CN113793273A - Point cloud noise deleting method based on phase shift fringe brightness amplitude - Google Patents
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Abstract
The invention discloses a point cloud noise deleting method based on phase shift fringe brightness amplitude, which is used for solving the problem of overhigh noise judgment false alarm in point cloud reconstruction. The method comprises the following steps: forming not less than 3 sets of phase shifting pictures for each pixel; obtaining a gray value group corresponding to each pixel according to the phase shift photo group, and calculating a projector phase value corresponding to each pixel by using the gray value; and obtaining the sine wave projection amplitude of the pixel according to the phase value, wherein if the sine wave projection amplitude is less than a preset threshold value, the formed 3D point is noise and is deleted. The amplitude of the phase shift fringe projection in the sine form is used as a basis for noise judgment, more reconstructed point clouds can be reserved, and the quality of point cloud reconstruction is improved.
Description
Technical Field
The invention relates to the technical field of point cloud noise deletion, in particular to a point cloud noise deletion method based on phase shift fringe brightness amplitude.
Background
At present, in the process of reconstructing a 3D point cloud by using a structured light image, due to the influence of factors such as high light reflection or shadow occlusion of a photographed object, an accurate gray image cannot be photographed in some areas in a field of view, so that when the phase of an image pixel is calculated by using a grating stripe, an erroneous phase result is obtained at the pixel position, and finally, noise appears on the reconstructed 3D point cloud. This is a problem that the structured light reconstruction 3D point cloud technology often encounters in practical application and must solve.
Structured light rebuilds 3D point cloud technique to the 3D camera that ordinary 2D camera and projecting apparatus are constituteed is the shooting equipment, by the projecting apparatus with the grating stripe of predetermineeing, including Gray code, phase shift code etc. projection to the target surface, shoot the projection scene by the 2D camera simultaneously, obtain the projected object photo of taking the stripe. And calculating the projector phase corresponding to each pixel according to the picture, and finally calculating the 3D coordinate corresponding to each pixel, namely the surface point cloud of the target by using the 2D camera pixel and the projector phase corresponding to the pixel through the spatial intersection of the light paths of the two pixels. According to the principle of structured light spot cloud reconstruction, the accuracy of the final point cloud is closely related to the calculation of the phase, and the calculation of the phase is hooked with the shooting quality of the projection scene. In practical applications, the photographed target often causes overexposure and whitening of some areas or dark shading in the photographed stripe photo due to the reflection performance of the photographed target or due to the shading of the appearance. The phases calculated by these low-quality shooting regions are unreliable, and the reconstructed point cloud is noise deviating from the actual position relative to the whole target and should be deleted. Since the normal projection of a set of phase shift codes on a pixel is bright and dark, it is usually determined whether the pixel is likely to form noise by the magnitude of the brightness difference of a series of phase shift code pictures on the same pixel. If the brightness difference is large, it indicates that the shooting is normal, and if the brightness difference is small, it indicates that the whole pixel is too bright or too dark, and noise is formed.
At present, the commonly used method for judging noise by the brightness difference of a group of phase shift codes on one pixel has the defect of large false alarm. This is because the number of phase shift stripes in sine wave form is different, and there are 4-step phase shift, 5-step phase shift, etc., so that a group of projection stripes presents gray scale on one pixel, and the peaks and valleys of the sine wave cannot be obtained. Therefore, the brightness difference of the phase shift fringes is certainly smaller than the amplitude of the sine wave, and if the overall smaller brightness difference of the phase shift fringes is used to judge the noise, the false alarm phenomenon is too high.
The method solves the problem of overhigh noise judgment false alarm in point cloud reconstruction, and is one of important basic technologies in reconstructing 3D point cloud by using structured light images.
Disclosure of Invention
The embodiment of the invention provides a point cloud noise deleting method based on phase shift fringe brightness amplitude, which is used for solving the problem of overhigh noise judgment false alarm in point cloud reconstruction.
The embodiment of the invention provides a point cloud noise deleting method based on phase shift fringe brightness amplitude, which comprises the following steps:
step A: forming not less than 3 sets of phase shifting pictures for each pixel;
and B: obtaining a gray value group corresponding to each pixel according to the phase shift photo group, and calculating a projector phase value corresponding to each pixel by using the gray value;
and C: and acquiring a sine wave projection amplitude of the pixel according to the phase value, wherein the sine wave projection amplitude is less than a preset threshold value, judging that a 3D point formed corresponding to the pixel is noise, and deleting the 3D point corresponding to the pixel.
In a preferred embodiment, step a specifically includes: the phase shift stripes in the sine form, which are not less than 3 steps, are sequentially projected onto a target object through a projector, and the projected target object is shot by a 2D camera to obtain a phase shift photo group.
In a preferred embodiment, the step C obtains the amplitude of the sine wave projection of the pixel according to the phase value, and the specific implementation method includes:
the obtained phase value and the gray value of the corresponding projection picture of the pixel are utilized to combine the sine wave formula of the phase shift fringe
And obtaining the sine wave projection amplitude projected to the pixel, wherein u and v are respectively the column coordinate and the row coordinate of the pixel, I (u and v) is the gray value of the pixel, B is the phase value, T is the period length of the phase shift stripe, A is the object color, and B is the sine wave projection amplitude of the pixel.
In a preferred embodiment, the phase value B is calculated by using a phase-shifting picture group with no less than 3 steps, and is substituted into a sine wave formula, and a corresponding sine wave formula group is formed by combining different I (u, v) obtained by multiple times of shooting, and the object color A and the sine wave projection amplitude B are calculated by using least square.
In a preferred embodiment, the predetermined threshold is 8. Experiments show that when the threshold value of the sine wave projection amplitude is set to be 8, the noise points can be well deleted, and meanwhile, correct object surface point clouds can be kept.
In a preferred embodiment, the 3D points corresponding to the pixels are removed by using morphological dilation and erosion techniques. The method specifically comprises the following steps: marking pixels corresponding to noise points in a photo as white, marking other pixels as black, firstly expanding white points according to a set window size, marking neighborhood pixels in an expansion window as white, then corroding boundary points of an expanded white area, wherein the sizes of a corrosion window and the expansion window are consistent, and points in the corrosion window are marked as black, and finally, a span area of the white points is unchanged and a communication area is formed; and 3D points corresponding to the last remaining connected white pixels are noise points to be deleted finally.
The embodiment of the invention has the beneficial effects that: compared with the existing point cloud reconstruction noise judgment method, the amplitude of the phase shift fringe projection in the sine form is used as the basis for noise judgment, and the problem of over-high false alarm of judgment noise caused by the fact that the wave crest and the wave trough of sine brightness can not be ensured to simultaneously appear in a group of phase shift projections of the same pixel in the traditional noise judgment method is effectively solved. Therefore, more reconstructed point clouds can be reserved, and the quality of point cloud reconstruction is improved.
Drawings
FIG. 1 illustrates a method for removing noise in a point cloud according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a target object to be point cloud reconstructed according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a phase-shifted photo group under a 5-step phase-shifted projection according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a reconstruction result of 3D point cloud without noise deletion according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a reconstruction result of 3D point cloud deletion noise according to an embodiment of the present invention.
Detailed Description
The following describes in detail a specific implementation of a point cloud noise removing method based on phase shift fringe luminance amplitude according to an embodiment of the present invention with reference to fig. 1, fig. 2, fig. 3, fig. 4, and fig. 5.
The embodiment of the invention provides a point cloud noise deleting method based on phase shift fringe brightness amplitude, which comprises the following steps:
step A: forming not less than 3 sets of phase shifting pictures for each pixel;
and B: obtaining a gray value group corresponding to each pixel according to the phase shift photo group, and calculating a projector phase value corresponding to each pixel by using the gray value;
and C: and acquiring a sine wave projection amplitude of the pixel according to the phase value, wherein the sine wave projection amplitude is less than a preset threshold value, judging that a 3D point formed corresponding to the pixel is noise, and deleting the 3D point corresponding to the pixel.
Fig. 2 is a target object to be subjected to point cloud reconstruction, and it can be seen that at the edge of the object, a shadow band is formed due to the shielding of the self height on the peripheral area.
In this embodiment, step a specifically includes: by means of a projector, 5-step phase shift stripes in a sinusoidal form are sequentially projected onto a target object, and the projected target object is photographed by a 2D camera to obtain a phase shift photo group, which is a group of photos projected by 5-step phase shift codes as shown in fig. 3, and a phase value and a sinusoidal stripe brightness amplitude of each pixel can be calculated from the group of photos.
In this embodiment, the sine wave projection amplitude of the pixel is obtained according to the phase value in step C, and the specific implementation method is as follows:
the obtained phase value and the gray value of the corresponding projection picture of the pixel are utilized to combine the sine wave formula of the phase shift fringe
And obtaining the sine wave projection amplitude projected to the pixel, wherein u and v are respectively the column coordinate and the row coordinate of the pixel, I (u and v) is the gray value of the pixel, B is the phase value, T is the period length of the phase shift stripe, A is the object color, and B is the sine wave projection amplitude of the phase shift code.
And (3) calculating a phase value B by using the phase-shifting picture group of the 5 steps, substituting the phase value B into a sine wave formula, forming a corresponding sine wave formula group by combining different I (u, v) obtained by multiple times of shooting, and calculating an object color A and a sine wave projection amplitude B by using least square.
The phase shift fringe sine wave formula has 3 unknown quantities A, B, b in total, because multiple (3 or more) phase shift photographs are taken, the phase value b can be calculated by using the photographs and then substituted into the sine wave formula, and the A, B can be calculated by using least squares according to the different I (u, v) obtained from multiple photographs.
FIG. 4 is the 3D point cloud reconstruction of the object of FIG. 2, without point cloud denoising. Fig. 5 is a reconstructed point cloud obtained by performing a noise removal technique in the reconstruction process according to the present embodiment, where noise generated in a shadow band region is accurately removed. Compared with fig. 4 and 5, the image effect after the point cloud noise based on the phase shift fringe brightness amplitude is deleted is better.
The preset threshold is 8. Experiments show that when the threshold value of the sine wave projection amplitude is set to be 8, the noise points can be well deleted, and meanwhile, correct object surface point clouds can be kept.
In a 3D camera, for each pixel of a 2D picture, a sine wave formula is used to calculate that the projected fringe taken by the pixel is the pixel from the projector (i.e., the phase). The ray of the 2D camera whose optical center points to its picture pixel must intersect the ray of the projector whose optical center points to its phase, and this intersection point is the 3D point corresponding to the picture pixel under consideration.
In reality, the shadow region formed by the occlusion of an object or the overexposure region formed by high reflection light are main sources of noise and are connected regions. Therefore, after the noise points are determined by the amplitude of the sine wave projection, the points judged to be noise may be discrete, and when the noise is deleted, the 3D points corresponding to the pixels can be deleted by using the expansion and corrosion technology in morphology. The method specifically comprises the following steps: marking pixels corresponding to noise points in a photo as white, marking other pixels as black, firstly expanding white points according to a set window size, marking neighborhood pixels in an expansion window as white, then corroding expanded white area boundary points (namely pixels with black points in the neighborhood), wherein the sizes of a corrosion window and the expansion window are consistent, the points in the corrosion window are marked as black, and finally, the span area of the white points is unchanged and a communication area is formed; and 3D points corresponding to the last remaining connected white pixels are noise points to be deleted finally.
Compared with the existing point cloud reconstruction noise judgment method, the point cloud noise deleting method based on the phase shift stripe brightness amplitude takes the size of the phase shift stripe projection brightness amplitude in a sine form as the basis of noise judgment. The problem of over-high false alarm of the judgment noise caused by the fact that the wave crest and the wave trough of sinusoidal brightness can not be ensured to simultaneously appear in a group of phase shift projections of the same pixel in the traditional noise judgment method is effectively solved. Therefore, more reconstructed point clouds can be reserved, and the quality of point cloud reconstruction is improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (7)
1. A point cloud noise deleting method based on phase shift fringe brightness amplitude is characterized by comprising the following steps:
step A: forming not less than 3 sets of phase shifting pictures for each pixel;
and B: obtaining a gray value group corresponding to each pixel according to the phase shift photo group, and calculating a projector phase value corresponding to each pixel by using the gray value;
and C: and acquiring a sine wave projection amplitude of the pixel according to the phase value, wherein the sine wave projection amplitude is less than a preset threshold value, judging that a 3D point formed corresponding to the pixel is noise, and deleting the 3D point corresponding to the pixel.
2. The method according to claim 1, wherein step a is specifically: the phase shift stripes in the sine form, which are not less than 3 steps, are sequentially projected onto a target object through a projector, and the projected target object is shot by a 2D camera to obtain a phase shift photo group.
3. The method of claim 2, wherein the step C of obtaining the amplitude of the sinusoidal projection of the pixel according to the phase value is implemented by:
combining the sine wave formula of the phase shift fringe with the obtained phase value and the gray value of the corresponding projection picture of the pixel
And obtaining the sine wave projection amplitude projected to the pixel, wherein u and v are respectively a column coordinate and a row coordinate of the pixel, I (u, v) is the gray value of the pixel, B is the phase value, T is the period length of the phase shift stripe, a is the object color, and B is the sine wave projection amplitude of the pixel.
4. The method of claim 3, wherein the phase value B is calculated by using a phase-shifting picture group with no less than 3 steps, and is substituted into the sine wave formula, and a corresponding sine wave formula group is formed by combining different I (u, v) obtained by multiple times of shooting, and the object color A and the sine wave projection amplitude B are calculated by using least square.
5. The method of claim 1, wherein the predetermined threshold is 8.
6. The method of claim 1, wherein the 3D points corresponding to the pixels are deleted using a dilation and erosion technique in morphology.
7. The method according to claim 6, characterized in that, the pixels corresponding to the noise points in the picture are marked as white, other pixels are black, the white points are expanded according to the set window size, the neighborhood pixels in the expansion window are marked as white, then the boundary points of the expanded white area are corroded, the corrosion window and the expansion window are consistent in size, the points in the corrosion window are marked as black, finally, the span area of the white points is unchanged, and a connected area is formed; and 3D points corresponding to the last remaining connected white pixels are noise points to be deleted finally.
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