CN117213367A - Line spectrum confocal high-precision calibration method, system, equipment and storage medium - Google Patents
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Abstract
The application discloses a line spectrum confocal high-precision calibration method, a system, equipment and a storage medium, wherein the method comprises the following steps: collecting a spectrum center point fed back by a calibration object, and fitting the spectrum center point into a combined curve equation; taking the coordinates of any spectrum center point, taking the coordinates into a combined curve equation, outputting a coordinate set with the difference value between the coordinate set and the actual coordinate set smaller than a first threshold value and the number of spectrum center points larger than a second threshold value, and fitting the coordinate set into a new curve equation; and selecting a new curve equation corresponding to the coordinate set with the largest number of spectrum center points, and calculating calibration parameters of line spectrum confocal according to the corresponding relation between the new curve equation or the feature point coordinates and the real coordinates. According to the application, the accuracy of curve equation fitting is effectively improved by optimizing the curve equation of the pixel coordinates in the spectrum distribution image; and the conversion from the pixel point to the space point is completed by establishing a one-to-one correspondence between the space point and the pixel point, so that the calibration of the line spectrum confocal system is realized.
Description
Technical Field
The application belongs to the field of spectrum confocal, and particularly relates to a line spectrum confocal high-precision calibration method, a system, equipment and a storage medium.
Background
The spectrum confocal is a non-contact three-dimensional measurement technology using an optical method, broad spectrum complex color light emitted by a light source is converged at different axial positions through a dispersion lens, and only monochromatic light meeting confocal conditions can be detected to the greatest extent by a spectrometer. The distance of the object surface in the axial direction can be deduced by measuring the peak wavelength. According to the measurement mode, the method can be divided into a point confocal system and a line confocal system, and the real space coordinates are reversely deduced according to the pattern shot by the sensor. And due to the influence of factors such as nonlinearity of chromatic dispersion, distortion of a chromatic dispersion lens, distortion of an imaging spectrometer and the like, the confocal system needs to be subjected to distortion correction.
The traditional distortion correction method is usually a Zhang's calibration method and an improvement method thereof, but in a spectrum confocal system, a sensor only records returned spectrum information, an image of a photographed object is not directly obtained, and calibration by a conventional method is difficult.
The spectral confocal measuring system based on the spectral confocal technology utilizes the dispersive objective lens group to ensure that a light source is dispersed after being focused by the dispersive objective lens group, continuous monochromatic light focuses which are different from the dispersive lens are formed on an optical axis, so that the corresponding relation between the wavelength and the axial distance is established, and then the spectral information after the surface of an object to be measured is reflected is obtained by utilizing a spectrometer and the like, so that the corresponding position information is obtained. If the light source is a small hole, final focusing imaging is a point, which is called point scanning confocal; if the light source is a line light source that passes through the slit, the final image is a scan line, known as line scan confocal.
Patent CN114754676a discloses a linear spectrum confocal calibration method, device, equipment, system and storage medium, and proposes to collect a sensor imaging image formed by measuring a calibration plate by using the calibration plate in the range of the linear spectrum confocal sensor, and perform position calibration, peak calibration and distance test to obtain a sensor calibration result. The method is similar to the calibration flow of the point confocal system, and only the axial direction of the system is calibrated, namely, only the sensor image and the axial position are calibrated, and the actual transverse position corresponding to each point on the sensor image cannot be calibrated.
In summary, the prior art has the following disadvantages:
(1) In the traditional spectrum confocal system, a sensor only records returned spectrum information, an object image is not directly acquired, and calibration by a conventional method is difficult;
(2) In the existing linear spectrum confocal calibration method, only the sensor image and the axial position are calibrated, and the actual transverse position corresponding to each point on the sensor image cannot be calibrated.
Disclosure of Invention
The application aims to overcome the problems in the prior art and provide a line spectrum confocal high-precision calibration method, a system, equipment and a storage medium.
In order to achieve the technical purpose and the technical effect, the application is realized by the following technical scheme:
a line spectrum confocal high-precision calibration method comprises the following steps:
collecting a spectrum center point fed back by a calibration object, and fitting the spectrum center point into a combined curve equation;
taking the coordinates of any spectrum center point, taking the coordinates into a combined curve equation, outputting a coordinate set with the difference value between the coordinate set and the actual coordinate set smaller than a first threshold value and the number of spectrum center points larger than a second threshold value, and fitting the coordinate set into a new curve equation;
and selecting a new curve equation corresponding to the coordinate set with the largest number of spectrum center points, and calculating calibration parameters of line spectrum confocal according to the corresponding relation between the new curve equation or the feature point coordinates and the real coordinates.
Further, the aggregate curve segment is connected directly with the central feature point or through a continuous aggregate curve.
Further, the collection curve has feature points with different heights relative to the line light source.
Further, the calibration parameters are calculated by a least square method.
And further, the method also comprises calibration inspection, which is used for detecting whether the calibration parameters are successful, collecting the coordinates of the feature points after the conversion of the calibration objects by replacing or moving the calibration objects, and calculating whether the difference value between the calibration coordinate values and the real coordinate values of the corresponding feature points after the conversion of the calibration objects is in the inspection threshold range or not based on the calibration parameters.
Further, there is a known corresponding curve equation on the surface of the calibration object.
Further, if the number of the characteristic points in the integrated curve is smaller or is 0, the distance between the calibration object and the linear light source is adjusted, so that the number of the characteristic points in the integrated curve is larger, and the calibration accuracy is improved.
The application also provides a line spectrum confocal high-precision calibration system, which comprises:
the linear light source module irradiates the surface of the calibration object after being dispersed by the lens group;
the surface of the calibration object irradiated by the linear light source is provided with a plurality of characteristic points with different relative linear light source heights, and the relative positions of the characteristic points are known;
and the calibration operation module is used for executing the calibration method.
The application also proposes a device comprising a memory and a processor, the memory storing a computer program for execution by the processor, the computer program being arranged to perform the calibration method described above when run.
The application also proposes a computer-readable storage medium comprising a computer program which, when executed by a processor, implements the above-mentioned calibration method.
The beneficial effects of the application are as follows:
(1) According to the application, the accuracy of curve equation fitting is effectively improved by optimizing the curve equation of the pixel coordinates in the spectrum distribution image;
(2) According to the application, the number of the collected feature points is effectively increased through rotation and translation, so that the calibration precision is obviously improved, and meanwhile, the data support is further provided for the precision of the calibration parameters through increasing the number of the virtual intersection points;
(3) According to the method, the conversion from the pixel point to the space point is completed by establishing the one-to-one correspondence between the space point and the pixel point, so that the calibration of the line spectrum confocal system is realized;
(4) The application can simultaneously calibrate the axial transverse position mapping relation between the two-dimensional plane of the sensor and the actual space by utilizing the constructed space characteristic points;
(5) The application has simple flow and convenient operation, and effectively saves labor and time cost;
(6) The fitting model is simple and universal, and the calibration precision is improved.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a line spectrum confocal calibration method in the application;
FIG. 2 is a schematic diagram of the implementation of the line spectrum confocal calibration method in the application;
FIG. 3 is a schematic diagram of superimposed intersections of measurement signals obtained by a calibration object cross-section and line spectrum confocal sensor according to a first embodiment of the application;
FIG. 4 is a schematic diagram of superimposed intersections of measurement signals obtained by a calibration object cross-section and line spectrum confocal sensor according to a second embodiment of the application;
FIG. 5 is a schematic diagram of superimposed intersections of measurement signals obtained by a calibration object cross-section and line spectrum confocal sensor according to a third embodiment of the application;
fig. 6 is a schematic diagram of a coordinate system in the present application.
Description of the embodiments
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
As shown in fig. 1, the present embodiment first provides a line spectrum confocal high-precision calibration method, which includes the following steps:
s1: collecting a spectrum center point fed back by a calibration object, and fitting the spectrum center point into a combined curve equation;
as shown in fig. 2, a calibration object is placed below the line light source with the line spectrum confocal, and the calibration object is installed in the range of the line spectrum confocal sensor; the light with wide spectrum is emitted by linear light source, and the light with different wavelength is focused at different positions by the dispersion of the dispersion objective lens in the lens, and forms a confocal plane, and then irradiates the surface of the calibration object.
The light of the linear light source on different focal planes is reflected by using the difference of the surface heights of the calibration objects. The reflected light passes through the conjugate slit of the spectrometer and is focused on the area array sensor through the original illumination light path of the single-axis system or the imaging light path of the double-axis system.
And the spectrometer decodes the spectrum data of the reflected light acquired by the area array sensor to obtain the surface depth information of the calibration object in the coverage area of the incident light.
The central position of the line light source incident to the surface of the calibration object corresponds to the spectral center point of the corresponding pixel on the surface of the area array sensor. The plurality of spectrum center points can fit a collection curve corresponding to the real space curve on the surface of the line light source covering calibration object.
Only the light focused on the surface of the calibration object can enter an imaging light path to be collected by the area array camera, and the defocused light is greatly attenuated, so that the depth of the surface of the calibration object obtained by the spectrometer does not exceed the dispersion range of the linear light source. Thus, the aggregate curve may have a discontinuous curve. And if the number of the characteristic points in the integrated curve is smaller or is 0, adjusting the distance between the calibration object and the linear light source to enable the number of the characteristic points in the integrated curve to be larger, and improving the calibration precision.
And collecting a spectral distribution image corresponding to the reflected scanning line by using a sensor, extracting spectral information peak coordinate points according to rows or columns, and fitting according to each coordinate point to obtain sensor pixel coordinates corresponding to the surface curve of the calibration object and the characteristic points.
The calibration object is a three-dimensional calibration plate and comprises a plurality of inclined planes with known intervals, intersecting lines of adjacent planes are parallel to each other and have known intervals, and the plane of the scanning line is perpendicular to the bottom surface of the three-dimensional calibration plate and the intersecting lines of the inclined planes of the three-dimensional calibration plate.
Fitting to obtain a calibration object surface curve, specifically, extracting characteristic points in the calibration object surface curve by setting wave crests and wave troughs with different known heights, wherein the wave crests and the wave troughs can be curves. If the peak or trough is curved, the corresponding laser line center point coordinates should be fit to the curve. The corresponding curve equation should be:
wherein a is a fitting coefficient, and the curve fitting method is the same as the random consistency sampling algorithm. Common curve equations are polynomial curve equations.
S2: and taking the coordinates of any spectrum center point, taking the coordinates into a combined curve equation, outputting a coordinate set with the difference value between the coordinate set and the actual coordinate set smaller than a first threshold value and the number of spectrum center points larger than a second threshold value, and fitting the coordinate set into a new curve equation.
The spectrum center point is a point with larger curvature on the image edge, namely a curve wave peak point, a wave valley point and an inflection point.
In the integrated curve, any characteristic point is taken, the characteristic point is taken as a central characteristic point, the integrated curve segments between two adjacent characteristic points on two sides of the characteristic point are taken, and the intersection points or extension intersection points of the two integrated curve segments are fitted.
If the aggregate curve segment between the non-adjacent feature points on either side of the center feature point, the fitted extension intersection point cannot correspond to the center feature point.
The pixel coordinates of the intersection point of the scanning line and the inclined plane intersection line are extracted from the spectrum distribution image, and the specific steps are as follows:
s201, setting the spectrum distribution image as I 1 For I 1 Sequentially performing Gaussian filtering, median filtering and thresholding to obtain a processed graph I 2 The method comprises the steps of carrying out a first treatment on the surface of the The spectrum distribution of the processed image is obvious, the operation of extracting the center point is convenient, and the accuracy of the subsequent calibration is improved;
s202, extracting I 2 The coordinates of the spectral center point corresponding to the mid-reflection linear dispersion light are recorded aspointsThe method comprises the steps of carrying out a first treatment on the surface of the The spectrum returned by incident linear dispersion light projected on the object is not ideal monochromatic light, but has a spectrum with a certain widthThe distribution is that the center point of the spectrum distribution is extracted and the center line is reconstructed, namely the ideal spectrum signal. For the technology of extracting the line center point, a gray level gravity center method, a Gaussian fitting method and the like are common;
s203, extract I 2 Pixel coordinates u and v of intersection points of reflective linear dispersion light and inclined plane intersection lines in the image; specifically, the method further comprises the following steps:
s2031, for the extracted spectrum center point coordinatespointsSmoothing to obtain a sequence curve S;
common smoothing processes include mean smoothing and exponential smoothing.
Assuming that the point coordinates points contain N point coordinates, the average smoothed window size is m, which is generally an odd number, then for the coordinate points (x i ,y i ) I=1, 2,.. i The smoothing formula of (2) is as follows:
wherein,the representation is rounded down and boundary conditions need to be considered when performing mean smoothing.
The exponential smoothing smoothes the current coordinate point by using the current point coordinates and the last smoothed point coordinates. Exponential smoothing versus coordinate point (x) i ,y i ) I=1, 2,.. i The formula is as follows:
representing y i Is a smoothed result of (2);representing y i-1 The smoothing result of (a), namely the last smoothing point coordinates;the weighting coefficients are represented in the range 0-1.
As shown in fig. 3, as a first embodiment, a sequence curve S is formed by connecting two straight lines intersecting each other, specifically as follows:
s2032a, obtaining coordinates corresponding to the wave crest and the wave trough in the sequence curve S, and marking as u 0 、v 0 Filtering out other interference wave crest and wave trough coordinates;
s2033a, atpointsFind the abscissa at [ v ] 0 -n,v 0 +n]Coordinate points within the range, [ v ] 0 -n,v 0 +m][ v ] 0 +m,v 0 +n]Fitting coordinate points in the range by adopting a preset least square method respectively to obtain a linear equation y corresponding to inclined planes on two sides of the intersection point 1 =k 1 x+b 1 Y 2 =k 2 x+b 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein k is 1 、b 1 、k 2 、b 2 Are fitting coefficients, m and n are preset parameters, n>m>0；
S2034a, calculating the coordinates of the intersection of the two straight lines, namely the pixel coordinates u and v of the intersection of the inclined plane to be extracted and the incident linear dispersion light.
As shown in fig. 4, as a second embodiment, the sequence curve S may also be formed by intersecting a straight line and a sinusoidal line, specifically as follows:
s2032b, obtaining coordinates corresponding to the wave crest and the wave trough in the sequence curve S, and marking as u 0 、v 0 Filtering out other interference wave crest and wave trough coordinates;
s2033b atpointsFind the abscissa at [ v ] 0 -n,v 0 +n]Coordinate points within the range, [ v ] 0 -n,v 0 -m][ v ] 0 +m,v 0 +n]Fitting coordinate points in the range by adopting a preset least square method respectively to obtain a linear equation y corresponding to inclined planes on two sides of the intersection point 1 =k 1 x+b 1 And sinusoidal equation y=asin (ωx+Φ) +b; wherein k is 1 、b 1 The A, omega, phi and B are fitting coefficients, and the m and n are preset parameters，n>m>0；
S2034b, calculating coordinates of intersection lines of the straight line and the sinusoidal curve, wherein the coordinates are pixel coordinates u and v of intersection points of the inclined plane intersection line and the incident linear dispersion light to be extracted.
As shown in fig. 5, as a third embodiment, the sequence curve S may also be formed by connecting two sinusoidal curves in an intersecting manner, specifically as follows:
s2032c, obtaining coordinates corresponding to the wave crest and the wave trough in the sequence curve S, and marking as u 0 、v 0 Filtering out other interference wave crest and wave trough coordinates;
s2033c atpointsFind the abscissa at [ v ] 0 -n,v 0 +n]Coordinate points within the range, [ v ] 0 -n,v 0 -m][ v ] 0 +m,v 0 +n]Fitting coordinate points in the range by adopting a preset least square method respectively to obtain two sinusoidal equations y corresponding to inclined planes on two sides of the intersection point 1 =A 1 sin(ω 1 x+φ 1 )+B 1 Y 2 =A 2 sin(ω 2 x+φ 2 )+B 2 The method comprises the steps of carrying out a first treatment on the surface of the Wherein A is 1 、ω 1 、φ 1 、B 1、 A 2 、ω 2 、φ 2 、B 2 Are fitting coefficients, m and n are preset parameters, n>m>0；
S2034c, calculating coordinates of intersection lines of two sinusoids, wherein the coordinates are pixel coordinates u and v of intersection points of inclined plane intersection lines and incident linear dispersion light needing to be extracted.
From the above, besides the fitting by least square method, the fitting for new curve equation can also be performed by random sampling, inpointsFind the abscissa at [ v ] 0 -n,v 0 ]And obtaining a set P of coordinate points in the range, wherein the set P contains n+1 groups of coordinate points. In order to improve the accuracy of straight line fitting, a new curve equation is fitted according to the following steps:
step 1 randomly selects m (m < n+1) coordinate points from the set P, and fits a linear equation using the m coordinate points.
Step 2 for the coordinates in set Px, y), substituting the linear equation if the difference between the y coordinate calculated by the linear equation and the actual y coordinate is less than the threshold valueTdThen consider the coordinates to satisfy the linear equation and add the point coordinates to set S; otherwise, the linear equation is considered not satisfied.
Step 3 if the size of the set S, i.e. the number of coordinate points, is greater than the thresholdT N Then the data in set S is used to re-fit the linear equation to y=kx+b; if the size of the set S is smaller than the threshold valueT N Step 1 is returned.
Step 4 repeats Step 1 to Step 3a plurality of times, and outputs a group of coordinate points with the largest set S and the calculated linear equation y=k opt x+b opt 。
S3: selecting a new curve equation corresponding to the coordinate set with the largest number of spectrum center points, and calculating calibration parameters of line spectrum confocal according to the corresponding relation between the new curve equation or feature point coordinates and real coordinates;
firstly, extracting intersection points of a new curve equation or feature point coordinates in the step S203, extracting real feature point coordinates (X, Z) corresponding to each intersection point, and corresponding pixel coordinates (u, v) of feature points on the whole sensor plane to the real feature point coordinates (X, Z) one by one;
secondly, establishing a fitting model of real feature point coordinates X and Z relative to pixel coordinates:
wherein N is the highest term frequency, and a and b are fitting coefficients;
and finally, calculating the model parameters by adopting a preset least square method to obtain the calibration parameters of the line scanning confocal system.
The extraction of the real characteristic point coordinates can be applied to two scenes of relative fixing or relative moving of the calibration object and the linear light source, and in order to further improve the calibration precision, besides the known information of the characteristic points of the surface of the calibration object, a curve equation corresponding to the surface of the calibration object can be provided, so that precision support is provided for fitting of pixel coordinates.
For two scenes of relative movement of a calibration object and a linear light source, the real coordinates of the characteristic points of the surface of the calibration object covered by the linear light source before and after the movement are required to be recorded, and the real coordinates of the characteristic points of the surface of the calibration object covered by the linear light source after the relative pose of the calibration object and the linear light source is changed are determined according to the known rotation amount or translation amount and the known surface information of the calibration object, wherein the specific steps are as follows:
s301, moving the three-dimensional calibration plate, and recording each moving position;
s302, according to each moving position recorded in the step S301, it is set as [ z ] 1 ,z 2 ,z 3 ,...,z n ]Finding a reference zero point in the middle to obtain Z coordinates corresponding to all intersection points of each position;
s303, as the distance between the vertical lines of the three-dimensional calibration plate is known, a certain vertical line can be selected as an X-axis reference zero point, and then an X coordinate corresponding to each characteristic point of the current position can be obtained;
and obtaining the real characteristic point coordinates of the intersection point according to the steps.
However, the number of feature points that can be acquired is limited by only vertical translation. Therefore, the acquisition number of the characteristic points can be increased through known rotation and translation.
Rotation and translation are controlled by a six-axis control platform. Wherein, the XYZ three-axis translation is controlled by the lifting platform and the translation platform, and the XYZ three-axis rotation is controlled by the angular displacement platform. The lifting platform and the translation platform are provided with scales, so that translation movement at a specified distance can be realized; the angular displacement table is also provided with scales, and can also realize the rotation of a designated angle. Thus, the subsequent rotation and translation may be considered to be known in terms of both the angle of rotation and the amount of translation.
Assume that world coordinates corresponding to the extracted spectrum center point coordinates arePwTaking outPwThe part of (a) is [ (a) and (b)x,y,z) Herex,y,z) Compared to the reference origin. The lifting platform and the translation platform translate, the angular displacement platform rotates, and the three-axis translational momentum is assumed to be%tx,ty,tz) The rotation angle isThe transformation of the rotation angle and the rotation matrix can be realized according to the Rodrigas formula, and therefore, the rotation angle can be converted into the rotation matrix R 3×3 Then for the known world coordinates # -x,y,z) After rotation and translation, the corresponding coordinates arex’,y’,z’) The method comprises the following steps:
similarly, the characteristic point set before rotation, namely the coordinate point at the position of the wave crest and the wave troughP f After rotation, the corresponding coordinatesP’ f Can be calculated from the above formula. The coordinate system established in the original image, as shown in figure 6,P 1 、P 3 andP 4 lying in a planey=0，P 1 、P 2 AndP 3 the two surfaces of the two surfaces are coplanar,P 2 、P 3 andP 4 coplanar. Meanwhile, since the structure of the calibration object is knownP 1 、P 2 、P 3 AndP 4 the rotated coordinates can be obtained by the above formula and written asP 1 ' 、P 2 ' 、P 3 ' AndP 4 ' 。
since three points can define a plane, andP 1 、P 2 、P 3 andP 4 is an ideal value and therefore the estimated plane is also ideal. The coplanarity relation is unchanged before and after the rotation of the calibration object, namelyP 1 ' 、P 2 ' AndP 3 ' the two surfaces of the two surfaces are coplanar,P 2 ' 、P 3 ' andP 4 ' coplanarity and corresponding fitted plane equations are respectively:
at the same time, planey=0A vertical plane which is marked on the calibration object by laser and is intersected with the characteristic point before rotationP 1 、P 3 AndP 4 the rotated laser-driven vertical plane is stilly=0The coordinates of the feature points on the corresponding calibration object satisfy the following conditions:
in the above formula, the plane equation parameter b is known 1 ,c 1 ,d 1 And b 2 ,c 2 ,d 2 According toy=0It can be seen that the unknowns can be calculated from the above equation setx，zAnd further obtaining coordinates of the feature points.
The central characteristic point and the two adjacent characteristic points on two sides of the central characteristic point can be directly connected or connected through continuous aggregation curves. When the collection curve segment between two adjacent characteristic points on two sides is selected, the collection curve segment comprises the central characteristic point, or the collection curve segment does not comprise the central characteristic point.
When the selected combined curve segment comprises the central characteristic point, the combined curve segment is directly connected with the central characteristic point, and the combined curve segment is fitted;
when the selected integrated curve segment does not comprise the central characteristic point, the integrated curve segment is connected with the central characteristic point through a continuous integrated curve, the integrated curve segment conforming to the curve equation type is fitted by matching with the actual curve equation type of the calibration object covered by the linear light source, and the integrated curve segment extends towards the central characteristic point by combining with the actual curve equation.
The two fitting set curve segments intersect or extend to intersect to form an intersection point.
For the calculated calibration parameters, whether the calibration parameters are successful or not can be detected through calibration inspection, the coordinates of the feature points after conversion of the calibration objects can be collected through replacement or movement of the calibration objects, and based on the calibration parameters, the difference value between the calibration coordinate values and the real coordinate values of the corresponding feature points after conversion of the calibration objects is calculated, and whether the difference value is in the inspection threshold range or not is judged, wherein the specific steps are as follows:
s401, scanning lines of a control line scanning confocal system are beaten on a three-dimensional calibration object;
s402, randomly moving the high-precision displacement table, collecting a scanning line reflection spectrogram at a sensor of each random motion position control line scanning confocal system, and simultaneously recording each motion position;
s403, recording a plurality of positions, collecting a plurality of spectrum images, and selecting one position as a reference position;
s404, identifying pixel coordinates of intersection points of the scanning lines and the inclined plane in each image, converting the central pixel coordinates into space coordinates according to the calibration parameters obtained above, and calculating the calibration coordinates of the current intersection points by subtracting the coordinates of the reference positions from the current coordinates;
s405, obtaining the real coordinates of the current intersection point relative to the reference position according to the current position minus the reference position;
s406, calculating a difference value between the real coordinates and the calculated calibration coordinates;
s407, judging whether the difference value is smaller than a given threshold value;
s408, judging whether the difference values of all the positions are smaller than a given threshold value, if yes, judging that the calibration is successful, otherwise, outputting that the calibration is unsuccessful.
The second aspect of the present application also provides a line spectrum confocal high-precision calibration system, comprising:
the linear light source module irradiates the surface of the calibration object after being dispersed by the lens group;
the surface of the calibration object irradiated by the linear light source is provided with a plurality of characteristic points with different relative linear light source heights, and the relative positions of the characteristic points are known;
and the calibration operation module is used for executing the line spectrum confocal calibration method.
The third aspect of the application also provides an apparatus comprising a memory and a processor, the memory having stored therein a computer program for execution by the processor, the computer program being arranged to perform the above-described line spectral confocal calibration method when run.
The fourth aspect of the present application also provides a computer readable storage medium comprising a computer program, characterized in that the computer program, when executed by a processor, implements the line spectrum confocal calibration method described above.
The storage medium may include, but is not limited to: various media capable of storing computer programs, such as a USB flash disk, a read-only memory, a random access memory, a removable hard disk, a magnetic disk or an optical disk.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The foregoing has shown and described the basic principles, principal features and advantages of the application. It will be understood by those skilled in the art that the present application is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present application, and various changes and modifications may be made without departing from the spirit and scope of the application, which is defined in the appended claims.
Claims (10)
1. The line spectrum confocal high-precision calibration method is characterized by comprising the following steps of:
collecting a spectrum center point fed back by a calibration object, and fitting the spectrum center point into a combined curve equation;
taking the coordinates of any spectrum center point, taking the coordinates into a combined curve equation, outputting a coordinate set with the difference value between the coordinate set and the actual coordinate set smaller than a first threshold value and the number of spectrum center points larger than a second threshold value, and fitting the coordinate set into a new curve equation;
and selecting a new curve equation corresponding to the coordinate set with the largest number of spectrum center points, and calculating calibration parameters of line spectrum confocal according to the corresponding relation between the new curve equation or the feature point coordinates and the real coordinates.
2. A line spectrum confocal high-precision calibration method according to claim 1, wherein said integrated curve segments are directly connected with said central characteristic points or connected through continuous integrated curves.
3. The method for calibrating line spectrum confocal precision according to claim 1, wherein the integrated curves have characteristic points with different heights relative to the line light source.
4. The method for calibrating line spectrum confocal high-precision according to claim 1, wherein the calibration parameters are calculated by a least square method.
5. The method according to claim 1, further comprising calibration checking for detecting whether the calibration parameters are successful, collecting coordinates of the feature points after conversion of the calibration object by replacing or moving the calibration object, and calculating a difference between the calibration coordinate values and the real coordinate values of the corresponding feature points after conversion of the calibration object based on the calibration parameters, wherein the difference is within a checking threshold range.
6. The method of claim 1, wherein the surface of the object has a known corresponding curve equation.
7. The linear spectrum confocal calibration method based on calibration object fixation according to claim 1, wherein if the number of characteristic points in the integrated curve is smaller or is 0, the distance between the calibration object and the linear light source is adjusted, so that the number of characteristic points in the integrated curve is larger, and the calibration precision is improved.
8. A line spectrum confocal high-precision calibration system, comprising:
the linear light source module irradiates the surface of the calibration object after being dispersed by the lens group;
the surface of the calibration object irradiated by the linear light source is provided with a plurality of characteristic points with different relative linear light source heights, and the relative positions of the characteristic points are known;
a calibration operation module for performing the calibration method according to any one of claims 1-7.
9. An apparatus comprising a memory and a processor, the memory having stored therein a computer program for execution by the processor, the computer program being arranged to perform the calibration method of any of claims 1-7 when run.
10. A computer readable storage medium comprising a computer program, characterized in that the computer program, when executed by a processor, implements the calibration method according to any one of claims 1-7.
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