherein the phase error mean value is calculated by the following formula:

where M represents the number of pixels and (x, y) is the pixel coordinate, phi _bi (x, y) is the predicted phase, phi, calculated for the encoded group of stripes after Gaussian blur _ideal (x, y) is an ideal phase calculated by the sine stripe image, and Mean is a phase error Mean value.

5. The method for measuring binary defocus three-dimensional value by subtracting the mean value of phase error according to claim 1, wherein the step S2 is performed by using computer simulation to perform gaussian blur for simulating defocus effect.

6. The phase error mean subtraction binary defocus three-dimensional measurement method according to claim 1, wherein the step S3 adopts a digital projector to perform defocus projection.

7. A three-dimensional measuring device is characterized by comprising at least one processor, at least one projection device for executing focus-departure projection, at least one acquisition camera for acquiring return images of an object to be measured and a memory which is in communication connection with the at least one processor; the projection device and the acquisition camera are respectively in communication connection with the processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 6.

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