Parallel flat plate parallelism measuring method

Abstract

The invention discloses a method for measuring the parallelism of a parallel plate. The method comprises the following steps: S1, collecting self-interference fringes of the parallel plate through an interferometer; s2, preprocessing the collected self-interference fringes, and filtering noise in a fringe pattern by using median filtering; s3, performing segmentation processing on the image by using a region growing algorithm; and S4, counting the number of bright fringes by using a connected region algorithm so as to calculate the parallelism. A to-be-tested sample is placed on a workbench, an interferometer light path is adjusted to collect a self-interference fringe pattern of the to-be-tested sample, the self-interference fringe pattern is processed, image segmentation is carried out on the self-interference fringe pattern of a parallel plate by utilizing a region growing algorithm, and the self-interference fringe pattern of the to-be-tested sample is obtained. The number of bright fringes after image segmentation is counted through a connected region algorithm, then the parallelism of the sample to be measured is measured, and the method is suitable for measurement of the parallel plate with the good parallelism and is high in measurement precision.

Description

Technical Field

[0001] The invention relates to the field of measurement technology, and in particular to a method for measuring the parallelism of a parallel plate. Background Art

[0002] In the manufacture of optical and electronic equipment, glass parallel plates or optical parts equivalent to parallel plates composed of two planes are often used, and these optical parts have high requirements for parallelism. Parallelism measurement is not only a key link in the manufacturing process, but also one of the means to ensure product quality, improve production efficiency and reliability. Therefore, it is very necessary to measure parallelism.

[0003] At present, the common method for measuring parallelism is to generate a light spot after the light beam is irradiated to the sample to be measured, and the parallelism is judged according to the position of the light spot. When the two surfaces are parallel, the two light spots completely overlap; when the two surfaces are not parallel, the positions of the two light spots may be intersecting, separated or tangent. The distance between the centers of the two light spots is solved by image processing methods, and the angle between the two planes, i.e., the parallelism, can be calculated based on the distance between the centers of the two light spots. However, the method of measuring parallelism using the position of the light spot is suitable for two planes with large parallelism, and the measurement error is large (the error is 2'), which has limitations for the measurement of parallel plates with high requirements for parallelism.

[0004] In view of this, it is necessary to design a parallel plate parallelism measurement method to overcome the above defects. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art.

[0006] To this end, the present invention provides a parallel plate parallelism measurement method, which is suitable for measuring parallel plates with good parallelism and has high measurement accuracy.

[0007] According to a first aspect of the present invention, a method for measuring the parallelism of a parallel plate comprises the following steps: S1, collect parallel plate self-interference fringes through interferometer; S2, preprocessing the collected self-interference fringes and filtering out the noise in the fringe pattern by using median filtering; S3, using region growing algorithm to segment the image; S4. Use the connected area algorithm to count the number of bright fringes to calculate the parallelism.

[0008] Preferably, the self-interference fringes are obtained by detecting a sample to be measured via a measuring device, and the measuring device at least comprises a laser, a beam expander, an aperture, a beam splitter, a collimator, an imaging lens, a CCD and a computer.

[0009] Further preferably, the laser, beam expander, aperture, beam splitter and collimator are all on the same horizontal plane, the sample to be tested is suitable for being placed on a workbench, and if there is an inclination angle between the front and rear surfaces of the sample to be tested placed on the workbench, the self-interference fringes are formed on the CCD.

[0010] Preferably, when using median filtering to filter out noise in the fringe pattern, the median filtering is centered on each pixel in the self-interference fringe pattern, selects a 3×3 filter window, sorts the grayscale values ​​of the 9 pixels in the window, and takes the middle value as the grayscale value of the pixel.

[0011] Further preferably, when the image is segmented using a region growing algorithm, the following steps are used to extract the region of interest: S31, selecting a suitable initial seed point; S32, traverse the entire image and find the pixel points with the maximum and minimum grayscale values; S33, taking the pixel points with the maximum and minimum grayscale values ​​as initial seed points for region growing, so as to accurately capture the main part of the stripes; S34: After obtaining the initial seed point, determine whether to merge the surrounding pixels into the current growth area based on the difference in grayscale values ​​between pixels.

[0012] Preferably, whether to merge surrounding pixels into the current growth area is determined by using the following calculation formula:

[0013] In the formula, is the gray value of the pixel to be judged, is the initial seed point pixel value, is the set grayscale threshold.

[0014] Further preferably, when selecting the threshold, multiple interference fringe images are tested, the regional growth effect is observed, and the threshold value is gradually adjusted. When the set threshold can completely separate the interference fringes, the threshold at this time is the optimal value.

[0015] Preferably, an eight-neighborhood growth method is selected when performing region growing. The eight-neighborhood refers to eight adjacent pixels above, below, left, right, and diagonally of the current pixel. The region growing rules based on the eight-neighborhood are as follows: S1' determines the seed point, traverses the entire image, finds the first pixel point that has not grown, takes the pixel point as the center, and determines whether the pixel values ​​of the eight neighborhoods of the pixel point meet the growth condition (the difference between the pixel value and the seed point pixel value is less than the set threshold). If so, the point is marked as "1"; S2' uses the newly grown point as a new seed point and repeats S1'; S3' continues until the entire image is traversed and the growth is terminated.

[0016] Further preferably, after the image is segmented using a region growing algorithm, the self-interference fringes are divided into black and white parts, and the image is scanned using a connected region analysis. According to the eight-connected analysis, the number of all connected regions marked as "1" in the image is counted, which is the number of bright fringes in the interference fringe diagram. The parallelism is calculated by counting the number of interference fringes within the measurement aperture: , In the formula, is the angle conversion value in seconds. , is the thickness of the test piece, is the refractive index of the sample to be tested, is the wavelength of the light source, m is the number of interference fringes, and D is the measurement aperture.

[0017] The beneficial effects of the present invention are as follows: by placing a sample to be tested on a workbench and adjusting the interferometer optical path to collect the self-interference fringe pattern of the sample to be tested, the self-interference fringe pattern is processed, the self-interference fringe pattern of the parallel plate is image segmented by using a region growing algorithm, and the number of bright fringes after image segmentation is counted by using a connected region algorithm, thereby realizing the measurement of the parallelism of the sample to be tested. The method is suitable for the measurement of parallel plates with good parallelism and has high measurement accuracy.

[0018] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0019] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0021] Figure 1 A structural diagram of a measuring device for a parallel plate parallelism measuring method of the present invention; Figure 2 Schematic diagram of the process of measuring the parallelism of parallel plates of the present invention; Figure 3 A flow chart of a method for segmenting an image using a region growing algorithm; Figure 4 Schematic diagram of the method flow of the region growing rule based on 8 neighborhoods.

[0022] Reference numerals: 1. Laser; 2. Beam expander; 3. Aperture; 4. Beam splitter; 5. Collimator; 6. Sample to be tested; 7. Imaging lens; 8. CCD; 9. Computer. DETAILED DESCRIPTION

[0023] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention. In the description of the present invention, it should be understood that, unless otherwise specified, the meaning of "multiple" is two or more.

[0024] See also Figure 1 to Figure 2 A method for measuring the parallelism of a parallel plate according to a specific embodiment of the present invention comprises the following steps: S1, collect parallel plate self-interference fringes through interferometer; S2, preprocessing the collected self-interference fringes and filtering out the noise in the fringe pattern by using median filtering; S3, using region growing algorithm to segment the image; S4. Use the connected area algorithm to count the number of bright fringes to calculate the parallelism.

[0025] Specifically, the self-interference fringes are detected by a measuring device on a sample 6 to be tested, and the measuring device at least includes a laser 1, a beam expander 2, an aperture 3, a beam splitter 4, a collimator 5, an imaging lens 7, a CCD 8, and a computer 9. Among them, the laser 1, the beam expander 2, the aperture 3, the beam splitter 4, and the collimator 5 are all on the same horizontal plane, and the sample 6 to be tested is suitable for being placed on a workbench. If there is an inclination between the front and rear surfaces of the sample 6 to be tested placed on the workbench, self-interference fringes will be formed on the CCD 8.

[0026] During measurement, the light emitted by the laser 1 is focused on the aperture 3 by the beam expander 2. After the light passes through the aperture 3 and reaches the beam splitter 4, the beam splitter 4 splits the light into two beams, one of which is used as the reference light, and the other is reflected by the sample 6 and then overlaps with the reference light to form interference fringes. When performing parallelism testing, the test piece is placed on the workbench and the self-interference fringes formed by the light reflected from the front and back surfaces of the test piece are used for testing.

[0027] If the front and rear surfaces of the test piece are strictly parallel, an interference field with uniform brightness will be obtained, and no interference fringes will be seen on CCD8; if there is a certain small inclination angle between the front and rear surfaces of the test piece, interference fringes will be seen on CCD8, and then by counting the number of self-interference fringes within the measurement range, the parallelism measurement can be achieved.

[0028] In addition, after the interferometer collects the self-interference fringes of the parallel plates, most of the noise in the interference fringe pattern can be filtered out using the median filter. The median filter takes each pixel in the interference fringe pattern as the center, selects a 3×3 filter window, sorts the grayscale values ​​of the 9 pixels in the window, and takes the middle value as the grayscale value of the pixel.

[0029] Then, see Figure 3 , and then use the region growing algorithm to segment the image, and use the following steps to extract the region of interest: S31, selecting a suitable initial seed point; S32, traverse the entire image and find the pixel points with the maximum and minimum grayscale values; S33, taking the pixel points with the maximum and minimum grayscale values ​​as initial seed points for region growing, so as to accurately capture the main part of the stripes; S34: After obtaining the initial seed point, determine whether to merge the surrounding pixels into the current growth area based on the difference in grayscale values ​​between pixels.

[0030] The following calculation formula is used to determine whether to merge surrounding pixels into the current growth area:

[0031] In the formula, is the gray value of the pixel to be judged, is the initial seed point pixel value, is the set grayscale threshold.

[0032] When selecting the threshold, multiple interference fringe images are tested, the regional growth effect is observed, and the threshold value is gradually adjusted. When the set threshold can completely separate the interference fringes, the threshold at this time is the optimal value.

[0033] It should be noted that see Figure 4 , when performing region growing, the eight-neighborhood growing method is selected. The eight-neighborhood refers to the eight adjacent pixels above, below, left, right, and diagonally of the current pixel. The region growing rules based on the eight-neighborhood are as follows: S1' determines the seed point, traverses the entire image, finds the first pixel point that has not grown, takes the pixel point as the center, and determines whether the pixel values ​​of the eight neighborhoods of the pixel point meet the growth condition (the difference between the pixel value and the seed point pixel value is less than the set threshold). If so, the point is marked as "1"; S2' uses the newly grown point as a new seed point and repeats S1'; S3' continues until the entire image is traversed and the growth is terminated.

[0034] After the image is segmented using the region growing algorithm, the self-interference fringes are divided into black and white parts. The connected region analysis is used to scan the image. According to the eight-connected analysis, the number of all connected regions marked as "1" in the image is counted, which is the number of bright fringes in the interference fringe diagram. The calculation of parallelism is mainly obtained by counting the number of interference fringes within the measurement aperture: , In the formula, is the angle conversion value in seconds. , is the thickness of the test piece, is the refractive index of the sample to be tested, is the wavelength of the light source, m is the number of interference fringes, and D is the measurement aperture.

[0035] Therefore, in summary, through the above measurement steps, the sample to be tested 6 is placed on the workbench, the interferometer optical path is adjusted, the self-interference fringe pattern of the sample to be tested 6 is collected, and the self-interference fringe pattern is preprocessed. In the preprocessing, the median filter is first used to filter out most of the noise in the interference fringe pattern, and then the self-interference fringe pattern is segmented by the region growing algorithm to separate the light and dark fringes (by traversing the entire image, finding the pixel points with the largest and smallest grayscale values, and using them as initial seed points for region growing; by testing multiple interference fringe patterns, observing the region growing effect, and gradually adjusting the threshold value, when the set threshold can completely separate the interference fringes, the value is set as the threshold, and then the entire image is traversed, and the grown seed points are marked as "1", until all pixel points are traversed and the growth stops). Finally, the number of bright fringes is counted using connected region analysis (the image after region growing is a binary image, and then the 8-neighborhood connectivity rule is used to divide the connected regions, traverse all pixels on the image, and count the number of connected regions). The parallelism can be calculated from the number of fringes. This method is suitable for the measurement of parallel plates with good parallelism and has high measurement accuracy.

[0036] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0037] The above description is based on the ideal embodiment of the present invention. Through the above description, relevant personnel can make various changes and modifications without departing from the technical concept of the present invention. The technical scope of the present invention is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A method for measuring the parallelism of a parallel plate, characterized in that: The following steps are involved: S1, collect parallel plate self-interference fringes through interferometer; S2, preprocessing the collected self-interference fringes and filtering out the noise in the fringe pattern by using median filtering; S3, using region growing algorithm to segment the image; S4. Use the connected area algorithm to count the number of bright fringes to calculate the parallelism.

2. The parallelism measurement method of parallel plates according to claim 1, characterized in that: The self-interference fringes are obtained by detecting a sample to be measured (6) via a measuring device, wherein the measuring device comprises at least a laser (1), a beam expander (2), an aperture (3), a beam splitter (4), a collimator (5), an imaging lens (7), a CCD (8) and a computer (9).

3. The parallelism measurement method of parallel plates according to claim 2, characterized in that: The laser (1), the beam expander (2), the aperture (3), the beam splitter (4) and the collimator (5) are all located on the same horizontal plane. The sample to be tested (6) is suitable for being placed on a workbench. If there is an inclination angle between the front and rear surfaces of the sample to be tested (6) placed on the workbench, the self-interference fringes are formed on the CCD.

4. The parallelism measurement method of parallel plates according to claim 3, characterized in that: When using median filtering to filter out noise in the fringe pattern, the median filtering takes each pixel in the self-interference fringe pattern as the center, selects a 3×3 filtering window, sorts the grayscale values ​​of the 9 pixels in the window, and takes the middle value as the grayscale value of the pixel.

5. The parallelism measurement method of parallel plates according to claim 4, characterized in that: When using the region growing algorithm to segment an image, the following steps are used to extract the region of interest: S31, selecting a suitable initial seed point; S32, traverse the entire image and find the pixel points with the maximum and minimum grayscale values; S33, taking the pixel points with the maximum and minimum grayscale values ​​as initial seed points for region growing, so as to accurately capture the main part of the stripes; S34: After obtaining the initial seed point, determine whether to merge the surrounding pixels into the current growth area based on the difference in grayscale values ​​between pixels.

6. The method for measuring the parallelism of parallel plates according to claim 5, characterized in that: To determine whether to merge surrounding pixels into the current growth area, the following calculation formula is used: In the formula, is the gray value of the pixel to be judged, is the initial seed point pixel value, is the set grayscale threshold.

7. The parallelism measurement method of parallel plates according to claim 6, characterized in that: When selecting the threshold, multiple interference fringe images are tested, the regional growth effect is observed, and the threshold value is gradually adjusted. When the set threshold can completely separate the interference fringes, the threshold at this time is the optimal value.

8. The method for measuring the parallelism of parallel plates according to claim 7, characterized in that: When performing region growing, the eight-neighborhood growing method is selected. The eight-neighborhood refers to the eight adjacent pixels above, below, left, right, and diagonally of the current pixel. The region growing rules based on the eight-neighborhood are as follows: S1' determines the seed point, traverses the entire image, finds the first pixel point that has not grown, takes the pixel point as the center, and determines whether the pixel values ​​of the eight neighborhoods of the pixel point meet the growth condition (the difference between the pixel value and the seed point pixel value is less than the set threshold). If so, the point is marked as "1"; S2' uses the newly grown point as a new seed point and repeats S1'; S3' continues until the entire image is traversed and the growth is terminated.

9. The method for measuring the parallelism of parallel plates according to claim 5, characterized in that: After the image is segmented using the region growing algorithm, the self-interference fringes are divided into black and white parts. The image is scanned using the connected region analysis. According to the eight-connected analysis, the number of all connected regions marked as "1" in the image is counted, which is the number of bright fringes in the interference fringe diagram. The parallelism is calculated mainly by counting the number of interference fringes within the measurement aperture. ， In the formula, is the angle conversion value in seconds. , is the thickness of the test piece, is the refractive index of the sample to be tested (6), is the wavelength of the light source, m is the number of interference fringes, and D is the measurement aperture.

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