WO2019153569A1 - 一种针对条纹投影三维测量***离焦现象的相位误差校正方法 - Google Patents
一种针对条纹投影三维测量***离焦现象的相位误差校正方法 Download PDFInfo
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- WO2019153569A1 WO2019153569A1 PCT/CN2018/087387 CN2018087387W WO2019153569A1 WO 2019153569 A1 WO2019153569 A1 WO 2019153569A1 CN 2018087387 W CN2018087387 W CN 2018087387W WO 2019153569 A1 WO2019153569 A1 WO 2019153569A1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
- G01B11/2504—Calibration devices
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/24—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
- G01B11/25—Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures by projecting a pattern, e.g. one or more lines, moiré fringes on the object
- G01B11/254—Projection of a pattern, viewing through a pattern, e.g. moiré
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- the invention belongs to the field of three-dimensional reconstruction in computer vision, and particularly relates to a phase error correction method for the defocus phenomenon of a stripe projection three-dimensional measurement system.
- FPP fringe projection profilometry
- active light projection technology it is often assumed that an object point on the surface of the object to be tested only directly receives illumination from the sensor of the projection device. This assumption does not hold true in many practical situations.
- an object point on the object may also receive indirect illumination caused by mutual reflection, subsurface scattering and defocusing. If these indirect illuminations are not considered in the FPP system, it may lead to more obvious systematic errors.
- the invention aims to provide a phase error correction method for the defocus phenomenon of a stripe projection three-dimensional measurement system, first analyzing an analytical expression of a phase error caused by camera defocus, and then directly solving the phase error and correcting the phase. method.
- this method has no additional hardware requirements for the measurement system, and it does not need to project additional fringe patterns.
- the correction can be done directly by using the fringe pattern originally affected by the camera's defocusing phenomenon.
- the corrected phase combined with the calibration parameters can obtain high-precision three-dimensional reconstruction results.
- the present invention adopts the following technical solutions:
- a phase error correction method for a defocusing phenomenon of a stripe projection three-dimensional measurement system comprising the following steps:
- step S2 For the fringe pattern acquired in step S1, the background image I' is solved, and then the phase error is solved by the traditional phase shift method. Phase
- step S4 Using the edge image obtained in step S3, recovering the clear background image I s ' of the background image I′ before defocusing;
- step S6 For each pixel to be processed determined in step S5, calculate the phase gradient direction according to the neighborhood average method:
- u and v are the horizontal and vertical indices of the pixel coordinates of the image;
- w is the width of a predetermined square neighborhood;
- ⁇ u and ⁇ v are the phase partial derivatives along the u and v directions, respectively;
- ⁇ (x i , x o ) is the phase difference between the pixels x i and x o , on the premise of the near-neighborhood planarity assumption, Where vector Pointed to x i by x o ; Is the gradient direction of the pixel x o , that is, the step obtained in step S6
- the phase density of the neighborhood where ⁇ is x o that is, the phase difference of adjacent pixels along the phase gradient direction, can be directly obtained in the phase map.
- the range of the neighborhood to be summed is wide. For a square region of 6 ⁇ +1, ⁇ is calculated in step S5.
- the corrected phase information is obtained, and finally, the three-dimensional information of the measuring object can be obtained by combining the calibration information.
- the phase error correction method for the defocusing phenomenon of the stripe projection three-dimensional measurement system the specific operation of projecting the N standard phase-shifted sinusoidal stripe images required on the object using the projector in step S1 is: according to the active light
- the hardware triangle relationship in the projection 3D measurement system fixes the projector and the camera, and places the object with a complex surface texture in an appropriate position.
- the grayscale value of the stripe is set to:
- a and B are the stripe background intensity and the stripe modulation degree coefficient respectively
- ⁇ is the set phase value
- the phase error correction method for the defocusing phenomenon of the stripe projection three-dimensional measurement system is: first adjusting the aperture size, shutter speed and sensitivity of the camera, so that The captured image will not appear image saturation, that is, the grayest value of the brightest area in the image is less than 255. Under this camera parameter, the N fringe pattern is collected. When the camera is out of focus, the stripe gray collected by the camera The degree is:
- x c represents any pixel of the acquired image
- x o is the pixel corresponding to x c corresponding to the projector format
- x i is the neighborhood pixel of x o in the projector format
- T(x i , x o ) is the influence coefficient of pixel x i on x o
- T(x i , x o ) ⁇ G(x i , x o ) ⁇ r i , where ⁇ is the gain of the camera, G(x i , x o )
- the point spread function PSF caused by camera blur, r i is the reflectance coefficient of the object surface point corresponding to x c .
- the phase error correction method for the defocusing phenomenon of the stripe projection three-dimensional measurement system the specific method of restoring the clear background image I s ' before the defocusing of the background image I′ in step S4 is: for each edge pixel Find the local maximum and minimum along the direction of the gray gradient. Since the maximum and minimum values are distributed on both sides of the pixel, the gray value of all pixels from the maximum and minimum pixel positions to the edge pixel position is set to the maximum. The value or the minimum value, for each edge pixel to perform such processing, a clear background image I s ' can be obtained.
- the present invention is directed to a conventional fringe projection three-dimensional measuring system, which is easy to cause image blur due to camera depth of field problems, and further causes significant phase error.
- a phase error correction algorithm based on analytical expression is proposed.
- the method proposed in this patent does not rely on any hardware other than the measurement system itself, nor does it rely on projection of high frequency fringes.
- an analytical expression of phase error is established. Then combine the point spread function PSF of each pixel to blur the front background image I s ', phase direction And the phase density ⁇ , accurately solve the magnitude of the phase error, thereby directly correcting the phase solved by the conventional phase shift method.
- the corrected phase combined with the calibration information can obtain the corrected three-dimensional reconstruction result.
- the whole phase correction is based on rigorous mathematical process, and the algorithm implementation process is simple. It is suitable for the case where the depth of the camera is small and the image is often blurred in the traditional stripe projection three-dimensional measurement system. It is also suitable for the case where the measurement object is translucent and subsurface scattering occurs.
- Figure 1 is a flow chart of the entire process of the invention.
- Figure 2 is a frame diagram of a stripe projection three-dimensional measurement system.
- Figure 3 is a schematic diagram of a test object.
- Figure 4 is a schematic diagram of pixel points that need to be processed in this patent.
- Figure 5 is a calculated pre-blur background image.
- Fig. 6 is a schematic diagram showing the calculation result of the blur function PSF.
- Fig. 7 is a schematic diagram of the phase difference ⁇ (x i , x o ).
- Figure 8 is a schematic diagram of phase error calculated using the patent for a test object.
- Figure 9 is a schematic view of an experimental object.
- FIG. 10 is a diagram of a three-dimensional reconstruction result obtained by directly applying a conventional method.
- FIG. 11 is a diagram of a three-dimensional reconstruction result obtained by phase correction after applying the patent algorithm.
- MATLAB is used as a programming tool to process the sinusoidal stripes generated by the computer and the fringe images collected by the CCD camera.
- This example uses a white plane with a black texture as the object to be tested, confirming the validity of the error correction method proposed in this patent. It is understood that the examples are intended to be illustrative only and not to limit the scope of the invention, and the scope of the invention Limited range.
- a phase error correction method for the defocus phenomenon of the stripe projection three-dimensional measurement system the algorithm flow is shown in Figure 1.
- the block diagram of the measurement system is shown in Figure 2.
- Step 1 Fix the projector and camera according to the hardware triangle relationship in the active light projection 3D measurement system, and place the object with complex surface texture in a suitable position. Use the projector to project the required N standard phase-shifted sinusoidal image on the object.
- the grayscale value of the stripe is set to:
- a and B are the stripe background intensity and the stripe modulation degree coefficient respectively
- ⁇ is the set phase value
- Step 2 Set the camera related parameters: aperture size, shutter speed and sensitivity so that the captured image will not be saturated (ie, the grayest value of the brightest area in the image is less than 255).
- the N fringe pattern is acquired under this camera parameter.
- the grayscale value of the stripe captured by the camera is:
- x c represents any pixel of the acquired image
- x o is the pixel corresponding to x c corresponding to the projector format
- x i is the neighborhood pixel of x o in the projector format
- T(x i , x o ) is the influence coefficient of pixel x i on x o
- T(x i , x o ) ⁇ G(x i , x o ) ⁇ r i , where ⁇ is the gain of the camera, G(x i , x o )
- the point spread function PSF caused by camera blur, r i is the reflectance coefficient of the object surface point corresponding to x c .
- Step 3 For the fringe pattern acquired in step 2, the background image I' is solved, as shown in FIG. Then use the traditional phase shift method to solve the phase with phase error ⁇ (x c )
- Step 4 Perform edge extraction on the background image I' obtained in step 3. For each pixel in the image, it is judged whether there is an edge point within 10 pixels of its neighborhood. If not, the pixel is not processed; if so, the pixel is the object to be processed by the patent. 4 is a classification result of the background image I' shown in FIG. 3, in which the all black area (image gray value is 0) is a pixel not processed by the patent; for the non-all black area (image gray value is greater than 0) Each pixel, as there are edge pixels in the neighborhood, is the part to be processed by this patent.
- Step 5 Using the edge image obtained in step 4, the clear background image I s ' of the background image I' before defocusing is restored.
- the specific method is: for each edge pixel, find local maximum and minimum along the gray gradient direction, since the maximum and minimum values are distributed on both sides of the pixel, all from the maximum minimum pixel position to the edge pixel position The gray value of the pixel is set to the maximum or minimum value.
- a clear background image I s ' can be obtained, as shown in FIG. As can be seen from the figure, I s 'better reflects the background image that is not blurred by the camera's defocus.
- Step 6 Calculate the point spread function G caused by camera blur for each edge pixel according to the clear background image I s ' obtained in step 5 by minimizing the image distance as follows, which is described by a single parameter standard deviation ⁇ .
- Figure 6 shows the calculated PSF results. It is worth noting that in order to reduce the complexity of the algorithm, only the PSF of the edge pixels is calculated. The other pixels of the area to be processed have their PSF set to be the same as the nearest edge pixel.
- Step 7 Calculate the phase gradient direction according to the neighborhood average method for each pixel to be processed determined in step 4:
- u and v are the horizontal and vertical indices of the pixel coordinates of the image; w is the width of a predetermined square neighborhood; with They are phase partial derivatives along the u and v directions, respectively.
- the method can obtain the phase gradient direction of each pixel under the influence of camera defocus and random noise with higher precision.
- Step 8 The pre-defocus background image I s ', the point spread function G and the phase gradient direction obtained according to the above steps For each pixel to be processed, calculate the phase error caused by the camera's defocus:
- ⁇ (x i , x o ) is the phase difference between the pixels x i and x o .
- the gradient direction of the pixel x o which is obtained in step 7.
- the phase density of the neighborhood where ⁇ is x o that is, the phase difference of adjacent pixels along the phase gradient direction, can be directly obtained in the phase diagram, and the phase difference diagram is as shown in FIG. 7 .
- the size of the neighborhood in which the summation is performed is a square region having a width of 6 ⁇ +1, and ⁇ is calculated in step 6.
- the phase error of the final solution is shown in Fig. 8. It can be seen that the systematic error caused by camera blur is concentrated at the edge of the image, that is, where the reflectance of the surface of the object changes greatly.
- Step 9 According to the formula Obtain corrected phase information. Finally, combined with the calibration information, three-dimensional information of the measured object can be obtained.
- 9 to 11 are the second set of measured experiments, and FIG. 9 is the target of the object to be tested, and the surface of the object has a textured area with a large jump.
- Fig. 10 and Fig. 11 are the results of the three-dimensional reconstruction measured by the conventional method and the phase error correction by the method, respectively. It can be seen that the correction caused by the defocusing of the camera is significantly reduced by the correction of the patented method. It is worth mentioning that the method proposed in this patent does not need to project additional fringe patterns, but directly performs phase error analysis and correction with the pictures required by the traditional phase shift algorithm. The three-dimensional reconstruction map obtained from the corrected phase information effectively reduces the systematic error caused by the camera's defocus.
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- 一种针对条纹投影三维测量***离焦现象的相位误差校正方法,其特征在于,该方法包括如下步骤:S1.使用投影仪在物体上投射所需的N幅标准相移正弦条纹图像,对N幅条纹图进行采集;S3.对S2中得到的背景图像I'进行边缘提取;S4.用步骤S3中得到的边缘图像,恢复背景图像I'在离焦之前的清晰背景图像I s';S5.根据步骤S4中求得的清晰背景图像I s',通过最小化如下图像距离来计算每一个边缘像素由相机模糊引起的点扩散函数G,由单参数标准差σ描述,d=||I'-I s'*G|| 2;S6.对于步骤S5中确定的每一个待处理的像素,跟据邻域平均法计算相位梯度方向:其中,u和v为图像像素坐标的横向和纵向索引;w为一个预设的正方形邻域的宽;φ u和φ v分别为沿u和v方向的相位偏导数;其中Δ(x i,x o)是像素x i与x o之间的相位差,在近邻域平面性假设的前提下, 其中向量 由x o指向x i; 为像素点x o的梯度方向,即步骤S6中求得的 ρ为x o的邻域的相位密度,即相邻像素沿着相位梯度方向的相位差值,可直接在相位图中获取,在计算相位误差时,进行求和的邻域的大小范围为宽为6σ+1的正方形区域,σ在步骤S5中计算得到。
- 根据权利要求1所述的针对条纹投影三维测量***离焦现象的相位误差校正方法,其特征在于,步骤S1中所述的对N幅条纹图进行采集的具体方法是:首先调整摄像机的光圈大小,快门速度和感光度,使得采集回来的图像不会出现图像饱和,即图像中最亮区域灰度值小于255),在此相机参数下对N幅条纹图进行采集,在相机出现离焦现象时,相机采集到的条纹灰度值为:
- 根据权利要求1所述的针对条纹投影三维测量***离焦现象的相位误差校正方法,其特征在于,步骤S4中所述的恢复背景图像I'在离焦之前的清晰背景图像I s'的具体方法是:对于每一个边缘像素,沿着灰度梯度方向寻找局部最大值和最小值,由于最大最小值分布于该像素的两侧,故将从最大最小值像素位置到边缘像素位置的所有像素的灰度值设为该最大值或最小值,对每一个边缘像素进行这样的处理,则可以得到清晰的背景图像I s'。
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CN114688995A (zh) * | 2022-04-27 | 2022-07-01 | 河北工程大学 | 一种条纹投影三维测量中的相位误差补偿方法 |
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