White light interference effective image extraction method, device, equipment, medium and product

Abstract

The present invention provides a method, device, equipment, medium and product for extracting effective white light interference images, which belongs to the field of precision optical measurement technology. The method includes: evaluating the white light interference image sequence of the sample to be tested based on the grayscale variance function and the grayscale gradient function respectively, obtaining the grayscale variance evaluation curve and the grayscale gradient evaluation curve; determining whether the sample to be tested has a step based on the grayscale variance evaluation curve; when the sample to be tested has a step, determining the step area, and fusing the grayscale variance evaluation curve and the grayscale gradient evaluation curve based on the step area to obtain a fusion evaluation curve; determining the step shape of the step based on the fusion evaluation curve, and determining the number of images of the effective white light interference image based on the white light interference image sequence; determining the effective white light interference image in the white light interference image sequence based on the step shape, the step area and the number of images. The present invention improves the extraction accuracy of the effective white light interference image.

Description

Technical Field

[0001] The present invention relates to the field of precision optical measurement technology, and in particular to a method, device, equipment, medium and product for extracting effective white light interference images. Background Art

[0002] White light interferometry plays an extremely important role in the field of microstructure surface topography measurement. It has the advantages of non-contact, simple operation, fast speed and high precision. White light interferometry is to obtain an interference image with constantly changing fringe contrast by scanning the sample to be measured layer by layer in the vertical direction. When the optical path difference between the sample surface and the reference mirror is zero, the contrast of the generated white light interference fringes is the largest. It is often necessary to collect hundreds of images during measurement, and the images that are truly useful for the topography restoration algorithm are only those near the zero optical path difference position, which are called white light interferometry effective images. Other redundant interference images greatly occupy the computer's storage space and reduce the efficiency of topography measurement.

[0003] With the widespread use of microstructure devices in various industries, the shapes of samples are increasing. In addition to the common vertical step samples, there are also trapezoidal samples. The commonly used white light interference effective extraction method is to use the variance evaluation function for extraction. Since the intensity of the interference fringes on the slope part of the trapezoidal sample is low, the slope is easily misjudged as a vertical step using the variance evaluation function, and the effective interference image is inaccurately selected, resulting in inaccurate restoration of the sample morphology.

[0004] Therefore, there is an urgent need to provide a white light interferometry effective image extraction method, device, equipment, medium and product to achieve accurate extraction of white light interferometry effective images of multi-morphological samples, thereby improving the accuracy of sample morphology restoration. Summary of the invention

[0005] In view of this, it is necessary to provide a white light interferometry effective image extraction method, device, equipment, medium and product to solve the technical problem in the prior art of using variance evaluation function to extract white light interferometry effective images, resulting in inaccurate extracted white light interferometry effective images.

[0006] On the one hand, in order to solve the above technical problems, the present invention provides a white light interference effective image extraction method, comprising:

[0007] Based on the grayscale variance function and the grayscale gradient function, the white light interference image sequence of the sample to be tested is evaluated respectively to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve;

[0008] Determining whether there is a step in the sample to be tested based on the grayscale variance evaluation curve;

[0009] When there is a step in the sample to be tested, determining the step area, and fusing the grayscale variance evaluation curve and the grayscale gradient evaluation curve based on the step area to obtain a fused evaluation curve;

[0010] Determining a step shape of the step based on the fusion evaluation curve, and determining the number of images of white light interference effective images based on the white light interference image sequence;

[0011] A white light interference effective image in the white light interference image sequence is determined based on the step shape, the step area, and the number of images.

[0012] In a possible implementation, determining whether the sample to be tested has a step based on the grayscale variance evaluation curve includes:

[0013] Determining the number of peaks in the grayscale variance evaluation curve;

[0014] When the number of peaks is less than the peak threshold number, the sample to be tested does not have steps, and when the number of peaks is greater than or equal to the peak threshold number, the sample to be tested has steps.

[0015] In a possible implementation manner, determining the number of peaks in the grayscale variance evaluation curve includes:

[0016] Determine a target grayscale variance curve that is greater than a grayscale threshold value in the grayscale variance evaluation curve;

[0017] A target number of peaks in the target grayscale variance curve is determined, and the target number of peaks is used as the number of peaks.

[0018] In a possible implementation, when the sample to be tested has a step, determining the step area, and fusing the grayscale variance evaluation curve and the grayscale gradient evaluation curve based on the step area to obtain a fused evaluation curve, including:

[0019] When there is a step in the sample to be tested, determining the step area based on the grayscale variance evaluation curve;

[0020] Determine a gradient target curve segment in the grayscale gradient evaluation curve and a variance target curve segment in the grayscale variance evaluation curve based on the step region;

[0021] The variance target curve segment is replaced by the gradient target curve segment to obtain the fusion evaluation curve.

[0022] In a possible implementation manner, determining the step area based on the grayscale variance evaluation curve includes:

[0023] Determine the upper surface zero optical path difference position and the lower surface zero optical path difference position of the step based on the grayscale variance evaluation curve;

[0024] Acquire the image sequence number of the upper surface of the step corresponding to the zero optical path difference position of the upper surface and the image sequence number of the lower surface of the step corresponding to the zero optical path difference position of the lower surface;

[0025] The white light interference image between the image serial number of the upper surface of the step and the image serial number of the lower surface of the step is used as the step area.

[0026] In a possible implementation, determining the upper surface zero optical path difference position and the lower surface zero optical path difference position of the step based on the grayscale variance evaluation curve includes:

[0027] Determining a first zero optical path difference position and a second zero optical path difference position of the step based on the grayscale variance evaluation curve;

[0028] Acquiring the moving direction of the interference objective lens when acquiring the white light interference image sequence;

[0029] The upper surface zero optical path difference position and the lower surface zero optical path difference position are determined based on the movement direction of the interference objective lens, the first zero optical path difference position, and the second zero optical path difference position.

[0030] In a possible implementation manner, determining the step shape of the step based on the fusion evaluation curve includes:

[0031] Determine a target fusion curve segment in the fusion evaluation curve based on the step area;

[0032] Determine whether the sampling values ​​of the target fusion curve segment are all greater than a sampling threshold;

[0033] When the sampling values ​​of the target fusion curve segment are all greater than the sampling threshold, the step shape of the sample to be tested is a trapezoid;

[0034] When the sampling values ​​of the target fusion curve segment are not all greater than the sampling threshold, the step shape of the sample to be tested is a vertical step.

[0035] In a possible implementation manner, determining the number of images of white light interference effective images based on the white light interference image sequence includes:

[0036] Acquiring the equivalent wavelength of the white light interference image sequence;

[0037] determining a coherence length and a scanning step size based on the equivalent wavelength;

[0038] The number of images of the white light interference effective image is determined based on the coherence length and the scanning step length.

[0039] In a possible implementation, the number of images of the white light interference effective image is:

[0040]

[0041]

[0042]

[0043] In the formula, is the number of images of the white light interference image; is the coherence length; is the scanning step length; is the equivalent wavelength; is the spectral width of the light source.

[0044] In a possible implementation, when the step shape of the sample to be tested is a trapezoid, the image number range of the effective white light interference image is to ;

[0045] In the formula, is the starting image sequence number of the step area; is the ending image sequence number of the step area; is the number of images of the effective white light interference image.

[0046] In a possible implementation, when the step shape of the sample to be tested is a vertical step, determining the white light interference effective image based on the number of images of the white light interference effective image, the step area, and the step shape of the sample to be tested includes:

[0047] Determine a reference fusion curve segment whose sampling value of the target fusion curve segment is less than the sampling threshold;

[0048] Determine the starting white light interference image sequence number and the ending white light interference image sequence number of the reference fusion curve segment;

[0049] The white light interference effective image is determined based on the image quantity of the white light interference effective image, the step area, the starting white light interference image sequence number and the ending white light interference image sequence number.

[0050] In a possible implementation, when the step shape of the sample to be tested is a vertical step, the image number range of the effective white light interference image is to ,as well as to ;

[0051] In the formula, is the starting white light interference image serial number; is the sequence number of the terminated white light interference image.

[0052] In a possible implementation manner, the grayscale gradient function is a Tenengrad function.

[0053] In a possible implementation, the grayscale variance function is:

[0054]

[0055] The gray gradient function is:

[0056]

[0057]

[0058]

[0059] In the formula, is the image sequence number; is the total number of image rows; is the total number of image columns; For the image Grayscale value of the pixel.

[0060] In a possible implementation, the white light interference image sequence of the sample to be tested is evaluated based on the grayscale variance function and the grayscale gradient function to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve, including:

[0061] Based on the grayscale variance function and the grayscale gradient function, the white light interference image sequence of the sample to be tested is evaluated respectively to obtain an initial grayscale variance evaluation curve and an initial grayscale gradient evaluation curve;

[0062] The initial grayscale variance evaluation curve and the initial grayscale gradient evaluation curve are normalized to obtain the grayscale variance evaluation curve and the grayscale gradient evaluation curve.

[0063] In a possible implementation, after the initial grayscale variance evaluation curve and the initial grayscale gradient evaluation curve are normalized to obtain the grayscale variance evaluation curve and the grayscale gradient evaluation curve, the method further includes:

[0064] The grayscale variance evaluation curve is subjected to denoising processing.

[0065] On the other hand, the present invention also provides a white light interference effective image extraction device, comprising:

[0066] An image evaluation curve acquisition unit is used to evaluate the white light interference image sequence of the sample to be tested based on the grayscale variance function and the grayscale gradient function, respectively, to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve;

[0067] A step determination unit, used for determining whether there is a step in the sample to be tested based on the grayscale variance evaluation curve;

[0068] An evaluation curve fusion unit, used for determining a step area when there is a step in the sample to be tested, and fusing the grayscale variance evaluation curve and the grayscale gradient evaluation curve based on the step area to obtain a fused evaluation curve;

[0069] A related parameter determination unit, configured to determine a step shape of the step based on the fusion evaluation curve, and determine the number of images of the white light interference effective image based on the white light interference image sequence;

[0070] The white light interference effective image determining unit is used to determine the white light interference effective image in the white light interference image sequence based on the step shape, the step area and the number of images.

[0071] On the other hand, the present invention also provides a surface topography measurement device, including a memory and a processor, wherein:

[0072] The memory is used to store programs;

[0073] The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the white light interference effective image extraction method described in any one of the possible implementations above.

[0074] On the other hand, the present invention also provides a computer-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the white light interference effective image extraction method described in any possible implementation method mentioned above are implemented.

[0075] On the other hand, the present invention also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the white light interference effective image extraction method described in any possible implementation manner described above.

[0076] The beneficial effects of the present invention are as follows: the white light interference effective image extraction method provided by the present invention evaluates the white light interference image sequence of the sample to be tested based on the grayscale variance function and the grayscale gradient function respectively, and can accurately determine the position of zero optical path difference through the grayscale variance function, and accurately determine whether there is a step in the sample to be tested. When there is a step in the sample to be tested, the grayscale variance evaluation curve and the grayscale gradient evaluation curve are fused to obtain a fused evaluation curve, and the fused evaluation curve has both the accuracy of the grayscale variance evaluation curve in determining the position of zero optical path difference and the obvious characterization of the slope part of the trapezoidal sample by the grayscale gradient evaluation curve. Therefore, the shape of the step can be accurately determined based on the fused evaluation curve, and the white light interference effective image can be determined based on the shape of the step. The white light interference effective image required for reconstructing the step can be accurately determined, and redundant images can be avoided from being obtained, and white light interference effective images can be avoided from being missed, thereby further improving the accuracy of the determined white light interference effective image. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0078] Figure 1 A schematic diagram of an embodiment of the white light interference effective image extraction method provided by the present invention;

[0079] Figure 2 For the present invention Figure 1 A schematic flow chart of an embodiment of S102;

[0080] Figure 3 For the present invention Figure 2 A schematic flow chart of an embodiment of S201;

[0081] Figure 4 For the present invention Figure 1 A schematic flow chart of an embodiment of S103;

[0082] Figure 5 For the present invention Figure 4 A schematic flow chart of an embodiment of S401;

[0083] Figure 6 For the present invention Figure 5 A schematic flow chart of an embodiment of S501;

[0084] Figure 7 For the present invention Figure 1 A schematic flow chart of an embodiment of determining the number of images of the effective white light interference image in S104;

[0085] Figure 8 For the present invention Figure 1 A schematic flow chart of an embodiment of determining the step shape of a step based on the fused evaluation curve in S104;

[0086] Fig. 9 For the present invention Figure 1 A schematic flow chart of an embodiment of S105;

[0087] Fig.10 For the present invention Figure 1 A schematic flow chart of an embodiment of S101;

[0088] Fig.11 A schematic diagram of an embodiment of a grayscale variance evaluation curve and a grayscale gradient evaluation curve provided by the present invention;

[0089] Fig.12 A schematic diagram of an embodiment of a fusion evaluation curve provided by the present invention;

[0090] Fig.13 A schematic diagram of the structure of an embodiment of the white light interference effective image extraction device provided by the present invention;

[0091] Fig.14 A schematic structural diagram of an embodiment of the surface topography measurement device provided by the present invention. DETAILED DESCRIPTION

[0092] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0093] It should be understood that the schematic drawings are not drawn to scale. The flowchart used in the present invention shows the operations implemented according to some embodiments of the present invention. It should be understood that the operations of the flowchart can be implemented out of order, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art, under the guidance of the content of the present invention, can add one or more other operations to the flowchart, and can also remove one or more operations from the flowchart. Some of the block diagrams shown in the accompanying drawings are functional entities, which do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor systems and / or microcontroller systems.

[0094] Reference to an "embodiment" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0095] The present invention provides a white light interference effective image extraction method, device, equipment, medium and product, which are described below respectively.

[0096] Before presenting the embodiments, the technical principle of three-dimensional topography measurement using white light interferometry is introduced.

[0097] White light interferometry is an optical instrument that uses the interference principle to measure the optical path difference and determine the three-dimensional topography. Specifically: any change in the optical path difference between two coherent light beams will very sensitively cause the movement of interference fringes, and the change in the optical path of a coherent light beam is caused by the change in the geometric path it passes through or the refractive index of the medium, so the movement of the interference fringes can measure the slight change in geometric length, thereby measuring the three-dimensional topography.

[0098] Figure 1 A schematic flow chart of an embodiment of the white light interference effective image extraction method provided by the present invention is as follows: Figure 1 As shown, the white light interference effective image extraction method includes:

[0099] S101, evaluating the white light interference image sequence of the sample to be tested based on the grayscale variance function and the grayscale gradient function, respectively, to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve;

[0100] S102, determining whether there is a step in the sample to be tested based on the grayscale variance evaluation curve;

[0101] S103, when there is a step in the sample to be tested, determine the step area, and fuse the grayscale variance evaluation curve and the grayscale gradient evaluation curve based on the step area to obtain a fused evaluation curve;

[0102] S104, determining the step shape of the step based on the fusion evaluation curve, and determining the number of images of the white light interference effective image based on the white light interference image sequence;

[0103] S105 . Determine a white light interference effective image in the white light interference image sequence based on the step shape, the step area, and the number of images.

[0104] The grayscale gradient function in step S101 may be any one of a Brenner gradient function, a Tenengrad gradient function, and a Laplacian gradient function.

[0105] It should be noted that the step area in step S104 refers to all white light interference images between the step start position and the step end position.

[0106] It has been verified that the Tenengrad gradient function has a more obvious characteristic representation of the trapezoidal steps. Therefore, in a specific embodiment of the present invention, the grayscale gradient function in step S101 is the Tenengrad gradient function.

[0107] In a specific embodiment of the present invention, the grayscale variance function is expressed as:

[0108]

[0109] The expression of gray gradient function is:

[0110]

[0111]

[0112]

[0113] In the formula, is the image sequence number; is the total number of image rows; is the total number of image columns; For the image Grayscale value of the pixel.

[0114] It should be understood that: the white light interference image sequence in step S101 can be obtained based on a white light interferometer. Specifically, the measurement principle of the white light interferometer is: the illumination light beam emitted by the white light source is divided into two beams of light by a semi-reflective and semi-transmissive beam splitter, one beam of light is projected onto the surface of the reference mirror, and the other beam of light is projected onto the sample to be measured through the interference objective lens. The two beams of light reflected from the two surfaces are synthesized into one beam of light after passing through the beam splitter again, and a white light interference image is generated on the photosensitive surface of the CCD camera by the optical imaging system. The reference mirror is driven up and down by a driving device to change the optical path between the two beams of light, and a white light interference image sequence is obtained accordingly.

[0115] It should also be noted that the basic principle of step S102 is that the grayscale variance evaluation curve is a curve used to describe the degree of grayscale change in an image. When there are steps in the image, the degree of grayscale change at the starting and ending positions of the steps should be large. Therefore, the grayscale variance curve can be used to detect whether there are steps.

[0116] Compared with the prior art, the white light interference effective image extraction method provided by the embodiment of the present invention evaluates the white light interference image sequence of the sample to be tested based on the grayscale variance function and the grayscale gradient function respectively, and can accurately determine the position of zero optical path difference through the grayscale variance function, and accurately determine whether there is a step in the sample to be tested. When there is a step in the sample to be tested, the grayscale variance evaluation curve and the grayscale gradient evaluation curve are fused to obtain a fused evaluation curve. The fused evaluation curve has both the accuracy of the grayscale variance evaluation curve in determining the zero optical path difference position and the obvious characterization of the grayscale gradient evaluation curve in the slope part of the trapezoidal sample. Therefore, the shape of the step can be accurately determined based on the fused evaluation curve, and the white light interference effective image can be determined based on the shape of the step. The white light interference effective image required for reconstructing the step can be accurately determined, and redundant images can be avoided. And the white light interference effective image can be avoided from being missed, and the accuracy of the determined white light interference effective image is further improved.

[0117] The step refers to the presence of a protrusion in the sample to be tested, which includes the starting position of the protrusion and the ending position of the protrusion, which is represented by a peak in the grayscale variance evaluation curve. Therefore, in some embodiments of the present invention, Figure 2 As shown, step S102 includes:

[0118] S201, determining the number of peaks in the grayscale variance evaluation curve;

[0119] S202. When the number of peaks is less than the peak threshold number, there is no step in the sample to be tested; when the number of peaks is greater than or equal to the peak threshold number, there is a step in the sample to be tested.

[0120] Since the step includes a step start position and a step end position, in a specific embodiment of the present invention, the number of peak thresholds is 2.

[0121] Since the step refers to a relatively large protrusion, in order to avoid the adverse effect of the tiny protrusion caused by the manufacturing accuracy on the determination of whether the step exists, in some embodiments of the present invention, such as Figure 3 As shown, step S201 includes:

[0122] S301, determining a target grayscale variance curve that is greater than a grayscale threshold value in a grayscale variance evaluation curve;

[0123] S302, determining the target peak number in the target grayscale variance curve, and taking the target peak number as the peak number.

[0124] The embodiment of the present invention sets a target grayscale variance curve that is greater than the grayscale threshold in the grayscale variance evaluation curve based on the grayscale threshold, and performs peak number statistics in the target grayscale variance curve, that is, ensuring that the determined peak number is the peak value representing the step, so as to improve the accuracy of judging whether there is a step in the sample to be tested.

[0125] It should be understood that the grayscale threshold can be set or adjusted according to the actual application scenario. In a specific embodiment of the present invention, the grayscale threshold range is 0.15-0.25, and specifically, the grayscale threshold is 0.2.

[0126] In some embodiments of the present invention, Figure 4 As shown, step S103 includes:

[0127] S401, when there is a step in the sample to be tested, determining the step area based on the grayscale variance evaluation curve;

[0128] S402, determining a gradient target curve segment in a grayscale gradient evaluation curve and a variance target curve segment in a grayscale variance evaluation curve based on the step region;

[0129] S403: Replace the variance target curve segment with the gradient target curve segment to obtain a fusion evaluation curve.

[0130] The gradient target curve segment and the variance target curve segment in step S402 refer to the curve segments corresponding to the step areas in the grayscale gradient evaluation curve and the grayscale variance evaluation curve.

[0131] The embodiment of the present invention determines the step area based on the grayscale variance evaluation curve. The grayscale variance evaluation function can be used to accurately determine the characteristics of the plane zero optical path difference position and accurately determine the step area. After determining the step area, the gradient target curve segment is used to replace the variance target curve segment to obtain a fusion evaluation curve. The sensitivity of the grayscale gradient function to the gradient slope characteristics can be used to realize accurate judgment of the step shape.

[0132] Since accurate upper and lower surface of the step are required when reconstructing the three-dimensional morphology based on the effective image of white light reflection, in a specific embodiment of the present invention, Figure 5 As shown, step S401 includes:

[0133] S501, determining the upper surface zero optical path difference position and the lower surface zero optical path difference position of the step based on the grayscale variance evaluation curve;

[0134] S502, obtaining the image serial number of the upper surface of the step corresponding to the position of zero optical path difference on the upper surface and the image serial number of the lower surface of the step corresponding to the position of zero optical path difference on the lower surface;

[0135] S503 , taking the white light interference image between the image serial number of the upper surface of the step and the image serial number of the lower surface of the step as the step region.

[0136] The embodiment of the present invention can provide a reference for subsequent three-dimensional shape reconstruction by determining the upper surface zero optical path difference position and the lower surface zero optical path difference position of the step based on the grayscale variance evaluation curve, thereby achieving accurate reconstruction of the three-dimensional shape.

[0137] Specifically, if the image number of the upper surface of the step is 200 and the image number of the lower surface of the step is 500, then the step area is all white light interference images with image numbers of 200-500.

[0138] Since the upper and lower surfaces of the step cannot be determined only by the grayscale variance evaluation curve, in order to solve this technical problem, in a specific embodiment of the present invention, Figure 6 As shown, step S501 includes:

[0139] S601, determining a first zero optical path difference position and a second zero optical path difference position of a step based on a grayscale variance evaluation curve;

[0140] S602, obtaining the moving direction of the interference objective lens when acquiring the white light interference image sequence;

[0141] S603 , determining the upper surface zero optical path difference position and the lower surface zero optical path difference position based on the moving direction of the interference objective lens, the first zero optical path difference position and the second zero optical path difference position.

[0142] The embodiment of the present invention determines the upper surface and the lower surface in the first zero optical path difference position and the second zero optical path difference position based on the movement direction of the interference objective lens when acquiring the white light interference image sequence, thereby ensuring the accuracy of the upper surface zero optical path difference position and the lower surface zero optical path difference position.

[0143] Among them, when the interference objective lens moves from top to bottom, the first zero optical path difference position is the zero optical path difference position on the upper surface, and the second zero optical path difference position is the zero optical path difference position on the lower surface; when the reflection objective lens moves from bottom to top, the first zero optical path difference position is the zero optical path difference position on the lower surface, and the second zero optical path difference position is the zero optical path difference position on the upper surface.

[0144] In a specific embodiment, if the movement direction of the interference objective lens is from top to bottom, when the image number of the first zero optical path difference position is 200 and the image number of the second zero optical path difference position is 500, the position with image number 200 is the zero optical path difference position of the upper surface, and the position with image number 500 is the zero optical path difference position of the lower surface.

[0145] In a specific embodiment of the present invention, Figure 7 As shown, the step S104 of determining the number of images of the effective white light interference images based on the white light interference image sequence includes:

[0146] S701, obtaining an equivalent wavelength of a white light interference image sequence;

[0147] S702, determining the coherence length and the scanning step length based on the equivalent wavelength;

[0148] S703 , determining the number of images of the white light interference effective image based on the coherence length and the scanning step length.

[0149] It should be noted that the equivalent wavelength refers to the wavelength obtained after calibrating the nominal wavelength in the white light interferometer. For example, when the nominal wavelength is 600nm, the actual wavelength after calibration is 546nm, then the equivalent wavelength is 546nm.

[0150] In a specific embodiment of the present invention, the number of images of the white light interference effective image is:

[0151]

[0152]

[0153]

[0154] In the formula, is the number of images of the white light interference image; is the coherence length; is the scanning step length; is the equivalent wavelength; is the spectral width of the light source.

[0155] In a specific embodiment of the present invention, when the equivalent wavelength =546mm, the scanning step length is 68.25mm, and the spectral width of the light source is 62.4mm, then the number of images of the white light interference image is 70.

[0156] In some embodiments of the present invention, Figure 8 As shown, determining the step shape of the step based on the fused evaluation curve in step S104 includes:

[0157] S801, determining a target fusion curve segment in a fusion evaluation curve based on a step region;

[0158] S802, determining whether the sampling values ​​of the target fusion curve segment are all greater than the sampling threshold;

[0159] S803, when the sampling values ​​of the target fusion curve segment are all greater than the sampling threshold, the step shape of the sample to be tested is a trapezoid;

[0160] S804: When the sampling values ​​of the target fusion curve segment are not all greater than the sampling threshold, the step shape of the sample to be tested is a vertical step.

[0161] The embodiment of the present invention can accurately determine the step shape of the sample to be tested by judging the sampling value and sampling threshold of the target fusion curve segment, and then can extract the white light interferometry effective image under different step shapes, thereby improving the applicability of the white light interferometry effective image extraction method to multi-morphological samples and improving the extraction accuracy of the white light interferometry effective image.

[0162] The target fusion curve segment in step S801 is the curve segment within the image number range corresponding to the step region in the fusion evaluation curve. For example, if the fusion evaluation curve includes images 1-700, when the step region is the image number of 200-500, the target fusion curve segment is the fusion evaluation curve segment corresponding to the image number of 200-500.

[0163] When the sampling values ​​of the target fusion curve segment are all greater than the sampling threshold, it means that the slope of the target fusion curve segment changes continuously, that is, the step shape of the sample to be tested is a trapezoid. When the sampling values ​​of the target fusion curve segment are not all greater than the sampling threshold, it means that the slope of the target fusion curve segment does not change continuously, and there is a mutation, that is, the step shape of the sample to be tested is a vertical step.

[0164] In a specific embodiment of the present invention, when the step shape of the sample to be tested is a trapezoid, the image number range of the effective white light interference image is to ;

[0165] In the formula, is the starting image number of the region; is the ending image number of the step area; is the number of images of the effective white light interference image.

[0166] Specifically, is the image serial number on the step surface; is the image number of the lower surface of the step.

[0167] The embodiment of the present invention can improve the reliability of the determined white light interference effective image and avoid missing the white light interference effective image by expanding the step area determined based on the grayscale variance function based on the number of images of the white light interference effective image.

[0168] It should be noted that when the number of images of the white light interference effective image is an odd number, there are two processing methods. One is to extract one more white light interference image from the upper surface or the lower surface of the step as the white light interference effective image. The other is to add one to the number of images of the odd number of white light interference effective images to make it an even number, and then symmetrically divide it to obtain the image sequence number range of the white light interference effective image.

[0169] In some embodiments of the present invention, when the step shape of the sample to be tested is a vertical step, Fig. 9 As shown, step S105 is specifically as follows:

[0170] S901, determining a reference fusion curve segment whose sampling value of the target fusion curve segment is less than a sampling threshold;

[0171] S902, determining the starting white light interference image sequence number and the ending white light interference image sequence number of the reference fusion curve segment;

[0172] S903 , determining a white light interference effective image based on the number of images of the white light interference effective image, the step area, the starting white light interference image sequence number and the ending white light interference image sequence number.

[0173] The embodiment of the present invention can obtain the starting and ending positions of the vertical step by referring to the starting white light interference image sequence number and the ending white light interference image sequence number of the fused curve segment, thereby ensuring accurate extraction of the white light interference effective image of the vertical step.

[0174] It should be understood that the sampling threshold can be set or adjusted according to the actual application scenario. In a specific embodiment of the present invention, the sampling threshold ranges from 0.15 to 0.35, and specifically, the sampling threshold is 0.2.

[0175] In a specific embodiment of the present invention, when the step shape of the sample to be tested is a vertical step, the image number range of the effective white light interference image is to ,as well as to ;

[0176] In the formula, is the starting white light interference image serial number; The sequence number for terminating the white light interference image.

[0177] Since the grayscale variance function and the grayscale gradient function have different operators, in the subsequent processing, the grayscale variance evaluation curve and the grayscale gradient evaluation curve need to be fused. In order to avoid errors in the statistical distribution analysis of the fused curve due to inconsistent orders of magnitude, in some embodiments of the present invention, Fig.10 As shown, step S101 includes:

[0178] S1001, evaluating the white light interference image sequence of the sample to be tested based on the grayscale variance function and the grayscale gradient function, respectively, to obtain an initial grayscale variance evaluation curve and an initial grayscale gradient evaluation curve;

[0179] S1002 , normalizing the initial grayscale variance evaluation curve and the initial grayscale gradient evaluation curve to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve.

[0180] The embodiment of the present invention obtains a grayscale variance evaluation curve and a grayscale gradient evaluation curve by normalizing the initial grayscale variance evaluation curve and the initial grayscale gradient evaluation curve, thereby achieving consistency between the grayscale variance evaluation curve and the grayscale gradient evaluation curve, and thus improving the accuracy of subsequent analysis.

[0181] The purpose of normalization is to limit the value range of the grayscale variance evaluation curve and the grayscale gradient evaluation curve to between (0, 1).

[0182] In a specific embodiment of the present invention, when the grayscale gradient evaluation function is the Tenengrad function and the equivalent wavelength is 546 mm, 684 white light interference images are obtained, and the corresponding grayscale variance evaluation curve and grayscale gradient evaluation curve are as follows: Fig.11 As shown by Fig.11 It can be seen that the grayscale variance evaluation curve includes two peaks, and the images corresponding to the two peaks are the 357th and 535th interference images respectively; therefore, there are steps in the sample to be tested. When the interference objective lens moves from bottom to top, it can be seen that the 357th image corresponds to the zero optical path difference position on the lower surface, and the 535th image corresponds to the zero optical path difference position on the upper surface.

[0183] Since there are steps in the sample, it is necessary to determine whether it is a vertical step or a trapezoidal step. The data corresponding to the 357th to 535th images in the Tenengrad function evaluation curve are replaced with the grayscale variance evaluation curve for fusion to obtain the fusion evaluation curve. The fusion evaluation curve is as follows: Fig.12 The sampling threshold is plotted on Fig.12 It can be seen that the data corresponding to the 357th to 535th images are all greater than the sampling threshold, so the sample to be tested is a trapezoid.

[0184] Further, when the number of white light interference images is 70, the corresponding white light interference valid images are white light interference images with image numbers 322-570.

[0185] Since the grayscale variance evaluation curve is greatly affected by noise, the noise is reflected as a peak in the grayscale variance evaluation curve, which will lead to inaccurate judgment on whether there is a step in the sample to be tested. In order to solve this technical problem, in some embodiments of the present invention, after step S1002, the following is further included:

[0186] The grayscale variance evaluation curve is denoised.

[0187] By performing denoising on the grayscale variance evaluation curve, it is possible to ensure that the determination of the number of peaks is not affected by noise, thereby improving the accuracy of the number of peaks and further improving the accuracy of the determined white light interference effective image.

[0188] Among them, denoising methods include but are not limited to Gaussian filtering, median filtering, PM equation denoising, etc.

[0189] In a specific embodiment of the present invention, the denoising method is Gaussian filtering. Specifically, a Gaussian filter with a window of 6 is selected to smooth the grayscale variance evaluation curve to remove the influence of noise.

[0190] In summary, the embodiment of the present invention first analyzes the change of the gray value of the image through the gray variance function and the Tenengrad function; after normalizing the two, the gray variance evaluation curve is enveloped and the number of its peaks and the corresponding effective interference image sequence number are extracted; when the number of peaks meets the requirements, the effective section of the Tenengrad and gray variance evaluation curves are fused; finally, the relationship between the fused new curve and the threshold is judged, combined with the coherence length, and the start and end positions of the effective interference image are determined. The effective interference image position collected by the white light interferometer measurement system can be confirmed, and it is applicable to a variety of samples with slopes such as steps or microlenses, trapezoids, etc., which improves the universality of the measured samples and the measurement speed of the white light interferometer.

[0191] In order to better implement the white light interference effective image extraction method in the embodiment of the present invention, based on the white light interference effective image extraction method, the embodiment of the present invention also provides a white light interference effective image extraction device, such as Fig.13 As shown, the white light interference effective image extraction device 1300 includes:

[0192] An image evaluation curve acquisition unit 1301 is used to evaluate the white light interference image sequence of the sample to be tested based on the grayscale variance function and the grayscale gradient function, respectively, to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve;

[0193] A step determination unit 1302 is used to determine whether there is a step in the sample to be tested based on the grayscale variance evaluation curve;

[0194] The evaluation curve fusion unit 1303 is used to determine the step area when there is a step in the sample to be tested, and fuse the grayscale variance evaluation curve and the grayscale gradient evaluation curve based on the step area to obtain a fused evaluation curve;

[0195] A related parameter determination unit 1304, configured to determine the step shape of the step based on the fusion evaluation curve, and determine the number of images of the white light interference effective image based on the white light interference image sequence;

[0196] The white light interference effective image determining unit 1305 is used to determine the white light interference effective image in the white light interference image sequence based on the step shape, the step area and the number of images.

[0197] The white light interference effective image extraction device 1300 provided in the above embodiment can implement the technical solution described in the above white light interference effective image extraction method embodiment. The specific implementation principles of the above modules or units can refer to the corresponding contents in the above white light interference effective image extraction method embodiment, which will not be repeated here.

[0198] like Fig.14 As shown, the present invention also provides a surface topography measurement device 1400. The surface topography measurement device 1400 includes a processor 1401, a memory 1402 and a display 1403. Fig.14 Only some of the components of the surface topography measurement device 1400 are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0199] In some embodiments, the processor 1401 may be a central processing unit (CPU), a microprocessor or other data processing chip, and is used to run program codes or process data stored in the memory 1402, such as the white light interferometry effective image extraction method of the present invention.

[0200] In some embodiments of the present invention, processor 1401 may be a single server or a server group. The server group may be centralized or distributed. In some embodiments, processor 1401 may be local or remote. In some embodiments, processor 1401 may be implemented in a cloud platform. In one embodiment, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-cloud, etc., or any combination thereof.

[0201] In some embodiments, the memory 1402 may be an internal storage unit of the surface topography measurement device 1400, such as a hard disk or memory of the surface topography measurement device 1400. In other embodiments, the memory 1402 may also be an external storage device of the surface topography measurement device 1400, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the surface topography measurement device 1400.

[0202] Furthermore, the memory 1402 may include both an internal storage unit of the surface topography measurement device 1400 and an external storage device. The memory 1402 is used to store application software installed in the surface topography measurement device 1400 and various data.

[0203] In some embodiments, the display 1403 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 1403 is used to display information of the surface topography measurement device 1400 and to display a visual user interface. The components 1401-1403 of the surface topography measurement device 1400 communicate with each other via a system bus.

[0204] In some embodiments of the present invention, when the processor 1401 executes the white light interference effective image extraction program in the memory 1402, the following steps may be implemented:

[0205] Based on the grayscale variance function and the grayscale gradient function, the white light interference image sequence of the sample to be tested is evaluated respectively to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve;

[0206] Determine whether there is a step in the sample to be tested based on the grayscale variance evaluation curve;

[0207] When there are steps in the sample to be tested, the step area is determined, and the grayscale variance evaluation curve and the grayscale gradient evaluation curve are fused based on the step area to obtain a fused evaluation curve;

[0208] determining the step shape of the step based on the fusion evaluation curve, and determining the number of images of the effective white light interference image based on the white light interference image sequence;

[0209] The white light interference effective image in the white light interference image sequence is determined based on the step shape, the step area and the number of images.

[0210] It should be understood that: when the processor 1401 executes the white light interference effective image extraction program in the memory 1402, in addition to the above functions, other functions can also be implemented. For details, please refer to the description of the corresponding method embodiment above.

[0211] Furthermore, the embodiment of the present invention does not specifically limit the type of the surface topography measuring device 1400 mentioned. The surface topography measuring device 1400 may be a portable surface topography measuring device such as a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop computer, etc. Exemplary embodiments of portable surface topography measuring devices include but are not limited to portable surface topography measuring devices equipped with iOS, Android, Microsoft or other operating systems. The above-mentioned portable surface topography measuring device may also be other portable surface topography measuring devices. It should also be understood that in some other embodiments of the present invention, the surface topography measuring device 1400 may not be a portable surface topography measuring device, but a desktop computer with a touch-sensitive surface (e.g., a touch panel).

[0212] Correspondingly, an embodiment of the present invention also provides a computer-readable storage medium, which is used to store computer-readable programs or instructions. When the program or instructions are executed by a processor, the steps or functions in the white light interference effective image extraction method provided in the above-mentioned method embodiments can be implemented.

[0213] Accordingly, an embodiment of the present invention further provides a computer program product, including a computer program / instruction, which implements the steps of the white light interference effective image extraction method in any one of the above embodiments when the computer program / instruction is executed by a processor.

[0214] Those skilled in the art will appreciate that all or part of the processes of the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the computer program can be stored in a computer-readable storage medium, wherein the computer-readable storage medium is a disk, an optical disk, a read-only storage memory, or a random access memory, etc.

[0215] The above is a detailed introduction to a white light interference effective image extraction method, device, equipment, medium and product provided by the present invention. Specific examples are used in this article to illustrate the principle and implementation mode of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation mode and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A white light interference effective image extraction method, characterized in that: include: Based on the grayscale variance function and the grayscale gradient function, the white light interference image sequence of the sample to be tested is evaluated respectively to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve; Determining whether there is a step in the sample to be tested based on the grayscale variance evaluation curve; When there is a step in the sample to be tested, determining the step area, and fusing the grayscale variance evaluation curve and the grayscale gradient evaluation curve based on the step area to obtain a fused evaluation curve; Determining a step shape of the step based on the fusion evaluation curve, and determining the number of images of white light interference effective images based on the white light interference image sequence; A white light interference effective image in the white light interference image sequence is determined based on the step shape, the step area, and the number of images.

2. The white light interference effective image extraction method according to claim 1, characterized in that: The step of determining whether the sample to be tested has a step based on the grayscale variance evaluation curve includes: Determining the number of peaks in the grayscale variance evaluation curve; When the number of peaks is less than the peak threshold number, the sample to be tested does not have steps, and when the number of peaks is greater than or equal to the peak threshold number, the sample to be tested has steps.

3. The white light interference effective image extraction method according to claim 2, characterized in that: Determining the number of peaks in the grayscale variance evaluation curve includes: Determine a target grayscale variance curve that is greater than a grayscale threshold value in the grayscale variance evaluation curve; A target number of peaks in the target grayscale variance curve is determined, and the target number of peaks is used as the number of peaks.

4. The white light interference effective image extraction method according to claim 1, characterized in that: When the sample to be tested has a step, determining the step area, and fusing the grayscale variance evaluation curve and the grayscale gradient evaluation curve based on the step area to obtain a fused evaluation curve, including: When there is a step in the sample to be tested, determining the step area based on the grayscale variance evaluation curve; Determine a gradient target curve segment in the grayscale gradient evaluation curve and a variance target curve segment in the grayscale variance evaluation curve based on the step region; The variance target curve segment is replaced by the gradient target curve segment to obtain the fusion evaluation curve.

5. The white light interference effective image extraction method according to claim 4, characterized in that: The step area is determined based on the grayscale variance evaluation curve, including: Determine the upper surface zero optical path difference position and the lower surface zero optical path difference position of the step based on the grayscale variance evaluation curve; Acquire the image sequence number of the upper surface of the step corresponding to the zero optical path difference position of the upper surface and the image sequence number of the lower surface of the step corresponding to the zero optical path difference position of the lower surface; The white light interference image between the image serial number of the upper surface of the step and the image serial number of the lower surface of the step is used as the step area.

6. The white light interference effective image extraction method according to claim 5, characterized in that: The step of determining the upper surface zero optical path difference position and the lower surface zero optical path difference position of the step based on the grayscale variance evaluation curve comprises: Determining a first zero optical path difference position and a second zero optical path difference position of the step based on the grayscale variance evaluation curve; Acquiring the moving direction of the interference objective lens when acquiring the white light interference image sequence; The upper surface zero optical path difference position and the lower surface zero optical path difference position are determined based on the movement direction of the interference objective lens, the first zero optical path difference position, and the second zero optical path difference position.

7. The white light interference effective image extraction method according to claim 1, characterized in that: The step of determining the step shape of the step based on the fusion evaluation curve includes: Determining a target fusion curve segment in the fusion evaluation curve based on the step area; Determine whether the sampling values ​​of the target fusion curve segment are all greater than a sampling threshold; When the sampling values ​​of the target fusion curve segment are all greater than the sampling threshold, the step shape of the sample to be tested is a trapezoid; When the sampling values ​​of the target fusion curve segment are not all greater than the sampling threshold, the step shape of the sample to be tested is a vertical step.

8. The white light interference effective image extraction method according to claim 7, characterized in that: The step of determining the number of images of effective white light interference images based on the white light interference image sequence comprises: Acquiring the equivalent wavelength of the white light interference image sequence; determining a coherence length and a scanning step size based on the equivalent wavelength; The number of images of the white light interference effective image is determined based on the coherence length and the scanning step length.

9. The white light interference effective image extraction method according to claim 8, characterized in that: The number of images of the effective white light interference image is: In the formula, is the number of images of the white light interference image; is the coherence length; is the scanning step length; is the equivalent wavelength; is the spectral width of the light source.

10. The white light interference effective image extraction method according to claim 9, characterized in that: When the step shape of the sample to be tested is a trapezoid, the image number range of the effective white light interference image is to ; In the formula, is the starting image sequence number of the step area; is the ending image sequence number of the step area; is the number of images of the effective white light interference image.

11. The white light interference effective image extraction method according to claim 10, characterized in that: When the step shape of the sample to be tested is a vertical step, determining the white light interference effective image based on the number of images of the white light interference effective image, the step area, and the step shape of the sample to be tested includes: Determine a reference fusion curve segment whose sampling value of the target fusion curve segment is less than the sampling threshold; Determine the starting white light interference image sequence number and the ending white light interference image sequence number of the reference fusion curve segment; The white light interference effective image is determined based on the image quantity of the white light interference effective image, the step area, the starting white light interference image sequence number and the ending white light interference image sequence number.

12. The white light interference effective image extraction method according to claim 11, characterized in that: When the step shape of the sample to be tested is a vertical step, the image number range of the effective white light interference image is to ,as well as to ; In the formula, is the starting white light interference image serial number; is the sequence number of the terminated white light interference image.

13. The white light interference effective image extraction method according to any one of claims 1 to 12, characterized in that: The grayscale gradient function is a Tenengrad function.

14. The white light interference effective image extraction method according to claim 13, characterized in that: The grayscale variance function is: The gray gradient function is: In the formula, is the image sequence number; is the total number of image rows; is the total number of image columns; For the image The grayscale value of the pixel.

15. The white light interference effective image extraction method according to claim 1, characterized in that: The method of evaluating the white light interference image sequence of the sample to be tested based on the grayscale variance function and the grayscale gradient function to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve comprises: Based on the grayscale variance function and the grayscale gradient function, the white light interference image sequence of the sample to be tested is evaluated respectively to obtain an initial grayscale variance evaluation curve and an initial grayscale gradient evaluation curve; The initial grayscale variance evaluation curve and the initial grayscale gradient evaluation curve are normalized to obtain the grayscale variance evaluation curve and the grayscale gradient evaluation curve.

16. The white light interference effective image extraction method according to claim 15, characterized in that: After the initial grayscale variance evaluation curve and the initial grayscale gradient evaluation curve are normalized to obtain the grayscale variance evaluation curve and the grayscale gradient evaluation curve, the method further includes: The grayscale variance evaluation curve is subjected to denoising processing.

17. A white light interference effective image extraction device, characterized in that: include: An image evaluation curve acquisition unit is used to evaluate the white light interference image sequence of the sample to be tested based on the grayscale variance function and the grayscale gradient function, respectively, to obtain a grayscale variance evaluation curve and a grayscale gradient evaluation curve; A step determination unit, used for determining whether there is a step in the sample to be tested based on the grayscale variance evaluation curve; An evaluation curve fusion unit, used for determining a step area when there is a step in the sample to be tested, and fusing the grayscale variance evaluation curve and the grayscale gradient evaluation curve based on the step area to obtain a fused evaluation curve; A related parameter determination unit, configured to determine a step shape of the step based on the fusion evaluation curve, and determine the number of images of the white light interference effective image based on the white light interference image sequence; The white light interference effective image determining unit is used to determine the white light interference effective image in the white light interference image sequence based on the step shape, the step area and the number of images.

18. A surface topography measuring device, characterized in that: comprising a memory and a processor, wherein: The memory is used to store programs; The processor is coupled to the memory and is used to execute the program stored in the memory to implement the steps in the white light interference effective image extraction method described in any one of claims 1 to 16.

19. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the white light interference effective image extraction method described in any one of claims 1 to 16 are implemented.

20. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the white light interference effective image extraction method described in any one of claims 1 to 16 are implemented.

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