CN114764180B - Focusing method and focusing system for object to be measured, device and storage medium - Google Patents

Focusing method and focusing system for object to be measured, device and storage medium Download PDF

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CN114764180B
CN114764180B CN202011636597.0A CN202011636597A CN114764180B CN 114764180 B CN114764180 B CN 114764180B CN 202011636597 A CN202011636597 A CN 202011636597A CN 114764180 B CN114764180 B CN 114764180B
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focusing
calibration
image
layer
measured
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CN114764180A (en
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陈鲁
吕肃
李青格乐
张嵩
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Shenzhen Zhongke Feice Technology Co Ltd
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Shenzhen Zhongke Feice Technology Co Ltd
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    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B7/00—Mountings, adjusting means, or light-tight connections, for optical elements
    • G02B7/28—Systems for automatic generation of focusing signals
    • G02B7/36—Systems for automatic generation of focusing signals using image sharpness techniques, e.g. image processing techniques for generating autofocus signals
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B21/00—Microscopes
    • G02B21/24—Base structure
    • G02B21/241—Devices for focusing
    • G02B21/244—Devices for focusing using image analysis techniques
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B7/00—Mountings, adjusting means, or light-tight connections, for optical elements
    • G02B7/28—Systems for automatic generation of focusing signals
    • G02B7/36—Systems for automatic generation of focusing signals using image sharpness techniques, e.g. image processing techniques for generating autofocus signals
    • G02B7/38—Systems for automatic generation of focusing signals using image sharpness techniques, e.g. image processing techniques for generating autofocus signals measured at different points on the optical axis, e.g. focussing on two or more planes and comparing image data

Abstract

A focusing method, a focusing system, a device and a storage medium for an object to be measured, wherein the focusing method comprises the following steps: obtaining calibration images of an object to be measured at different focusing heights; acquiring a distribution relation between a first focusing degree parameter and a focusing height of each layer of calibration graph according to the calibration image, wherein the distribution relation is Gaussian distribution; respectively carrying out weighting treatment on the logarithm of the distribution relation of the multi-layer calibration graph to obtain a calibration curve which has a linear relation with the focusing height; obtaining an optimal focusing height reference value; shooting to obtain a to-be-detected image of the to-be-detected object; acquiring a second focal power parameter of each layer of calibration graph according to the image to be measured; respectively solving the logarithm of the second power parameter of each layer of calibration graph in the image to be measured, and then carrying out weighting treatment to obtain a test difference value; and determining the actual height corresponding to the test difference value by using a calibration curve, and calculating the difference value between the reference value of the optimal focusing height and the actual height as the defocus amount of the image to be measured. The invention can improve focusing speed while ensuring focusing accuracy.

Description

Focusing method and focusing system for object to be measured, device and storage medium
Technical Field
Embodiments of the present invention relate to the field of measurement, and in particular, to a focusing method, a focusing system, a focusing device, and a storage medium for an object to be measured.
Background
In applications where measurement is performed based on high magnification microscopy imaging, the accuracy of focusing often directly affects the accuracy of the measurement, for example, in overlay error measurement, the measured overlay errors may differ even by tens of nanometers at different heights. On the other hand, the focusing speed directly affects the measurement efficiency, and too long focusing time will result in lower measurement efficiency.
There are two conventional focusing algorithms, one is to determine the best focusing height by using the response of the image focusing power (for example, image sharpness) to the height based on the images photographed at different heights in an imaging manner, but in order to achieve higher measurement accuracy, it is often required to photograph multiple images in a smaller step, the data acquisition time is long, and the measurement efficiency is low. The other is to measure the distance of the object from the lens in a non-imaging way (e.g. by means of interference), but this way requires the provision of additional optical systems (e.g. interference systems), which are costly and complex overall systems.
Disclosure of Invention
The embodiment of the invention solves the problem of providing a focusing method, a focusing system, a focusing device and a storage medium for an object to be tested, and improves focusing speed while guaranteeing focusing precision.
In order to solve the above problems, an embodiment of the present invention provides a focusing method for an object to be measured, where the object to be measured includes a plurality of layers of calibration patterns, the plurality of layers of calibration patterns have different heights along a focusing direction, and the focusing method includes: acquiring calibration images of the object to be measured at different focusing heights along the focusing direction; acquiring a distribution relation between a first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution; respectively carrying out weighting treatment after logarithm calculation on the distribution relation corresponding to the multi-layer calibration graph to obtain a calibration curve, wherein the calibration curve and the focusing height are in a linear relation; obtaining an optimal focusing height reference value of the multi-layer calibration graph; shooting and obtaining a to-be-detected image of the to-be-detected object; acquiring a second focal power parameter of each layer of calibration graph in the image to be measured according to the image to be measured; the second power parameters of each layer of calibration graph in the image to be tested are respectively logarithmized, and then the weighting processing is carried out to obtain a test difference value; and determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the optimal focusing height reference value and the actual height to be used as the defocus amount of the image to be tested.
Correspondingly, the embodiment of the invention also provides a focusing system of an object to be measured, wherein the object to be measured comprises a plurality of layers of calibration patterns, the plurality of layers of calibration patterns have different heights along the focusing direction, and the focusing system comprises: the image acquisition module is used for acquiring calibration images of the object to be detected at different focusing heights along the focusing direction and shooting and acquiring the image to be detected of the object to be detected; the first image processing module is used for acquiring the distribution relation between the first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution; the first data processing module is used for acquiring the distribution relation between the first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution; the second data processing module is used for acquiring the optimal focusing height reference value of the multi-layer calibration graph; the second image processing module is used for acquiring second focal power parameters of each layer of calibration graph in the image to be detected according to the image to be detected; the third data processing module is used for carrying out the weighting processing after respectively carrying out logarithm on the second power parameter of each layer of calibration graph in the image to be tested to obtain a test difference value; and the fourth data processing module is used for determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the best focusing height reference value and the actual height to be used as the defocus amount of the image to be detected.
Correspondingly, the embodiment of the invention also provides equipment, which comprises at least one memory and at least one processor, wherein the memory stores one or more computer instructions, and the one or more computer instructions are executed by the processor to realize the focusing method of the object to be tested.
Correspondingly, the embodiment of the invention also provides a storage medium, wherein one or more computer instructions are stored in the storage medium, and the one or more computer instructions are used for realizing the focusing method of the object to be measured.
Compared with the prior art, the technical scheme of the embodiment of the invention has the following advantages:
in the focusing method provided by the embodiment of the invention, after the calibration images of the object to be tested under different focusing heights are acquired along the focusing direction, the distribution relation between the first focusing degree parameter and the focusing height of each layer of calibration image is acquired according to the calibration images, the distribution relation is Gaussian, and then the distribution relation corresponding to the multi-layer calibration image is logarithmically calculated, and then weighting processing is carried out, so that a calibration curve with a linear relation is acquired, namely a differential response curve of the first focusing degree parameter under a logarithmic coordinate system is acquired, therefore, the focusing speed of the image to be tested can be increased by acquiring the relation between the first focusing degree parameter difference value and the focusing height under the logarithmic coordinate system in advance, carrying out weighting processing after the second focusing degree parameter of each layer of calibration image in the image to be tested is logarithmically calculated respectively, and acquiring a test difference value, and substituting the known test difference value into the calibration curve, so that the actual height of the image to be tested can be acquired, and the focusing speed of the image to be tested can be increased by calculating the best focusing step size (compared with the best focusing step size of the image to be increased by a contrast ratio under the interference contrast mode, and the contrast ratio of the invention, and the method can be increased by determining the contrast ratio of the contrast value under the contrast mode.
In the focusing system provided by the embodiment of the invention, after the image acquisition module is utilized to acquire the calibration images of the object to be measured under different focusing heights along the focusing direction, the first image processing module acquires the distribution relation between the first focusing degree parameter and the focusing height of each layer of calibration patterns according to the calibration images, the distribution relation is Gaussian distribution, then the first data processing module is utilized to respectively calculate the logarithm of the distribution relation corresponding to the plurality of layers of calibration patterns, and then weighting processing is carried out to acquire the calibration curve with linear relation, the calibration curve is the differential response curve of the first focusing degree parameter under the logarithmic coordinate system, therefore, after the image acquisition module is utilized to acquire the image to be measured, the second focusing degree parameter of each layer of calibration patterns in the image to be measured is acquired through the second image processing module, the third data processing module respectively obtains the logarithm of the second focal power parameter of each layer of calibration graph in the image to be measured, then carries out the weighting processing, after obtaining a test difference value, the fourth data processing module substitutes the known test difference value into the calibration curve to obtain the actual height of the image to be measured, thus obtaining the defocus amount of the image to be measured by calculating the difference value between the optimal focal height reference value and the actual height, compared with the scheme of shooting a plurality of images in a smaller step size to determine the optimal focal height reference value and the scheme of determining the optimal focal height reference value in a non-imaging mode (such as an interference mode), the embodiment of the invention can improve the focal speed while guaranteeing the focal accuracy without increasing the cost of additional hardware (such as an interference system), for example, the focusing accuracy can meet the requirements of multiple microimaging.
Drawings
FIG. 1 is a flow chart of an embodiment of a focusing method for an object to be measured according to the present invention;
FIG. 2 is a schematic diagram of a calibration image of an embodiment of step S1 in FIG. 1;
FIG. 3 is a flowchart of an embodiment of step S2 in FIG. 1;
FIG. 4 is a schematic diagram showing a distribution relationship between a first focusing power parameter and a focusing power and a calibration curve in a logarithmic coordinate system in an embodiment of step S3 in FIG. 1;
FIG. 5 is a flowchart of an embodiment of step S4 in FIG. 1;
FIG. 6 is a functional block diagram of one embodiment of a focusing system for an object under test of the present invention;
fig. 7 is a hardware configuration diagram of an apparatus according to an embodiment of the present invention.
Detailed Description
As is clear from the background art, in the current focusing method, it is difficult to improve the focusing speed while ensuring the focusing accuracy.
In order to solve the technical problem, an embodiment of the present invention provides a focusing method for an object to be measured, where the object to be measured includes a plurality of layers of calibration patterns, the plurality of layers of calibration patterns have different heights along a focusing direction, and the focusing method includes: acquiring calibration images of the object to be measured at different focusing heights along the focusing direction; acquiring a distribution relation between a first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution; respectively carrying out weighting treatment after logarithm calculation on the distribution relation corresponding to the multi-layer calibration graph to obtain a calibration curve, wherein the calibration curve and the focusing height are in a linear relation; obtaining an optimal focusing height reference value of the multi-layer calibration graph; shooting and obtaining a to-be-detected image of the to-be-detected object; acquiring a second focal power parameter of each layer of calibration graph in the image to be measured according to the image to be measured; the second power parameters of each layer of calibration graph in the image to be tested are respectively logarithmized, and then the weighting processing is carried out to obtain a test difference value; and determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the optimal focusing height reference value and the actual height to be used as the defocus amount of the image to be tested.
In the focusing method provided by the embodiment of the invention, the relation between the first focusing degree parameter difference value and the focusing height under the logarithmic coordinate system is obtained in advance, after the image to be measured is obtained, the weighting processing is carried out after the second focusing power parameter of each layer of calibration graph in the image to be measured is respectively calculated, the test difference value is obtained, and the known test difference value is substituted into the calibration curve, so that the actual height of the image to be measured can be obtained, and the defocusing amount of the image to be measured can be obtained by calculating the difference value between the optimal focusing height reference value and the actual height.
Referring to fig. 1, a flowchart of an embodiment of a focusing method of an object to be measured according to the present invention is shown.
In this embodiment, the object to be measured includes multiple layers of calibration patterns, where the multiple layers of calibration patterns have different heights along the focusing direction. In this embodiment, the focusing method includes the following basic steps:
Step S1: acquiring calibration images of the object to be measured at different focusing heights along the focusing direction;
step S2: acquiring a distribution relation between a first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution;
step S3: respectively carrying out weighting treatment after logarithm calculation on the distribution relation corresponding to the multi-layer calibration graph to obtain a calibration curve, wherein the calibration curve and the focusing height are in a linear relation;
step S4: obtaining an optimal focusing height reference value of the multi-layer calibration graph;
step S5: shooting and obtaining a to-be-detected image of the to-be-detected object;
step S6: acquiring a second focal power parameter of each layer of calibration graph in the image to be measured according to the image to be measured;
step S7: the second power parameters of each layer of calibration graph in the image to be tested are respectively logarithmized, and then the weighting processing is carried out to obtain a test difference value;
step S8: and determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the optimal focusing height reference value and the actual height to be used as the defocus amount of the image to be tested.
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
Referring to fig. 1 and 2 in combination, fig. 2 is a schematic diagram of a calibration image of an embodiment of step S1 in fig. 1.
Specifically, step S1 is executed to obtain calibration images 110 of the object under test at different focusing heights along the focusing direction.
In this embodiment, the object to be measured (not shown) includes multiple layers of calibration patterns 100, where the multiple layers of calibration patterns 100 have different heights along the focusing direction, and the calibration images 110 of the object to be measured at different focusing heights are obtained first, so as to prepare for obtaining the distribution relationship between the first focusing degree parameter and the focusing height corresponding to each layer of calibration patterns 100.
Specifically, in the focusing direction, the object to be measured is photographed at different focusing heights, and an image of the object to be measured is obtained as a calibration image 110, wherein the object to be measured comprises a plurality of layers of calibration patterns 100, and the calibration image 110 contains images of the calibration patterns 100. It should be noted that, the multi-layer calibration pattern 100 having different heights along the focusing direction means that: the multi-layer calibration pattern 100 is located at different height positions on the object to be measured along the focusing direction. That is, the multiple layers of calibration patterns 100 are located on the same object to be measured, and the multiple layers of calibration patterns 100 are spatially located at different layers along the normal direction of the surface of the object to be measured.
It should be further noted that, for the same calibration image 110, the focusing heights of the calibration patterns 100 located at different layers are different, and thus, the focusing heights of the multi-layer calibration patterns 100 are different. As an example, the object to be measured is a wafer (wafer), and the calibration pattern 100 is an overlay mark pattern, which is spatially located in different layers on the wafer.
As an example, the number of calibration patterns 100 is two, i.e., the object to be measured includes two layers of calibration patterns 100. Specifically, the two layers of calibration patterns 100 are a first layer of calibration pattern 101 and a second layer of calibration pattern 102, respectively, and the first layer of calibration pattern 101 and the second layer of calibration pattern 102 have different heights along the focusing direction. It should be noted that, the first layer of calibration patterns 101 and the second layer of calibration patterns 102 may be two adjacent layers of calibration patterns 100, or may be separated by one or more layers of other calibration patterns. It should be noted that, in other embodiments, the number of the calibration patterns may be three or four, and the number of the calibration patterns may be more than four.
Specifically, the step of acquiring calibration images 110 of the object under test at different focusing heights along the focusing direction includes: shooting an object to be detected under different focusing heights to obtain a plurality of calibration images 110, wherein each calibration image 110 contains images of the multi-layer calibration pattern 100. That is, each time one calibration image 110 is taken, the multi-layered calibration pattern 100 is taken at the same time, i.e., the images of the multi-layered calibration pattern 100 are displayed in the same calibration image 110.
In this embodiment, the images of the first layer calibration pattern 101 and the second layer calibration pattern 102 are displayed in the same calibration image 110. On the one hand, the first focusing degree parameter of the multi-layer calibration pattern 100 can be obtained by shooting one calibration image 110 at the same time, the efficiency of obtaining the first focusing degree parameter is higher, and meanwhile, for the same calibration image 110, the multi-layer calibration pattern 100 is shot at the same focusing height, the efficiency of obtaining the focusing height is higher, and the focusing height is easier to obtain. Thus, by having each of the calibration images 110 contain the multiple layers of calibration patterns 100, the efficiency of obtaining the first focus level parameter and focus level of each layer of the calibration patterns 100 in the calibration image 110 is improved.
Correspondingly, in this embodiment, the object to be measured is photographed at different focusing heights with a preset step length, and the calibration image 110 is obtained. The preset step size is not too small nor too large. If the preset step length is too small, a correspondingly large number of calibration images 110 need to be shot, so that the data acquisition time is long, and the focusing efficiency of the focusing method is low; if the preset step length is too large, the data volume is correspondingly too small, and then, when the distribution relation between the first focusing degree parameter of each layer of the calibration graph and the focusing height is acquired according to the calibration image, the acquired distribution relation has lower precision, so that the focusing precision is easily reduced. For this purpose, in this embodiment, the preset step size is 30 nm to 200 nm. For example, the preset step size is 50 nm, 100 nm or 150 nm.
In other embodiments, when multiple layers of calibration patterns cannot be shot into the same calibration image, the calibration images of each layer of calibration patterns at different focusing heights can be shot and obtained respectively, and the focusing height of each layer of calibration patterns and the first focusing degree parameter corresponding to the focusing height can be obtained as well.
In this embodiment, the focusing method further includes: an imaging system is provided. Correspondingly, through the imaging system, calibration images 110 of the object to be measured at different focusing heights are acquired along the focusing direction. As an example, the imaging system is a microscopic imaging device
With continued reference to fig. 1 and 2, step S2 is performed to obtain, according to the calibration image 110, a distribution relationship between the first focusing power parameter and the focusing height of each layer of calibration patterns 100, where the distribution relationship is gaussian distribution.
In the process of photographing the calibration pattern 100 (i.e., photographing the object to be measured) at different focusing heights, the focusing height at the time of photographing can be determined, and the first focusing height parameter can be obtained through the calibration pattern 110, so that the focusing height and the first focusing height parameter corresponding to the focusing height can be obtained. And obtaining the distribution relation between the first focusing degree parameter and the focusing height corresponding to each layer of calibration graph 100 so as to obtain a differential response curve of the first focusing degree parameter under a logarithmic coordinate system. Further, since the distribution relationship is gaussian, the obtained curve can be linearly related to the focal height by performing the weighting processing after the logarithm of the distribution relationship.
The focal height here is a photographing height. For example, the focal height is the distance between the object to be measured and the objective lens of the imaging system. It should be further noted that, for the same calibration image 110, the focusing heights of the calibration patterns 100 located in different layers are different, and thus, each layer of calibration pattern 100 has a function of the corresponding first focusing degree parameter and the focusing height.
The first focus parameter comprises image sharpness, image contrast, image center-to-center distance, image curvature, image autocorrelation, or a gaussian derivative of an image. By adopting the first focusing degree parameters of the types, the distribution relation between the first focusing degree parameters and the focusing heights is Gaussian distribution. As an example, the first focus parameter is image sharpness.
Referring to fig. 3 in combination, fig. 3 is a flowchart of an embodiment of step S2. In this embodiment, the step of obtaining the distribution relationship between the first focusing degree parameter and the focusing height of each layer of the calibration graph 100 according to the calibration image 110 includes: step S21 is performed to divide each calibration image 110 into a plurality of areas 130 (as shown in fig. 2), and each area 130 includes an image of the calibration pattern 100.
Each region 130 includes an image of a layer of calibration patterns 100, and the calibration patterns 100 located in the same region 130 have the same height.
As shown in fig. 2, in this embodiment, the object to be measured includes two layers of calibration patterns 100, the plurality of regions 130 are a first region 130a (shown as a dashed line frame in fig. 2) and a second region 130b (shown as a dashed line frame in fig. 2), respectively, and the calibration patterns 100 in the first region 130a and the second region 130b are located on different layers, that is, the calibration patterns 100 in the first region 130a and the second region 130b have different heights along the focusing direction.
In this embodiment, the step of obtaining the distribution relationship between the first focusing degree parameter and the focusing height of each layer of the calibration graph 100 according to the calibration image 110 further includes: step S22 is executed to calculate first focusing degree parameters of each region 130 at different focusing heights, and obtain a distribution relationship between the first focusing degree parameters and the focusing heights.
Specifically, the image sharpness corresponding to the calibration pattern 100 in the first region 130a and the second region 130b is expressed by using the formula (1) and the formula (2), respectively,
wherein G is 1 (z) is the image sharpness of the first region 130a, G 2 (z) image sharpness for second region 130bZ is the distance between the object to be measured and the imaging device, a 1 、a 2 、b 1 、b 2 、C 1 And C 2 Are all constant coefficients, and a 1 And a 2 All have Gaussian width, C 1 And C 2 Are coefficients related to the depth of field of the imaging device.
It should be noted that, since the calibration images 110 of the object under test under different focusing heights are obtained by the same imaging system, C 1 ＝C 2 。
With continued reference to fig. 1, and with reference to fig. 4, step S3 is performed, where the distribution relationships corresponding to the multi-layer calibration graph 100 are respectively logarithmized and then weighted, so as to obtain a calibration curve 140, where the calibration curve 140 has a linear relationship with the focusing height.
Fig. 4 is a schematic diagram of a distribution relationship of the first focusing power parameter and the focusing power and a calibration curve 140 in a logarithmic coordinate system, wherein the abscissa represents the focusing power and the ordinate represents the focusing power parameter (e.g. image sharpness) in an embodiment of step S3.
The calibration curve 140 is in a linear relation with the focusing height, so after the to-be-measured image of the to-be-measured object is obtained through subsequent shooting, the second focusing power parameter of each layer of calibration graph 100 in the to-be-measured image is respectively calculated and then subjected to the weighting processing to obtain a test difference value, and the known test difference value is substituted into the calibration curve 140 to obtain the actual height of the to-be-measured image, so that the defocus amount of the to-be-measured image can be obtained through calculating the difference value between the optimal focusing height reference value and the actual height.
Each layer of calibration patterns 100 has a distribution relationship between the corresponding first focusing degree parameter and the focusing height, and therefore, after logarithms are calculated on the distribution relationship corresponding to the multiple layers of calibration patterns 100, each layer of calibration patterns 100 corresponds to a curve. For example, as shown in fig. 3, the curve corresponding to the first region 130a is a first curve 131, and the curve corresponding to the second region 130b is a second curve 132.
Specifically, the step of weighting includes: providing a plurality of weighted values; and weighting the first focusing degree parameters by using each weighting value to obtain a calibration curve 140, and enabling the calibration curve 140 to have a linear relation with the focusing height through the weighting values.
In this embodiment, the number of the calibration patterns 100 is two, so the weighting values are 1 and-1, respectively, that is, the distribution relationships corresponding to the two layers of the calibration patterns 100 are subtracted from each other to obtain the calibration curve 140. In other embodiments, when the number of calibration patterns is three, the plurality of weighting values are 1, -1/2, and-1/2, respectively. In other embodiments, when the number of calibration patterns is four, the plurality of weighting values are 1, -1, and-1, respectively.
In this embodiment, the step of obtaining the calibration curve 140 further includes, before the logarithm of the distribution relationship corresponding to the multi-layer calibration graph 100 is calculated, respectively: and taking the Gaussian width as a normalization coefficient, and respectively carrying out first normalization processing on the distribution relation corresponding to the multi-layer calibration graph 100. The normalization is a linear characteristic transformation which scales the numerical range of the data according to a specific coefficient, but does not change the data distribution, and the influence of the coefficient is eliminated by performing normalization processing, so that the data processing is facilitated.
In this embodiment, a in the formula (1) 1 And a in formula (2) 2 Normalization.
Therefore, the function S (z) of the calibration curve 140 is expressed by equation (3),
as can be seen from equation (3), the calibration curve 140 is linear with the focal height in a logarithmic coordinate system.
With continued reference to fig. 1, step S4 is performed to obtain the best focus height reference value of the multi-layer calibration pattern 100.
In the subsequent actual detection process, when the image to be detected of the object to be detected is shot, the optimal focusing height reference value is used as a focusing reference position. Specifically, the second focal power parameter of each layer of calibration graph in the image to be measured is respectively calculated to be logarithm, then the weighting processing is carried out, after a test difference value is obtained, the actual height corresponding to the test difference value is determined by utilizing the calibration curve, and the difference value between the optimal focusing height reference value and the actual height is calculated to be used as the defocusing amount of the image to be measured, so that focusing can be realized according to the defocusing amount, and the defocusing amount is obtained through calculation, thereby improving focusing precision and further meeting the requirement of detection precision.
Referring to fig. 5 in combination, fig. 5 is a flowchart of an embodiment of step S4. In this embodiment, the step of obtaining the best focus height reference value of the multi-layer calibration pattern 100 includes: step S41 is executed, where the focusing height corresponding to the maximum value of the first focusing degree parameters of each layer of the calibration patterns 100 is obtained according to the distribution relationship corresponding to each layer of the calibration patterns 100.
The distribution relation between the first focusing degree parameter and the focusing height is Gaussian distribution, so that the focusing height corresponding to the maximum value of the first focusing degree parameter is the optimal focusing height reference value, that is, the peak value of the curve is the optimal focusing height reference value in the distribution relation between the first focusing degree parameter and the focusing height. Wherein, for the same calibration image 110, the focusing heights of the calibration patterns 100 located at different layers have differences, and thus, each layer of calibration patterns 100 has a corresponding maximum value of the first focusing degree parameter.
Therefore, in this embodiment, the step of obtaining the best focus height reference value of the multi-layer calibration pattern 100 further includes: step S42 is executed to calculate an average value of the focal heights corresponding to the maximum value of the first focal length parameters of each layer of calibration patterns 100 as the reference value of the optimal focal length. By calculating the average value of the focal height corresponding to the maximum value of the first focal height parameters of each layer of calibration patterns 100 as the optimal focal height reference value, the complexity of obtaining the optimal focal height reference value is reduced, and the obtained optimal focal height reference value is more accurate. In other embodiments, the step of obtaining the best focus height reference for the multi-layer calibration pattern comprises: acquiring third focal power parameters of calibration images at different focusing heights; and acquiring the focusing height corresponding to the maximum value of the plurality of third focal power parameters as an optimal focusing height reference value. In this embodiment, the third power parameter is used to characterize the overall focus quality of the calibration image. In other embodiments, the best focus height reference value may also be defined by empirical values or experimental data.
With continued reference to fig. 1, step S5 is performed to capture and acquire the image to be measured of the object to be measured.
And obtaining an image to be measured of the object to be measured by shooting, and preparing for obtaining second focusing power parameters of each layer of calibration graph 100 in the image to be measured later, so that after obtaining the defocusing amount of the image to be measured by subsequent calculation, the focusing height of the image to be measured is adjusted to an optimal focusing height reference value according to the defocusing amount. Specifically, the imaging system shoots and acquires the image to be detected of the object to be detected. The description of the calibration pattern 100 in the image to be measured may be combined with the related description referring to the foregoing steps, which is not repeated herein.
With continued reference to fig. 1, step S6 is performed to obtain, according to the image to be measured, a second focusing power parameter of each layer of calibration patterns 100 in the image to be measured.
And obtaining the second focusing power parameter of each layer of calibration graph 100 in the image to be tested, so that the second focusing power parameter of each layer of calibration graph 100 in the image to be tested is respectively calculated to be logarithmic, and then the weighting processing is carried out, so as to obtain a test difference value. Specifically, the step of obtaining the second focusing power parameter of each layer of calibration patterns 100 in the image to be measured according to the image to be measured includes: registering the image to be measured with the calibration image 110 to obtain a region of interest (regions of interest, ROI) in the image to be measured corresponding to the multi-layer calibration pattern 100; a second power parameter of the region of interest corresponding to the multi-layer calibration pattern 100 is acquired. By obtaining a second power parameter of the region of interest corresponding to the multi-layer calibration pattern 100, the focusing process may be expedited and simplified.
The second focus power parameter comprises image sharpness, image contrast, image center-to-center distance, image curvature, image autocorrelation, or a gaussian derivative of the image, and the first and second focus power parameters are of the same type. The focusing degree parameters of the calibration image 110 and the image to be measured are the same in type, so that the defocus amount of the image to be measured can be obtained by using the calibration curve 130 obtained through the calibration image 110.
In this embodiment, when the first focusing power parameter is obtained, the first focusing power parameter is the image sharpness, so in the step of obtaining the second focusing power parameter, the second focusing power parameter is also the image sharpness.
With continued reference to fig. 1, step S7 is executed, where the second power parameter of each layer of calibration graph 100 in the image to be tested is respectively calculated as logarithm, and then the weighting process is performed, so as to obtain a test difference value.
In step S3, the distribution relationships corresponding to the multi-layer calibration graph 100 are respectively logarithmized, and then a calibration curve 140 is obtained, where the calibration curve 140 and the focusing height are in a linear relationship, so that the actual height corresponding to the test difference can be obtained by substituting the test difference into the function corresponding to the calibration curve 140, and accordingly, the defocus amount of the image to be measured can be obtained by calculating the difference between the optimal focusing height reference value and the actual height.
Specifically, the step of obtaining the test difference value includes: and respectively logarithming the second power parameters of the region of interest, and then carrying out the weighting treatment. For a specific description of the weighting process, reference may be made to the corresponding description in the foregoing steps, which will not be repeated here.
In this embodiment, the step of obtaining the test difference value further includes, before logarithming the second power parameter of each layer of calibration patterns 100 in the image to be tested: and carrying out second normalization processing on the second power parameter of each layer of calibration graph 100 in the image to be detected by adopting the normalization coefficient which is the same as the first normalization processing. In the step of obtaining the calibration curve 140, before the logarithm of the distribution relationship corresponding to the multi-layer calibration graph 100 is obtained, the gaussian width is used as a normalization coefficient, and the first normalization processing is performed on the distribution relationship corresponding to the multi-layer calibration graph 100, so that the second normalization processing is performed on the second focal power parameter of each layer of calibration graph 100 in the image to be measured by adopting the normalization coefficient same as the first normalization processing, so that the test difference can be matched with the calibration curve 140, thereby improving the accuracy of data calculation and further improving the focusing precision.
With continued reference to fig. 1, step S8 is performed, where the actual height corresponding to the test difference is determined by using the calibration curve 130, and the difference between the best focus height reference value and the actual height is calculated as the defocus amount of the image to be measured.
The defocus amount is obtained by calculation, the accuracy of the defocus amount is high, and compared with a scheme of photographing a plurality of images in a small step size to determine the optimal focus height reference value and a scheme of determining the optimal focus height reference value in a non-imaging manner (e.g., by interference), the present embodiment can improve the focusing speed while ensuring the focusing accuracy without increasing additional hardware cost.
In this embodiment, the focusing method further includes: and focusing the object to be detected by the imaging system according to the defocus amount. Specifically, focusing the imaging system on the object to be measured according to the defocus amount includes: and relatively moving the focusing amount on the focusing height through the imaging system and the object to be detected.
Correspondingly, the embodiment of the invention also provides a focusing system. Referring to fig. 6, a functional block diagram of one embodiment of a focusing system for an object under test of the present invention is shown.
In this embodiment, the object to be measured (not shown) includes multiple layers of calibration patterns having different heights along the focusing direction. The focusing system includes: the image acquisition module 50 is configured to acquire calibration images 110 of the object to be measured at different focusing heights along the focusing direction, and further is configured to capture an image (not shown) of the object to be measured; a first image processing module 61, configured to obtain, according to the calibration image 110, a distribution relationship between a first focusing degree parameter and a focusing height of each layer of the calibration graph 100, where the distribution relationship is gaussian distribution; the first data processing module 71 is configured to perform a weighting process after logarithm of the distribution relationship corresponding to the multi-layer calibration graph 100, to obtain a calibration curve 140 (as shown in fig. 4), where the calibration curve 130 is in a linear relationship with the focusing height; a second data processing module 72, configured to obtain a best focus height reference value of the multi-layer calibration pattern 100; a second image processing module 62, configured to obtain a second focal power parameter of each layer of calibration patterns 100 in the image to be measured according to the image to be measured; the third data processing module 73 is configured to perform the weighting process after logarithm of the second power parameter of each layer of calibration graph 100 in the image to be tested, so as to obtain a test difference value; the fourth data processing module 80 is configured to determine an actual height corresponding to the test difference by using the calibration curve 130, and calculate a difference between the best focus height reference value and the actual height as the defocus amount of the image to be measured.
In the focusing system, after the image acquisition module 50 is used to acquire calibration images 110 of an object to be measured under different focusing heights along the focusing direction, the first image processing module 61 acquires a distribution relationship between a first focusing degree parameter and the focusing height of each layer of calibration graph 100 according to the calibration images 110, the distribution relationship is gaussian distribution, and then the first data processing module 71 is used to respectively logarithm the distribution relationship corresponding to the layers of calibration graphs 100 and then performs weighting processing to acquire a calibration curve 130140 calibration curve 140 with a linear relationship, namely a differential response curve of the first focusing degree parameter under a logarithmic coordinate system, so that after the image acquisition module 50 is used to acquire the image to be measured, the second focusing degree parameter of each layer of calibration graph 100 in the image to be measured is acquired through the second image processing module 62, and the third data processing module 73 performs the weighting processing after respectively logarithm of the second focal power parameter of each layer of calibration graph 100 in the image to be measured, after obtaining the test difference value, the fourth data processing module 80 substitutes the known test difference value into the calibration curve 140, so that the actual height of the image to be measured can be obtained, and the defocus amount of the image to be measured can be obtained by calculating the difference value between the optimal focal height reference value and the actual height.
The object to be measured (not shown) includes a plurality of layers of calibration patterns 100, the plurality of layers of calibration patterns 100 have different heights along the focusing direction, and the image acquisition module 50 is configured to acquire calibration images 110 of the object to be measured at different focusing heights along the focusing direction, so as to prepare for acquiring the distribution relationship between the first focusing degree parameter and the focusing height corresponding to each layer of calibration patterns 100. Specifically, the image obtaining module 50 is configured to capture images of an object to be measured in different focusing heights in a focusing direction, and obtain images of the object to be measured as a calibration image 110, where the object to be measured includes a plurality of layers of calibration patterns 100, and the calibration image 110 includes images of the calibration patterns 100. In this embodiment, the image acquisition module 50 is an imaging system. In particular, the imaging system comprises a microscopic imaging device.
As an example, the object to be measured is a wafer, and the calibration pattern 100 is an overlay mark pattern, where the overlay mark pattern is spatially located in different layers on the wafer.
In this embodiment, the number of calibration patterns 100 is two, i.e. the object to be measured includes two layers of calibration patterns 100. Specifically, the two layers of calibration patterns 100 are a first layer of calibration pattern 101 and a second layer of calibration pattern 102, respectively, and the first layer of calibration pattern 101 and the second layer of calibration pattern 102 have different heights along the focusing direction.
In this embodiment, the image acquisition module 50 captures a plurality of calibration images 110 at different focus heights, and each calibration image 110 contains an image of the multi-layer calibration pattern 100. That is, each time one calibration image 110 is photographed, the plurality of calibration patterns 100 are photographed at the same time, that is, the images of the plurality of calibration patterns 100 are displayed in the same calibration image 110. In this embodiment, the first layer calibration pattern 101 and the second layer calibration pattern 102 are displayed in the same calibration image 110.
In this embodiment, the image obtaining module 50 captures the object to be measured at different focusing heights with a preset step length to obtain the calibration image 110. Wherein, the preset step length is not too small or too large. If the preset step length is too small, correspondingly shooting a large number of calibration images 110, correspondingly causing long data acquisition time, thereby causing low focusing efficiency of the focusing method; if the preset step length is too large, the data volume is correspondingly too small, and then, when the distribution relation between the first focusing degree parameter of each layer of the calibration graph and the focusing height is acquired according to the calibration image, the acquired distribution relation has lower precision, so that the focusing precision is easily reduced. For this purpose, in this embodiment, the preset step size is 30 nm to 200 nm.
In this embodiment, the image acquisition module 50 is further configured to capture and acquire an image of the object to be detected during the actual detection process. And obtaining an image to be measured through shooting, and preparing for obtaining second focusing power parameters of each layer of calibration graph 100 in the image to be measured according to the image to be measured, so that after calculating and obtaining the defocus amount of the image to be measured, the focusing height of the image to be measured is adjusted to an optimal focusing height reference value according to the defocus amount.
The first image processing module 61 is configured to obtain, according to the calibration image 110, a distribution relationship between the first focusing degree parameter and the focusing height of each layer of the calibration image 100, where the distribution relationship is gaussian distribution. The image acquisition module 50 can determine the focus height during the process of capturing the calibration image 100 at different focus heights, and can acquire the first focus height parameter through the calibration image 110, thereby acquiring the focus height and the first focus height parameter corresponding to the focus height. Therefore, the distribution relation between the first focusing power parameter and the focusing height of each layer of calibration patterns 100 is acquired through the first image processing module 61, so that the acquired data is transmitted to the first data processing module 71, and the differential response curve of the first focusing power parameter under the logarithmic coordinate system is acquired by using the first data processing module 71. Further, since the distribution relationship is gaussian, the calibration curve 140 having a linear relationship with the focal height can be easily obtained by performing the weighting processing after the logarithm of the distribution relationship.
The first focus parameter comprises image sharpness, image contrast, image center-to-center distance, image curvature, image autocorrelation, or a gaussian derivative of the image. As one example, the first focus parameter is image sharpness.
Specifically, the first image processing module 61 divides each calibration image 110 into a plurality of regions 130 (as shown in fig. 2), each region 130 includes an image of a layer of calibration image 100, and is further configured to calculate a first focusing degree parameter of each region 130 at different focusing heights, so as to obtain a distribution relationship between the first focusing degree parameter and the focusing height. Each region 130 includes an image of a layer of calibration patterns 100, and the calibration patterns 100 located in the same region 130 have the same height. As shown in fig. 2, in this embodiment, the object to be measured includes two layers of calibration patterns 100, the plurality of regions 130 are a first region 130a (shown as a dashed line frame in fig. 2) and a second region 130b (shown as a dashed line frame in fig. 2), respectively, and the calibration patterns 100 in the first region 130a and the second region 130b are located on different layers, that is, the calibration patterns 100 in the first region 130a and the second region 130b have different heights along the focusing direction.
Specifically, the image sharpness corresponding to the calibration pattern 100 in the first region 130a and the second region 130b is expressed by using the formula (1) and the formula (2), respectively,
wherein G is 1 (z) is the image sharpness of the first region 130a, G 2 (z) is the image sharpness of the second region 130b, z is the distance between the object to be measured and the imaging device, a 1 、a 2 、b 1 、b 2 、C 1 And C 2 Are all constant coefficients, and a 1 And a 2 All have Gaussian width, C 1 And C 2 Are coefficients related to the depth of field. It should be noted that, since the same image acquisition module 50 is used to acquire the calibration images 110 of the object under test at different focusing heights, C 1 ＝C 2 。
The first data processing module 71 is configured to perform a weighting process after logarithm of the distribution relationship corresponding to the multi-layer calibration graph 100, so as to obtain a calibration curve 140 (as shown in fig. 4), where the calibration curve 130 is in a linear relationship with the focusing height. Referring to fig. 4 in combination, fig. 4 is a schematic diagram of a distribution relationship of a first focusing power parameter and a focusing power and a calibration curve 140 in a logarithmic coordinate system, with an abscissa representing the focusing power and an ordinate representing the focusing power parameter (e.g., image sharpness).
The calibration curve 140 is in a linear relationship with the focusing height, so that after the image to be measured of the object to be measured is obtained by subsequent shooting, the second focusing power parameter of each layer of calibration graph in the image to be measured is respectively logarithmized, then the weighting processing is performed to obtain a test difference value, and the known test difference value is substituted into a function corresponding to the calibration curve 140, so that the actual height of the image to be measured can be obtained, and the defocus amount of the image to be measured can be obtained by calculating the difference value between the optimal focusing height reference value and the actual height.
Each layer of calibration patterns 100 has a distribution relationship between the corresponding first focusing degree parameter and the focusing height, so the first data processing module 71 respectively logarithms the distribution relationship corresponding to the layers of calibration patterns 100, and each layer of calibration patterns 100 corresponds to a curve. For example, as shown in fig. 4, the curve corresponding to the first region 130a is a first curve 131, and the curve corresponding to the second region 130b is a second curve 132.
Specifically, the first data processing module 71 is configured to provide a plurality of weighted values, weight the plurality of first focusing power parameters with each weighted value, obtain the calibration curve 140, and make the calibration curve 140 have a linear relationship with the focusing height through the weighted values. In this embodiment, the number of calibration patterns 100 is two, so the weighting values are 1 and-1, respectively, that is, the distribution relationships corresponding to the two calibration patterns 100 are subtracted from each other to obtain the calibration curve 140. In other embodiments, when the number of calibration patterns is three, the plurality of weighting values are 1, -1/2, and-1/2, respectively. In other embodiments, when the number of calibration patterns is four, the plurality of weighting values are 1, -1, and-1, respectively.
In this embodiment, the first data processing module 71 is further configured to perform a first normalization process on the distribution relationships corresponding to the multi-layer calibration graph 100, using the gaussian width as the normalization coefficient, before the logarithms of the distribution relationships corresponding to the multi-layer calibration graph 100 are obtained respectively.
In this embodiment, the first data processing module 71 applies a in the formula (1) 1 And a in formula (2) 2 Normalization. Therefore, the function S (z) of the calibration curve 140 is expressed by equation (3),
as can be seen from equation (3), the calibration curve 140 is linear with the focal height in a logarithmic coordinate system.
The second data processing module 72 is used to obtain the best focus height reference value of the multi-layer calibration pattern 100.
In the actual detection process, when the image to be detected of the object to be detected is shot, the optimal focusing height reference value is used as a focusing reference position.
Specifically, the second focal power parameter of each layer of calibration graph 100 in the image to be measured is respectively calculated to be logarithmic, then the weighting processing is performed, after a test difference value is obtained, the actual height corresponding to the test difference value is determined by using the calibration curve, and the difference value between the optimal focusing height reference value and the actual height is calculated to be used as the defocusing amount of the image to be measured, so that focusing can be realized according to the defocusing amount, and the defocusing amount is obtained through calculation, thereby improving focusing precision and further meeting the requirement of detection precision.
Specifically, the second data processing module 72 is configured to obtain, according to a distribution relationship corresponding to each layer of calibration patterns 100, a focus height corresponding to a maximum value of the first focus degree parameters of each layer of calibration patterns 100, and calculate, as an optimal focus height reference value, an average value of focus heights corresponding to the maximum value of the first focus degree parameters of each layer of calibration patterns 100. The distribution relation between the first focusing degree parameter and the focusing height is Gaussian distribution, so that the focusing height corresponding to the maximum value of the first focusing degree parameter is the optimal focusing height reference value, that is, the peak value of the curve is the optimal focusing height reference value in the distribution relation between the first focusing degree parameter and the focusing height. By calculating the average value of the heights corresponding to the maximum values of the first focusing-angle parameters of the multi-layer calibration pattern 100 as the optimal focusing-angle reference value, the complexity of obtaining the optimal focusing-angle reference value is reduced, and the obtained optimal focusing-angle reference value is more accurate.
In other embodiments, the second data processing module may also be configured to obtain third focal power parameters of the calibration image at different focal heights, and further configured to obtain, as the best focal height reference value, a focal height corresponding to a maximum value of a plurality of the third focal power parameters, where in the embodiments, the third focal power parameters are used to characterize the overall focal quality of the calibration image. In other embodiments, the focusing system may also not be provided with the second data processing module, and the best focus height reference value may be customized through empirical values or experimental data.
After the image obtaining module 50 captures an image of the object to be measured, the second image processing module 62 is configured to obtain a second focusing power parameter of each layer of calibration patterns 100 in the image to be measured. And obtaining a test difference value by obtaining the second focusing power parameter of each layer of calibration graph 100 in the image to be tested so as to calculate and respectively logarithm the second focusing power parameter of each layer of calibration graph 100 in the image to be tested and then carrying out the weighting treatment.
Specifically, the second image processing module 62 is configured to register the image to be measured with the calibration image 110 to obtain a region of interest corresponding to the multi-layer calibration graph 100 in the image to be measured, and is further configured to obtain a second focal power parameter of the region of interest corresponding to the multi-layer calibration graph 100. By obtaining a second power parameter for the region of interest corresponding to the multi-layer calibration pattern 100, the focusing process can be expedited and simplified.
In this embodiment, the first focusing power parameter and the second focusing power parameter are the same in type, so that the defocus amount of the image to be measured can be obtained by using the calibration curve 130 obtained through the calibration image 110. In this embodiment, when the first focusing power parameter is acquired, the first focusing power parameter is the image sharpness, and therefore, when the second focusing power parameter is acquired, the second focusing power parameter is also the image sharpness.
The third data processing module 73 is configured to calculate the second power parameter of each layer of calibration graph 100, perform the weighting process after the second power parameter is respectively logarithmic, and obtain a test difference value. The calibration curve 140 is a linear function curve, so that the third data processing module 73 obtains a test difference value, and then the actual height corresponding to the test difference value can be obtained by substituting the test difference value into the calibration curve 140, and accordingly, the difference value between the reference value of the best focusing height and the actual height is calculated, so as to obtain the defocus amount of the image to be measured.
Specifically, the third data processing module 73 is configured to log the second power parameters of the region of interest, and perform the weighting processing to obtain a test difference value.
In this embodiment, the third data processing module 73 is further configured to perform a second normalization process on the second power parameter of each layer of calibration graph 100 in the image to be measured by using the same normalization coefficient as the first normalization process before the second power parameter of each layer of calibration graph 100 in the image to be measured is logarithmized.
The fourth data processing module 80 is configured to determine an actual height corresponding to the test difference by using the calibration curve 140, and calculate a difference between the reference value of the best focus height and the actual height as a defocus amount of the image to be measured
The image acquisition module 50, the first image processing module 61, the first data processing module 71, the second data processing module 72, the second image processing module 62 and the third data processing module 73 enable the defocus amount to be obtained through calculation, the defocus amount to have higher precision, and compared with a scheme of capturing a plurality of images in a smaller step size to determine the optimal focus height reference value and a scheme of determining the optimal focus height reference value in a non-imaging manner, the present embodiment can improve the focusing speed while ensuring the focusing precision without increasing additional hardware cost, for example, the focusing precision can satisfy the 100-fold micro imaging requirement.
In this embodiment, the image acquisition module 50 is further configured to focus the imaging system on the object to be measured according to the defocus amount. Specifically, the amount of focus is moved relatively in the focus height by the imaging system and the object to be measured.
The embodiment of the invention also provides equipment, which can realize the focusing method of the object to be tested by loading the focusing method of the object to be tested in a program form.
Referring to fig. 7, a hardware configuration diagram of an apparatus according to an embodiment of the present invention is shown. The device of this embodiment includes: at least one processor 01, at least one communication interface 02, at least one memory 03 and at least one communication bus 04.
In this embodiment, the number of the processor 01, the communication interface 02, the memory 03 and the communication bus 04 is at least one, and the processor 01, the communication interface 02 and the memory 03 complete communication with each other through the communication bus 04.
The communication interface 02 may be an interface of a communication module for performing network communication, for example, an interface of a GSM module.
The processor 01 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the focusing method described in this embodiment.
The memory 03 may comprise a high-speed RAM memory or may further comprise a non-volatile memory (non-volatile memory), such as at least one magnetic disk memory.
The memory 03 stores one or more computer instructions that are executed by the processor 01 to implement the focusing method of the object to be measured provided in the foregoing embodiment.
It should be noted that, the implementation terminal device may further include other devices (not shown) that may not be necessary for the disclosure of the embodiment of the present invention; embodiments of the present invention will not be described in detail herein, as such other devices may not be necessary to an understanding of the present disclosure.
The embodiment of the invention also provides a storage medium, which stores one or more computer instructions for implementing the focusing method of the object to be tested provided in the previous embodiment.
In the focusing method of the embodiment of the invention, the relation between the difference value of the first focusing degree parameter and the focusing height under the logarithmic coordinate system is obtained in advance, after the image to be measured is obtained, the weighting treatment is carried out after the second focusing degree parameter of each layer of calibration graph in the image to be measured is respectively calculated logarithmically, the test difference value is obtained, the known test difference value is substituted into the calibration curve, and the actual height of the image to be measured can be obtained, so that the defocus amount of the image to be measured can be obtained by calculating the difference value between the optimal focusing height reference value and the actual height.
The embodiments of the application described above are combinations of elements and features of the application. Unless otherwise mentioned, the elements or features may be considered optional. Each element or feature may be practiced without combining with other elements or features. In addition, embodiments of the application may be constructed by combining some of the elements and/or features. The order of operations described in embodiments of the application may be rearranged. Some configurations of any embodiment may be included in another embodiment and may be replaced with corresponding configurations of another embodiment. It will be obvious to those skilled in the art that claims which are not explicitly cited in each other in the appended claims may be combined into embodiments of the present application or may be included as new claims in a modification after submitting the present application.
Embodiments of the application may be implemented by various means, such as hardware, firmware, software or combinations thereof. In a hardware configuration, the method according to the exemplary embodiments of the present application may be implemented by one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, etc.
In a firmware or software configuration, embodiments of the present invention may be implemented in the form of modules, procedures, functions, and so on. The software codes may be stored in memory units and executed by processors. The memory unit may be located inside or outside the processor and may send and receive data to and from the processor via various known means.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the invention, and the scope of the invention should be assessed accordingly to that of the appended claims.

Claims (13)

1. A focusing method of an object to be measured, wherein the object to be measured includes a plurality of layers of calibration patterns having different heights along a focusing direction, the focusing method comprising:
acquiring calibration images of the object to be measured at different focusing heights along the focusing direction;
acquiring a distribution relation between a first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution;
respectively carrying out weighting treatment after logarithm calculation on the distribution relation corresponding to the multi-layer calibration graph to obtain a calibration curve, wherein the calibration curve and the focusing height are in a linear relation;
obtaining an optimal focusing height reference value of the multi-layer calibration graph;
shooting and obtaining a to-be-detected image of the to-be-detected object;
acquiring a second focal power parameter of each layer of calibration graph in the image to be measured according to the image to be measured;
the second power parameters of each layer of calibration graph in the image to be tested are respectively logarithmized, and then the weighting processing is carried out to obtain a test difference value;
and determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the optimal focusing height reference value and the actual height to be used as the defocus amount of the image to be tested.
2. The focusing method of claim 1, wherein the step of acquiring calibration images of the object under test at different focus heights along the focus direction comprises: shooting under different focusing heights to obtain a plurality of calibration images, wherein each calibration image contains images of the plurality of layers of calibration patterns;
the step of obtaining the distribution relation between the first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image comprises the following steps: dividing each calibration image into a plurality of areas, wherein each area comprises an image of a layer of calibration graph; and respectively calculating first focusing degree parameters of each region under different focusing heights, and acquiring the distribution relation between the first focusing degree parameters and the focusing heights.
3. The focusing method according to claim 1 or 2, wherein the object to be measured is photographed at different focusing heights in a preset step size of 30 nm to 200 nm, and the calibration image is obtained.
4. The focusing method of claim 1, wherein the step of obtaining the best focus height reference value of the multi-layered calibration pattern comprises: respectively acquiring the focusing height corresponding to the maximum value of the first focusing degree parameters of each layer of the calibration patterns according to the distribution relation corresponding to each layer of the calibration patterns; calculating an average value of the focusing heights corresponding to the maximum value of the first focusing degree parameters of each layer of the calibration patterns, and taking the average value as an optimal focusing height reference value;
Or alternatively, the process may be performed,
the step of obtaining the optimal focusing height reference value of the multi-layer calibration graph comprises the following steps: acquiring third focal power parameters of calibration images at different focusing heights; and acquiring focusing heights corresponding to the maximum values of the third focal power parameters as optimal focusing height reference values.
5. The focusing method of claim 1, wherein the step of obtaining a second focusing power parameter for each layer of calibration patterns in the image to be measured from the image to be measured comprises: registering the image to be detected with the calibration image to obtain a region of interest in the image to be detected, which corresponds to the multi-layer calibration graph; acquiring a second focal power parameter of the region of interest corresponding to the multi-layer calibration graph;
the step of obtaining the test difference value comprises the following steps: and respectively logarithming the second power parameters of the region of interest, and then carrying out the weighting treatment.
6. The focusing method of claim 1, wherein the step of obtaining the calibration curve further comprises, before logarithming the distribution relationships corresponding to the plurality of layers of calibration patterns, respectively: taking Gaussian width as a normalization coefficient, and respectively carrying out first normalization processing on the distribution relation corresponding to the multi-layer calibration graph;
The step of obtaining the test difference value further includes, before the step of logarithming the second power parameter of each layer of calibration pattern in the image to be tested: and carrying out second normalization processing on the second power parameter of each layer of calibration graph in the image to be detected by adopting the normalization coefficient which is the same as the first normalization processing.
7. The focusing method of claim 1, wherein the first focusing power parameter and the second focusing power parameter each comprise an image sharpness, an image contrast, an image center-to-center distance, an image curvature, an image autocorrelation, or a gaussian derivative of an image, and the first focusing power parameter and the second focusing power parameter are of the same type.
8. The focusing method according to claim 1, wherein the step of weighting includes: providing a plurality of weighted values; and weighting the first focusing degree parameters by using each weighting value to obtain a calibration curve, and enabling the calibration curve to have a linear relation with the focusing height through the weighting values.
9. The focusing method of claim 8, wherein the number of calibration patterns is two, and the plurality of weighting values are 1 and-1, respectively;
Or the number of the calibration patterns is three, and the weighting values are respectively 1, -1/2 and-1/2;
or the number of the calibration patterns is four, and the weighting values are respectively 1, -1, 1 and-1.
10. The focusing method of claim 9, wherein the focusing method further comprises: providing an imaging system;
acquiring calibration images of the object to be detected at different focusing heights along the focusing direction by the imaging system;
and shooting and acquiring the image to be detected of the object to be detected through the imaging system.
11. A focusing system for an object to be measured, the object to be measured comprising a plurality of layers of calibration patterns having different heights along a focusing direction, the focusing system comprising:
the image acquisition module is used for acquiring calibration images of the object to be detected at different focusing heights along the focusing direction and shooting and acquiring the image to be detected of the object to be detected;
the first image processing module is used for acquiring the distribution relation between the first focusing degree parameter of each layer of the calibration graph and the focusing height according to the calibration image, wherein the distribution relation is Gaussian distribution;
The first data processing module is used for carrying out weighting processing after respectively solving logarithms of the distribution relation corresponding to the multi-layer calibration graph to obtain a calibration curve, wherein the calibration curve and the focusing height are in a linear relation;
the second data processing module is used for acquiring the optimal focusing height reference value of the multi-layer calibration graph;
the second image processing module is used for acquiring second focal power parameters of each layer of calibration graph in the image to be detected according to the image to be detected;
the third data processing module is used for carrying out the weighting processing after respectively carrying out logarithm on the second power parameter of each layer of calibration graph in the image to be tested to obtain a test difference value;
and the fourth data processing module is used for determining the actual height corresponding to the test difference value by using the calibration curve, and calculating the difference value between the best focusing height reference value and the actual height to be used as the defocus amount of the image to be detected.
12. An apparatus comprising at least one memory and at least one processor, the memory storing one or more computer instructions, wherein the one or more computer instructions are executable by the processor to implement the method of focusing an object to be measured as claimed in any one of claims 1 to 10.
13. A storage medium storing one or more computer instructions for implementing a method of focusing an object to be measured according to any one of claims 1 to 10.
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