A method for measuring the direction of traces on the surface of an object based on statistical properties of normal vectors

Abstract

The application discloses a kind of object surface trace direction measurement methods based on normal vector statistical characteristics, first, the infrared image of four polarized angles of roughness contrast sample block surface is obtained, the polarization parameter of infrared radiation is calculated by solving Stokes vector;Second, select a sample block from roughness contrast sample block and extract the region in the sample block as the measured region;Then 180 space filters containing different direction test lines are established respectively, 180 groups of normal vectors are extracted respectively, and the cosine similarity of all normal vectors and the average value of normal vector on the group of test lines is calculated respectively and the average value is taken;Finally, the average cosine similarity of normal vector in different directions is obtained in turn, and the trace direction of the object is obtained according to the maximum value of the average cosine similarity of normal vector in different directions.The application greatly reduces the subjective error of trace inspection staff compared with the traditional measurement method, and the polarization detection equipment has low cost and simple measurement system arrangement, and is more suitable for actual working condition environment.

Description

Technical Field

[0001] This invention belongs to the field of computer vision technology, specifically relating to a method for measuring the direction of traces on the surface of an object based on the statistical characteristics of normal vectors. Background Technology

[0002] A trace is a three-dimensional shape formed on the contact area between a trace-producing object and a receiving object due to the influence of external factors (external force, pressure, temperature, etc.). Because of different causes of formation and different external factors, traces have different orientations. Trace orientation measurement has a wide range of applications, such as in industrial inspection to detect axial reciprocating motion traces inside hydraulic supports and radial reciprocating motion traces inside motors to determine whether they meet acceptable standards; and in criminal investigation to detect and analyze traces and their orientations made by firearms and other tools used in crimes to find clues for solving cases.

[0003] Currently, micron-level trace orientation detection mainly involves placing the object under a microscope and then manually observing and comparing it. This method of detection using a microscope and the naked eye has many drawbacks, such as long inspection time, low efficiency, and the inspection accuracy largely depending on the experience of the inspectors. In addition, microscope systems are expensive and difficult to apply to actual working conditions.

[0004] Infrared polarization imaging-based measurement methods can automate inspection, greatly reducing subjective errors by trace inspection personnel. Furthermore, the infrared polarization measurement system is simple to set up and more suitable for practical working environments. This method is based on the following experimental findings: the closer the angle of the test line module is to the actual trace direction of the object being measured, the lower the dispersion of the normal vector extracted by the test line module, and the closer the mean cosine similarity of the normal vector is to "1"; conversely, the greater the deviation of the angle of the test line module from the actual trace direction of the object being measured, the higher the dispersion of the normal vector extracted by the test line module, and the closer the mean cosine similarity of the normal vector is to "0". Therefore, by using test line modules with different directions and the surface normal vector of the target object for spatial filtering, and calculating the mean cosine similarity of the normal vector in different directions, a curve of test line direction versus mean cosine similarity of normal vector is plotted, and the direction of the lowest point is read to obtain the trace direction on the object's surface. This method can replace the trace direction detection method that combines microscopic imaging with manual judgment. Summary of the Invention

[0005] To overcome the shortcomings of existing technologies, this invention provides a method for measuring the direction of traces on object surfaces based on the statistical characteristics of normal vectors. First, infrared images of the surface of a roughness comparison sample at four polarization angles are acquired, and the polarization parameters of the infrared radiation are calculated by solving the Stokes vector. Second, a sample is selected from the roughness comparison samples, and its region is extracted as the area to be measured. Then, 180 spatial filters containing test lines in different directions are established, and 180 sets of normal vectors are extracted from each filter. The cosine similarity between all normal vectors on each test line and the average normal vector is calculated, and the average value is taken. Finally, the average cosine similarity of normal vectors in different directions is obtained sequentially, and the direction of the object trace is obtained based on the maximum value of the average cosine similarity of normal vectors in different directions. Compared with traditional measurement methods, this invention greatly reduces the subjective error of trace inspection personnel. Furthermore, the polarization detection equipment is low-cost, the measurement system is simple to set up, and it is more suitable for practical working environments.

[0006] The technical solution adopted by this invention to solve its technical problem includes the following steps:

[0007] Step 1: Obtain infrared images of the surface of the roughness comparison sample at four polarization angles, and calculate the polarization parameters of the infrared radiation by solving the Stokes vector;

[0008] Step 2: Extract an a×a pixel region A from the roughness comparison sample block as the region to be tested; calculate the direction angle and zenith angle distribution information of the normal vector in region A using the polarization parameters obtained in Step 1, and obtain the distribution information of the normal vector in region A;

[0009] Step 3: Construct 180 spatial filter modules, each containing test lines at different angles. Each spatial filter module has a pixel size of a′×a′, where a′... <a;

[0010] Step 4: Perform spatial filtering operations on the 180 spatial filter modules with region A respectively, and extract 180 sets of normal vectors respectively;

[0011] Step 5: Calculate the average value of each group of normal vectors, then calculate the cosine similarity between all normal vectors in the group and the average value of the normal vectors, and take the average value; obtain the direction of the object trace based on the maximum value of the average cosine similarity of the normal vectors at different angles.

[0012] Furthermore, the specific method of step 1 is as follows:

[0013] Infrared images of the roughness comparison sample surface at four polarization angles (0°, 45°, 90°, and 135°) were acquired using a focal plane infrared polarization camera or by mounting and rotating a linear polarizer in front of a regular infrared camera. The polarization phase angle and degree of polarization of the roughness comparison sample surface were calculated based on the Stokes vector.

[0014] Furthermore, the method for calculating the polarization parameters of infrared radiation by solving the Stokes vector is as follows:

[0015] The Stokes vector expression for the polarization state of light can be written in the following form:

[0016] S0 = 0.5 * (I0 + I 45 +I 90 +I 135 )

[0017] S1=I0-I 90

[0018] S2=I 45 -I 135

[0019] Among them, I0, I 45 I 90 I 135 These represent the light intensities at polarization directions of 0°, 45°, 90°, and 135°, respectively.

[0020] Based on the Stokes parameters, the polarization parameters, namely the degree of polarization DoLP and the polarization phase angle AoP, are further calculated using the following formulas:

[0021]

[0022]

[0023] Set the Stokes parameter S3 = 0.

[0024] Furthermore, the distribution information of the normal vector in region A is obtained as follows:

[0025] The azimuth angle θ is calculated using the following formula:

[0026]

[0027] Infrared radiation polarization degree DoLP and zenith angle The geometric expression is:

[0028]

[0029] in:

[0030]

[0031]

[0032] In the formula: n represents the real part of the refractive index of the object, and k represents the imaginary part of the refractive index of the object;

[0033] If the target surface is represented by z = f(x,y), then the normal vector of any point on the object surface is expressed by the following formula:

[0034]

[0035] Furthermore, the different angles in step 3 are 0°, 1°, ..., 179°.

[0036] Furthermore, the specific method for obtaining the object trace direction based on the maximum value of the average cosine similarity of the normal vectors at different angles in step 5 is as follows: sequentially obtain the average cosine similarity of the normal vectors in the directions of 0°, 1°, ..., 179°, draw a curve of the test line direction - the average cosine similarity of the normal vectors, and read the lowest point of the curve as the trace direction.

[0037] The beneficial effects of this invention are as follows:

[0038] Traditional methods for measuring the orientation of micron-level traces on object surfaces primarily rely on microscopy and manual judgment. These methods are time-consuming, inefficient, and their accuracy largely depends on the experience of the inspectors. Furthermore, microscopy systems are expensive and difficult to apply in real-world working conditions. This new method uses surface normal vector distribution and spatial filtering operations with test lines of different directions to obtain the orientation of traces on the object surface. Compared to traditional methods, this significantly reduces subjective errors by inspection personnel. Additionally, the polarization detection equipment is low-cost, the measurement system is simple to set up, and it is more suitable for real-world working environments. Attached Figure Description

[0039] Figure 1 This is the object under test (lathe sample block) used in the embodiments of the present invention.

[0040] Figure 2 These are infrared images of the surface of the object being tested at four polarization angles, according to an embodiment of the present invention.

[0041] Figure 3 This is the test area A extracted in this embodiment of the invention.

[0042] Figure 4 These are test line modules at different angles according to embodiments of the present invention.

[0043] Figure 5 It is the angle-normal vector average cosine similarity curve calculated in the embodiment of the present invention (the true value of the trace direction is 90°). Detailed Implementation

[0044] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0045] This invention provides a method for measuring the orientation of traces on the surface of an object based on the statistical properties of normal vectors, such as... Figure 1 As shown, use the lathe sample block as the test object; as Figure 2 shown, obtain infrared images of the surface of the roughness comparison sample block at four polarization angles, and calculate the polarization parameters of the infrared radiation by solving the Stokes vector; as Figure 3 shown, select a sample block from the roughness comparison sample block and extract area A within the sample block as the待测区域, and the pixel scale of area A is a×a; as Figure 4 shown, establish 180 spatial filters each containing test lines in different directions, the pixel scale of the module is a'×a' (a'<a), perform spatial filtering operations on area A with the test line modules in different directions respectively, extract 180 groups of normal vectors respectively, calculate the average value of the normal vectors of one group, and then calculate the average value of the cosine similarities between all the normal vectors on this group of test lines and the average value of the normal vectors; as Figure 5 shown, sequentially obtain the average cosine similarities of the normal vectors in the directions of 0°, 1°, ..., 179°, draw a curve graph of the test line direction - average cosine similarity of the normal vectors, and read out the lowest point of the curve graph as the trace direction.

[0046] The method is specifically implemented according to the following steps:

[0047] Step 1, as Figure 2 shown, use a split focal plane infrared polarization camera or install and rotate a linear polarizer in front of an ordinary infrared camera to obtain infrared images of the surface of the roughness comparison sample block at four polarization angles of 0°, 45°, 90°, and 135°, and calculate the polarization phase angle and polarization degree information of the surface of the roughness comparison sample block according to the Stokes vector;

[0048] Step 2, as Figure 3 shown, select a sample block from the roughness comparison sample block and extract area A within the sample block as the待测区域, the pixel scale of area A is a×a, calculate the direction angle and zenith angle distribution information of the normal vectors in A from the polarization phase angle and polarization degree information obtained in step 1, and finally obtain the distribution information of the normal vectors in A;

[0049] Step 3, as Figure 4 shown, establish 180 spatial filtering modules each containing test lines in the directions of 0°, 1°, ..., 179°, and the pixel scale of the module is a′×a′ (a′<a);

[0050] Step 4, perform spatial filtering operations on area A with the test line modules of 0°, 1°, ..., 179° respectively, extract 180 groups of normal vectors respectively, calculate the average value of the normal vectors of one group, and then calculate the average value of the cosine similarities between all the normal vectors on this group of test lines and the average value of the normal vectors;

[0051] Step 5, as Figure 5As shown, the mean cosine similarity of the normal vectors in the directions of 0°, 1°, ..., 179° is obtained sequentially, and a curve of the test line direction versus the mean cosine similarity of the normal vectors is plotted. The lowest point of the curve is the trace direction.

[0052] In the technical solution of this invention, an infrared image of the surface of the target under test at four polarization angles (0°, 45°, 90°, and 135°) is acquired using a focal plane infrared polarization camera. The Stokes vector expression for the polarization state of light is written in the following form:

[0053] S0 = 0.5 * (I0 + I 45 +I 90 +I 135 )

[0054] S1=I0-I 90

[0055] S2=I 45 -I 135

[0056] Based on the Stokes parameters, the degree of polarization DoLP and the polarization phase angle AoP can be further calculated, as shown in the following formula:

[0057]

[0058]

[0059] This invention only considers the linear polarization case, therefore the Stokes parameter S3 = 0 is taken here.

[0060] Since the Stokes vector S1 gives the direction of the azimuth plane, this relationship can be used to eliminate the ambiguity between the polarization phase angle and the azimuth angle, and can be calculated using the following formula:

[0061]

[0062] Infrared radiation polarization degree DoLP and zenith angle The geometric expression is:

[0063]

[0064] in:

[0065]

[0066]

[0067] In the formula: n represents the real part of the refractive index of the object, and k represents the imaginary part of the refractive index of the object;

[0068] By obtaining the degree of polarization and polarization phase angle of the infrared radiation on the target surface, the azimuth angle and zenith angle of the target surface can be calculated, and then the normal vector distribution on the target surface can be obtained. If the target surface is represented by z = f(x, y), the normal vector at any point on the object surface can be expressed by the following formula:

[0069]

[0070] In the technical solution of the present invention, based on the experimental finding that when the angle of the test line module is closer to the true trace direction of the measured object, the degree of dispersion of the normal vectors extracted by the test line module is lower, and the average cosine similarity of the normal vectors is closer to "1"; when the angle of the test line module deviates more from the true trace direction of the measured object, the degree of dispersion of the normal vectors extracted by the test line module is higher, and the average cosine similarity of the normal vectors is closer to "0", a test line module based on a spatial filtering form is designed to detect the trace direction of the measured object.

[0071] In the specific operation process of the present invention, first, infrared images of four polarization angles on the surface of the roughness comparison sample block are obtained, and the polarization parameters of the infrared radiation are calculated by solving the Stokes vector; secondly, a sample block is selected from the roughness comparison sample block, and the area A within the sample block is extracted as the待测区域 (to-be-measured area), and the pixel scale of area A is a×a; then, 180 spatial filters containing test lines in different directions are established, and the pixel scale of the module is a'×a' (a' < a). The test line modules in different directions are respectively subjected to spatial filtering operations with area A, 180 groups of normal vectors are respectively extracted, the average value of the normal vectors of one group is calculated, and then the cosine similarity between all the normal vectors on the test line of this group and the average value of the normal vectors is calculated and averaged; finally, the average cosine similarity of the normal vectors in different directions is obtained in sequence, and the trace direction of the object is obtained according to the maximum value of the average cosine similarity of the normal vectors in different directions. Specific embodiment:

[0073] The camera used in this embodiment is a self-developed infrared polarization camera, and the measurement target is a lathe sample block as Figure 1 shown; by using a split focal plane infrared polarization camera or by installing and rotating a linear polarizer in front of an ordinary infrared camera, infrared images of four polarization angles, namely 0°, 45°, 90°, and 135°, on the surface of the roughness comparison sample block are obtained as Figure 2 shown, and the polarization phase angle and degree of polarization information on the surface of the roughness comparison sample block are calculated according to the Stokes vector; a sample block is selected from the roughness comparison sample block, and the area A within the sample block is extracted as the待测区域 (to-be-measured area), and the pixel scale of area A is a×a, as Figure 3As shown, the direction angle and zenith angle distribution information of the normal vector in Area A are calculated from the polarization phase angle and degree of polarization information, and finally the distribution information of the normal vector in Area A is obtained. 180 spatial filtering modules each containing test lines in the directions of 0°, 1°, ..., 179° are established, and the pixel scale of the modules is a′×a′ (a′ < a) as Figure 4 shown; the test line modules and Area A are respectively subjected to spatial filtering operations, 180 groups of normal vectors are respectively extracted, the average value of the normal vectors in one group is calculated, and then the cosine similarity between all the normal vectors on the test line of this group and the average value of the normal vectors is calculated and averaged; the average cosine similarity of the normal vectors in the directions of 0°, 1°, ..., 179° is sequentially obtained, a curve graph of the test line direction - average cosine similarity of the normal vectors is plotted, and the lowest point of the curve graph is read out as the trace direction as Figure 5 shown.

[0074] Step 1, as Figure 2 shown, by using a split focal plane infrared polarization camera or by installing and rotating a linear polarizer in front of an ordinary infrared camera, infrared images at four polarization angles of 0°, 45°, 90°, and 135° on the surface of the roughness comparison sample block are obtained, and the polarization phase angle and degree of polarization information on the surface of the roughness comparison sample block are calculated according to the Stokes vector;

[0075] Step 2, as Figure 3 shown, select a sample block from the roughness comparison sample block and extract Area A within the sample block as the待测区域 (to-be-measured area), the pixel scale of Area A is a×a, the direction angle and zenith angle distribution information of the normal vector in Area A are calculated from the polarization phase angle and degree of polarization information obtained in Step 1, and finally the distribution information of the normal vector in Area A is obtained;

[0076] Step 3, as Figure 4 shown, 180 spatial filtering modules each containing test lines in the directions of 0°, 1°, ..., 179° are established, and the pixel scale of the modules is a′×a′ (a′ < a);

[0077] The specific method of Step 4 is: the test line modules in the directions of 0°, 1°, ..., 179° and Area A are respectively subjected to spatial filtering operations, 180 groups of normal vectors are respectively extracted, the average value of the normal vectors in one group is calculated, and then the cosine similarity between all the normal vectors on the test line of this group and the average value of the normal vectors is calculated and averaged;

[0078] Step 5, as Figure 5 shown, the average cosine similarity of the normal vectors in the directions of 0°, 1°, ..., 179° is sequentially obtained, a curve graph of the test line direction - average cosine similarity of the normal vectors is plotted, and the lowest point of the curve graph is read out as the trace direction.

Claims

1. A method for measuring the orientation of traces on an object surface based on the statistical properties of normal vectors, characterized in that, Includes the following steps: Step 1: Obtain infrared images of the surface of the roughness comparison sample at four polarization angles, and calculate the polarization parameters of the infrared radiation by solving the Stokes vector; Step 2: Extract from roughness comparison sample A pixel-scale region A is taken as the region to be tested; the direction angle and zenith angle distribution information of the normal vector in region A are calculated from the polarization parameters obtained in step 1, and the distribution information of the normal vector in region A is obtained; Step 3: Establish 180 spatial filter modules, each containing test lines at different angles. The pixel scale of each spatial filter module is... ; Step 4: Perform spatial filtering operations on the 180 spatial filter modules with region A respectively, and extract 180 sets of normal vectors respectively; Step 5: Calculate the average value of each group of normal vectors, then calculate the cosine similarity between all normal vectors in the group and the average value of the normal vectors, and take the average value; obtain the direction of the object trace based on the maximum value of the average cosine similarity of the normal vectors at different angles.

2. The method for measuring the direction of traces on the surface of an object based on the statistical properties of normal vectors according to claim 1, characterized in that, The specific method for step 1 is as follows: Infrared images of the roughness comparison sample surface at four polarization angles (0°, 45°, 90°, and 135°) were acquired using a focal plane infrared polarization camera or by mounting and rotating a linear polarizer in front of a regular infrared camera. The polarization phase angle and degree of polarization of the roughness comparison sample surface were then calculated based on the Stokes vector.

3. The method for measuring the direction of traces on the surface of an object based on the statistical properties of normal vectors according to claim 1, characterized in that, The method for calculating the polarization parameters of infrared radiation by solving the Stokes vector is as follows: The Stokes vector expression for the polarization state of light can be written in the following form: in, These represent the light intensities at polarization directions of 0°, 45°, 90°, and 135°, respectively. Based on the Stokes parameters, the polarization parameters are further calculated: degree of polarization. DOLP and polarization phase angle AOP The calculation formula is as follows: Take Stokes parameters .

4. The method for measuring the direction of traces on the surface of an object based on the statistical properties of normal vectors according to claim 1, characterized in that, The distribution information of the normal vectors in region A is obtained as follows: Azimuth Calculate using the following formula: Infrared radiation polarization degree DOLP With zenith angle The geometric expression is: in: In the formula: The real part of the refractive index of an object is represented. The imaginary part of the refractive index of an object; The target surface is made of If we express that the normal vector of any point on the surface of an object is given by the following formula: 。 5. The method for measuring the direction of traces on the surface of an object based on the statistical properties of normal vectors according to claim 1, characterized in that, The different angles in step 3 are 0°, 1°, ..., 179°.

6. The method for measuring the direction of traces on an object surface based on the statistical properties of normal vectors according to claim 1, characterized in that, The specific method for obtaining the object trace direction in step 5 based on the maximum value of the average cosine similarity of the normal vectors at different angles is as follows: obtain the average cosine similarity of the normal vectors in the directions of 0°, 1°, ..., 179° in sequence, draw a curve of test line direction - average cosine similarity of normal vectors, and read the lowest point of the curve as the trace direction.

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