CN107392899B - Automatic detection method for horizontal angle of grinding mark of steel ball grinding spot image - Google Patents

Automatic detection method for horizontal angle of grinding mark of steel ball grinding spot image Download PDF

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CN107392899B
CN107392899B CN201710597205.6A CN201710597205A CN107392899B CN 107392899 B CN107392899 B CN 107392899B CN 201710597205 A CN201710597205 A CN 201710597205A CN 107392899 B CN107392899 B CN 107392899B
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area
grinding
contrast
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mark
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CN107392899A (en
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肖梅
赵国玉
张雷
徐婷
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Changan University
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Abstract

The invention provides an automatic detection method of a horizontal angle of a grinding mark of a steel ball grinding spot image, which comprises the following steps of firstly carrying out gray processing on an acquired grinding spot image of a steel ball; rotating the obtained gray-scale grinding spot image f to obtain a rotating grinding spot image fθ(ii) a Selecting a reference area and 2s contrast areas from the obtained rotating grinding spot image, calculating gray level differences between the kth contrast area and eight adjacent direction area blocks of the kth contrast area and the reference area, taking the minimum value as the difference between the reference area and the kth contrast area, calculating the difference between all the contrast areas and the reference area by analogy, taking the sum of all the difference as the grinding mark difference of the direction angle theta, and finally calculating the horizontal angle of the grinding mark through the grinding mark difference; the detection method takes the area block as a processing object and the central area as a reference area, so that the processing result is inconsistent in thinking, higher in speed and more accurate in result.

Description

Automatic detection method for horizontal angle of grinding mark of steel ball grinding spot image
Technical Field
The invention belongs to the field of performance analysis of automobile running materials, and particularly relates to an automatic detection method for a horizontal angle of a grinding mark of a steel ball grinding spot image.
Background
With the rapid development of computer technology, image analysis and processing technology is widely applied to various fields of the automobile industry, such as: in the field of automobile operation materials, a four-ball friction tester is used for carrying out an abrasion resistance test, and the abrasion resistance of a lubricant is evaluated by measuring the diameter of an abrasion spot. In the process of measuring the grinding mark diameter, an operator uses a measuring tool (such as a vernier caliper or a straight ruler) to respectively measure the grinding mark diameters of the three bottom balls twice, the first measuring direction is along the grinding mark direction, the second measuring direction is perpendicular to the first measuring direction, namely the vertical direction of the grinding mark, and in the measuring process, the two measuring directions need to be qualitatively sensed and judged by a tester. When the sensing error or experience of a tester is insufficient, the determined grinding track direction deviates from the actual direction, and further the error occurs in the measurement of the grinding spot diameter.
Disclosure of Invention
The invention aims to provide an automatic detection method for a horizontal angle of a grinding mark of a steel ball grinding spot image, which solves the problem that the measurement of the horizontal angle of the grinding mark of the existing steel ball grinding spot image causes errors through the qualitative perception of testers.
In order to achieve the purpose, the invention adopts the technical scheme that:
the invention provides an automatic detection method for a horizontal angle of a grinding mark of a steel ball grinding spot image, which comprises the following steps:
step one, after a steel ball friction test is finished, acquiring an abrasion mark image through a high-power electron microscope or a scanning electron microscope, and marking the acquired abrasion mark image as F;
secondly, carrying out gray processing on the collected speckle image F by a weighted average method to obtain a gray speckle image F;
thirdly, clockwise rotating the gray scale abrasion pattern f obtained in the second step by theta degrees around the central point O of the image to obtain a rotary abrasion pattern fθHaving a size of mθ×nθ；
The fourth step, using the rotary grinding spot pattern f obtained in the third stepθIs taken as the center, an area is arbitrarily selected as a reference area Aθ；
Fifth step, the rotational wear pattern f obtained in the third stepθIn the central horizontal direction, with reference to the reference area AθAs the center, symmetrically selecting and referencing areas A to both sidesθS area blocks having the same size and shape as the comparison area DθObtaining 2s contrast areas in total;
sixthly, respectively calculating the comparison areas DθThe k-th contrast region of
Figure BDA0001356320270000021
And a contrast area
Figure BDA0001356320270000022
The adjacent eight-direction area blocks and the reference area AθThe gray difference between the two images is obtained, and the minimum value of the nine obtained gray differences is taken as a contrast area
Figure BDA0001356320270000023
And a reference area AθDegree of difference of (2)
Figure BDA0001356320270000024
Seventhly, calculating all the contrast areas D under the same direction angle thetaθAnd a reference area AθAnd the sum of the obtained degrees of difference is taken as the degree of difference C of the grinding mark at the direction angle thetaθ；
Eighth step, according to the difference degree C of the grinding marks obtained in the seventh stepθCalculating the horizontal angle of the grinding spot and the grinding scar
Figure BDA0001356320270000025
Preferably, in the first step, the pixel size of the speckle image F is mxn, the coordinate of any pixel point of the speckle image F is (x, y), x and y respectively represent the row and column of the pixel point, x and y are integers, x is greater than or equal to 1 and less than or equal to m, and y is greater than or equal to 1 and less than or equal to n.
Preferably, in the second step, the gray value of the pixel point (x, y) in the obtained gray speckle pattern f is f (x, y), and the calculation formula of f (x, y) is as follows:
f(x,y)＝0.299×R(x,y)+0.587×G(x,y)+0.144×B(x,y) (1)
wherein, R (x, y), G (x, y), B (x, y) respectively represent red R, green G, blue B component values of the pixel point (x, y) in the scrub pattern F.
Preferably, in the fourth step, the reference region aθIs a square of 2 omega +1 pixels on a side, the area of which
Figure BDA0001356320270000026
Is of a size of
Figure BDA0001356320270000027
Wherein, the value range of omega is 3-20.
Preferably, in the fifth step, the contrast area D is selectedθThe two adjacent region blocks do not overlap.
Preferably, in the fifth step, the distance between the center points of two adjacent area blocks is 2 ω + 1.
Preferably, the sixth step, the k-th contrast region
Figure BDA0001356320270000031
And a reference area AθDegree of difference of (2)
Figure BDA0001356320270000032
The calculating method of (2): comparing the k-th contrast area
Figure BDA0001356320270000033
Slightly moving 1 pixel in eight directions of upper left, upper right, upper left, right, lower left, lower right and lower right, respectively calculating the contrast area according to the formula (2)
Figure BDA0001356320270000034
The gray level difference of eight adjacent directional area blocks takes the minimum value of nine gray level differences as the contrast area
Figure BDA0001356320270000035
And a reference area AθDegree of difference of (2)
Figure BDA0001356320270000036
Figure BDA0001356320270000037
Wherein, i and j are integers and are respectively the kth contrast area
Figure BDA0001356320270000038
And a reference area AθThe row number and column number of the pixel coordinates,
Figure BDA0001356320270000039
alpha and beta are respectively k-th contrast area
Figure BDA00013563202700000310
A fine shift amount in the row direction and the column direction of (a) ═ 1,0,1, β ═ 1,0, 1; k is a contrast region
Figure BDA00013563202700000311
The number of (2); a. theθ(i, j) is a reference region AθThe gray value of the middle pixel point (i, j),
Figure BDA00013563202700000312
is the k contrast area
Figure BDA00013563202700000313
And the gray value of the middle pixel point (i + alpha, j + beta + k (2 omega + 1)).
Preferably, in the seventh step, the degree of difference in abrasion mark C at the orientation angle θ is calculated according to the formula (3)θ：
Figure BDA00013563202700000314
Preferably, the eighth step, horizontal angle of grinding mark
Figure BDA00013563202700000315
The calculation formula (c) is as follows:
Figure BDA00013563202700000316
compared with the prior art, the invention has the beneficial effects that:
the invention provides an automatic detection method of a horizontal angle of a grinding mark of a steel ball grinding spot image, which comprises the steps of firstly carrying out gray processing on the collected steel ball grinding spot image so as to achieve the purposes of reducing the interference of color information on a detection result and accelerating the operation speed; and carrying out rotation processing on the obtained gray-scale grinding mark image to convert oblique line direction processing into horizontal direction processing so as to obtain a direction angle theta with the most obvious strip distribution characteristic of the grinding mark image, selecting a reference area and 2s contrast areas in the obtained rotation grinding mark image, calculating gray level differences between the kth contrast area and eight adjacent direction area blocks and the reference area, taking the minimum value as the difference between the reference area and the kth contrast area, calculating the difference between all the contrast areas and the reference area by analogy, taking the sum of all the differences as the grinding mark difference of the direction angle theta, and finally calculating the horizontal angle of the grinding mark through the grinding mark difference. The detection method improves the determination precision of the horizontal angle of the grinding spots and reduces the workload of detection personnel; meanwhile, compared with the disclosed pixel-level processing method, the detection method takes the area block as a processing object and the central area as a reference area, and the processing result is inconsistent in thinking, higher in speed and more accurate in result.
Drawings
FIG. 1 is a scrub pattern F;
FIG. 2 is a gray scale mura pattern f;
FIG. 3 is a schematic view of the orientation angle θ;
FIG. 4 is a block of area before rotation;
FIG. 5 is a diagram of a rotating scrub pattern fθ；
FIG. 6 shows horizontal angles of the grinding spots
Figure BDA0001356320270000041
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The invention provides an automatic detection method for a horizontal angle of a grinding mark of a steel ball grinding spot image, which comprises the following steps:
step S0: acquiring a grinding spot image:
and after the steel ball friction test is finished, acquiring an abrasion mark image through a high-power electron microscope or a scanning electron microscope, marking the acquired abrasion mark image as F, and setting the size of the abrasion mark image as mxn. The wear pattern F collected in this embodiment is 768 × 1024, that is, m is 768 and n is 1024, as shown in fig. 1. Assuming that the coordinate of a certain pixel point is (x, y), x and y respectively represent the row number and the column number of the pixel point, and x and y are integers, satisfying: x is more than or equal to 1 and less than or equal to m, y is more than or equal to 1 and less than or equal to n, namely x is more than or equal to 1 and less than or equal to 768, and y is more than or equal to 1 and less than or equal to 1024.
Step S1: carrying out gray processing on the collected color speckle images:
because the speckle image does not have obvious color information, the speckle image is firstly subjected to gray processing, and the purposes of reducing the interference of the color information on the detection result and accelerating the operation speed can be achieved. The color image graying processing methods include a component method, an average value method, a maximum value method and a weighted average method, the embodiment adopts a weighted average method, specifically, the graying processing is performed on the wear pattern F acquired in step S0 to obtain a grayscale wear pattern F as shown in fig. 2, and the calculation formula is shown in formula (1):
f(x,y)＝0.299×R(x,y)+0.587×G(x,y)+0.144×B(x,y) (1)
wherein f (x, y) represents the gray value of a certain pixel point (x, y) in the gray scale speckle pattern f; r (x, y), G (x, y) and B (x, y) respectively represent R (red), G (green) and B (blue) component values of a pixel point (x, y) in the wear pattern F.
Step S2: rotating the grinding spot image:
the grinding spot image of the steel ball is mainly in a shape formed by mutual friction among the steel balls, and is represented as grinding marks and abnormal abrasion, wherein the abnormal abrasion is as follows: ablation and adhesion; the grinding marks are in strip distribution, the similarity of adjacent regions under different direction angles is measured by utilizing the characteristic, the strip distribution characteristic of the grinding marks under different direction angles can be measured, when the direction angle theta is consistent with the direction of the grinding marks, the similarity of the adjacent regions is the highest, and the strip distribution characteristic of the grinding marks is the most obvious. As shown in FIG. 3, the direction angle is the angle formed by any ray and the horizontal right ray with the image center point O as the vertex.
In actual operation, because the region block located at the azimuth of the image direction is difficult to select and the calculation is complicated, the invention adopts a method of rotating the image to turn the direction angle to the horizontal direction, and the region block at the azimuth of the direction angle is converted into the horizontal block, so that the subsequent processing can be simplified into horizontal processing, and the region block in fig. 4 can be turned to the horizontal direction as shown in fig. 5 through the rotation operation.
Specifically, the gray-scale abrasion pattern f is rotated clockwise by theta degrees around the central point O of the image to obtain a rotary abrasion pattern fθAssuming that it is m in sizeθ×nθAt this time, calculating the similarity of the region blocks in the horizontal direction is equivalent to calculating the similarity of the region blocks of the gray-scale pattern f in the azimuth of the direction angle θ.
Step S3: selecting a reference area:
the grinding mark strip characteristics of the edge area of the grinding mark image are not obvious because the edge area of the grinding mark is easily interfered by noise and grinding dust; the central area of the wear mark image has the most obvious wear mark strip characteristics, so the central area of the wear mark is selected as a reference area to measure the wear mark similarity when the direction angle theta is measured.
Specifically, the rotational scrub image f obtained in step S2θCentral point of (2)
Figure BDA0001356320270000061
Arbitrarily selecting a certain area as the center, called the reference area A as shown in FIG. 5θWherein, in the step (A),
Figure BDA0001356320270000062
and
Figure BDA0001356320270000063
are all integers, [ 2 ]]Representing a rounding operation.
Setting a reference area AθThe shape of (2 omega +1) is a square, the side length of the square is a (2 omega +1) pixel unit, the minimum element characteristic and the operation speed of a grinding crack are considered, the value range of omega is 3-20, and the area of the omega is the same as that of the minimum element characteristic and the operation speed
Figure BDA00013563202700000617
Is of a size of
Figure BDA0001356320270000064
In the present embodiment, the reference region AθArea of (2)
Figure BDA00013563202700000618
Is of a size of
Figure BDA00013563202700000619
Where ω is 5.
Step S4: contrast region DθSelecting:
the contrast area is an area selected for comparing the similarity of the area blocks in the central horizontal direction, and therefore, the reference area a needs to be used in the central horizontal directionθAs the center, symmetrically selecting and referencing areas A to both sidesθS area blocks having the same size and shape as the comparison area DθThe value range of s is 1-10; then 2s contrast areas D are obtainedθComparison region DθNumbered from left to right as
Figure BDA0001356320270000065
As shown in figure 5 of the drawings,
Figure BDA0001356320270000066
denotes the k-th contrast region D from the leftθ。
At the same time, selecting the contrast area DθIn this case, the positions of two adjacent area blocks are partially overlapped or not overlapped, and preferably, the distance between the center points of the two adjacent area blocks is (2 ω + 1).
In this embodiment, s is 3, and the adjacent region blocks do not overlap.
Step S5: calculating the k contrast region
Figure BDA0001356320270000067
And a reference area AθDegree of difference of (2)
Figure BDA0001356320270000068
In order to reduce the influence of noise, distortion caused by rotation, insufficient operation experience of a tester and the like, the k-th contrast area is not directly used
Figure BDA0001356320270000069
And a reference area AθGray scale difference of
Figure BDA00013563202700000610
As a contrast region
Figure BDA00013563202700000611
And a reference area AθThe degree of difference of (a);
but separately calculate the contrast regions DθThe k-th contrast region of
Figure BDA00013563202700000612
And a reference area AθDegree of difference therebetween
Figure BDA00013563202700000613
I.e. calculating the contrast areas separately
Figure BDA00013563202700000614
Itself and eight adjacent directional area blocks and reference area AθThe gray difference between the two areas is obtained, and the minimum value of the nine obtained gray differences is taken as the k-th contrast area
Figure BDA00013563202700000615
And a reference area AθDegree of difference therebetween
Figure BDA00013563202700000616
Specifically, the contrast region
Figure BDA0001356320270000071
Slightly moving 1 pixel in eight directions of upper left, upper right, upper left, right, lower left, lower right and lower right, respectively calculating the contrast area according to the formula (2)
Figure BDA0001356320270000072
The gray level difference of eight adjacent directional area blocks takes the minimum value of nine gray level differences as the k-th contrast area
Figure BDA0001356320270000073
And a reference area AθDegree of difference of (2)
Figure BDA0001356320270000074
Figure BDA0001356320270000075
Wherein, i and j are integers and are respectively the kth contrast area
Figure BDA0001356320270000076
And a reference area AθThe row number and column number of the pixel coordinates,
Figure BDA0001356320270000077
alpha and beta are respectively contrast regions
Figure BDA0001356320270000078
A fine shift amount in the row direction and the column direction of (a) ═ 1,0,1, β ═ 1,0, 1; k is a contrast region
Figure BDA0001356320270000079
The number of (2); a. theθ(i, j) is a reference region AθThe gray value of the middle pixel point (i, j),
Figure BDA00013563202700000710
as a contrast region
Figure BDA00013563202700000711
And the gray value of the middle pixel point (i + alpha, j + beta + k (2 omega + 1)).
Step S6: calculating the degree of difference C of grinding marks of the direction angle thetaθ：
First, according to the calculation method of step S5, all the contrast regions D having the same direction angle theta are calculatedθAnd a reference area AθDegree of difference of (2)
Figure BDA00013563202700000712
And the obtained difference degree
Figure BDA00013563202700000713
And the sum is used as the grinding mark difference degree of the direction angle theta, and the grinding mark difference degree is used for measuring the significance of the linear distribution characteristic of the grinding marks under the direction angle theta. With CθThe degree of difference in wear marks when the azimuth angle is θ is expressed by the following formula (3).
Figure BDA00013563202700000714
And 7: calculating horizontal angle of grinding mark
Figure BDA00013563202700000715
When the direction angle theta is consistent with the direction of grinding mark, comparing area DθAnd a reference area AθHas the highest similarity, the strip distribution characteristic of the grinding marks is also most obvious, and the grinding mark difference degree C of the direction angle thetaθAt the minimum, the direction angle θ at this time is equal to the horizontal angle of the wear mark as shown in FIG. 6
Figure BDA00013563202700000716
The calculation formula (4) is satisfied.
Figure BDA00013563202700000717
In this embodiment
Figure BDA0001356320270000081
Step S8: the algorithm ends.
According to the technical scheme of the invention, the advantages of the scheme of the invention are summarized from two aspects of running time and cost analysis.
(1) The measurement accuracy of the horizontal angle of the wear-scar image is improved. At present, the horizontal angle measurement of the wear-scar image is mainly determined by artificial naked eyes, certain errors are inevitably generated, and operation errors can occur due to insufficient experience, so that the errors can be reduced by using the method;
(2) the workload of detection personnel is reduced. When the experience of a measurer is insufficient or the abrasion mark is irregular, repeated measurement is often needed for many times, time and labor are wasted, the abrasion mark pattern F is automatically detected by the method, and the detection time is greatly saved. Taking an image having an image size of 768 × 1024 as an example, it takes approximately 30s for ordinary manual evaluation of the horizontal angle of the wear scar. The present invention takes about 3.7s for the image to be measured. Therefore, the processing speed of the method for measuring the horizontal angle of the grinding spots has obvious advantages.
(3) Compared with the disclosed pixel-level processing method, the method takes the area block as a processing object and the central area as a reference area, and the processing result is inconsistent in thinking, higher in speed and more accurate in result.
(4) And (5) analyzing the cost. The manual measurement process is time-consuming and labor-consuming. When the experience of the measuring personnel is insufficient, repeated measurement is often needed for many times, and time and labor are wasted. The method provided by the invention can directly utilize a computer to carry out measurement, and the cost of the invention can be saved.

Claims (7)

1. The automatic detection method for the horizontal angle of the grinding mark of the steel ball grinding spot image is characterized by comprising the following steps of:
step one, after a steel ball friction test is finished, acquiring an abrasion mark image through a scanning electron microscope, and marking the acquired abrasion mark image as F;
secondly, carrying out gray processing on the collected speckle image F by a weighted average method to obtain a gray speckle image F;
thirdly, clockwise rotating the gray scale abrasion pattern f obtained in the second step by theta degrees around the central point O of the image to obtain a rotary abrasion pattern fθHaving a size of mθ×nθ；
The fourth step, using the rotary grinding spot pattern f obtained in the third stepθIs taken as the center, an area is arbitrarily selected as a reference area Aθ；
Fifth step, the rotational wear pattern f obtained in the third stepθIn the central horizontal direction, with reference to the reference area AθAs the center, symmetrically selecting and referencing areas A to both sidesθSize and breadthS area blocks having the same shape as the contrast area DθObtaining 2s contrast areas in total;
sixthly, respectively calculating the comparison areas DθThe k-th contrast region of
Figure FDA0002684891540000011
And a contrast area
Figure FDA0002684891540000012
The adjacent eight-direction area blocks and the reference area AθThe gray difference between the two images is obtained, and the minimum value of the nine obtained gray differences is taken as a contrast area
Figure FDA0002684891540000013
And a reference area AθDegree of difference of (2)
Figure FDA0002684891540000014
Seventhly, calculating all the contrast areas D under the same direction angle thetaθAnd a reference area AθAnd the sum of the obtained degrees of difference is taken as the degree of difference C of the grinding mark at the direction angle thetaθ；
Calculating the wear scar difference C under the direction angle theta according to the formula (3)θ：
Figure FDA0002684891540000015
Eighth step, according to the difference degree C of the grinding marks obtained in the seventh stepθCalculating the horizontal angle of the grinding spot and the grinding scar
Figure FDA0002684891540000018
Horizontal angle of grinding mark
Figure FDA0002684891540000016
The calculation formula (c) is as follows:
Figure FDA0002684891540000017
2. the method for automatically detecting the horizontal angle of the grinding mark of the steel ball grinding spot image as claimed in claim 1, wherein the method comprises the following steps: in the first step, the pixel size of the speckle image F is mxn, the coordinate of any pixel point of the speckle image F is (x, y), x and y respectively represent the row and column of the pixel point, x and y are integers, x is greater than or equal to 1 and less than or equal to m, and y is greater than or equal to 1 and less than or equal to n.
3. The method for automatically detecting the horizontal angle of the grinding mark of the steel ball grinding spot image as claimed in claim 1, wherein the method comprises the following steps: in the second step, the gray value of the pixel point (x, y) in the obtained gray speckle pattern f is f (x, y), and the calculation formula of f (x, y) is as follows:
f(x，y)＝0.299×R(x，y)+0.587×G(x，y)+0.144×B(x，y) (1)
wherein, R (x, y), G (x, y), B (x, y) respectively represent red R, green G, blue B component values of the pixel point (x, y) in the scrub pattern F.
4. The method for automatically detecting the horizontal angle of the grinding mark of the steel ball grinding spot image as claimed in claim 1, wherein the method comprises the following steps: in the fourth step, the reference region AθIs a square of 2 omega +1 pixels on a side, the area of which
Figure FDA0002684891540000021
Is of a size of
Figure FDA0002684891540000022
Wherein, the value range of omega is 3-20.
5. The method for automatically detecting the horizontal angle of the grinding mark of the steel ball grinding spot image as claimed in claim 1, wherein the method comprises the following steps: in the fifth step, a contrast area D is selectedθWhen the positions of two adjacent area blocks are partially overlapped or not overlapped.
6. The method for automatically detecting the horizontal angle of the grinding mark of the steel ball grinding spot image as claimed in claim 5, wherein the method comprises the following steps: in the fifth step, the distance between the center points of two adjacent area blocks is 2 ω + 1.
7. The method for automatically detecting the horizontal angle of the grinding mark of the steel ball grinding spot image as claimed in claim 1, wherein the method comprises the following steps: sixth, comparing the regions
Figure FDA0002684891540000023
And a reference area AθDegree of difference of (2)
Figure FDA0002684891540000024
The calculating method of (2): comparing the regions
Figure FDA0002684891540000025
Slightly moving 1 pixel in eight directions of upper left, upper right, upper left, right, lower left, lower right and lower right, respectively calculating the contrast area according to the formula (2)
Figure FDA0002684891540000026
The gray level difference of eight adjacent directional area blocks takes the minimum value of nine gray level differences as the contrast area
Figure FDA0002684891540000027
And a reference area AθDegree of difference of (2)
Figure FDA0002684891540000028
Figure FDA0002684891540000029
Wherein i and j are integers and are respectively contrast areas
Figure FDA00026848915400000210
And a reference area AθThe row number and column number of the pixel coordinates,
Figure FDA0002684891540000031
alpha and beta are respectively contrast regions
Figure FDA0002684891540000032
A fine shift amount in the row direction and the column direction of (a) ═ 1,0,1, β ═ 1,0, 1; k is a contrast region
Figure FDA0002684891540000033
The number of (2); a. theθ(i, j) is a reference region AθThe gray value of the middle pixel point (i, j),
Figure FDA0002684891540000034
as a contrast region
Figure FDA0002684891540000035
And the gray value of the middle pixel point (i + alpha, j + beta + k (2 omega + 1)).
CN201710597205.6A 2017-07-20 2017-07-20 Automatic detection method for horizontal angle of grinding mark of steel ball grinding spot image Expired - Fee Related CN107392899B (en)

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