WO2023133729A1

WO2023133729A1 - Automatic focusing method, apparatus and device based on electron beam measurement device, and storage medium

Info

Publication number: WO2023133729A1
Application number: PCT/CN2022/071605
Authority: WO
Inventors: 杨彩虹; 韩春营; 俞宗强; 王振
Original assignee: 东方晶源微电子科技（北京）有限公司
Priority date: 2022-01-12
Filing date: 2022-01-12
Publication date: 2023-07-20

Abstract

The present application relates to an automatic focusing method, apparatus and device based on an electron beam measurement device, and a storage medium. The method comprises: acquiring a plurality of detection images collected by the current channel in an electron beam measurement device; adaptively adjusting a coarse focusing search step according to definition evaluation results of the plurality of detection images, and performing coarse focusing on the electron beam measurement device according to the adjusted coarse focusing search step, so as to determine an optimal coarse focusing position; and taking the optimal coarse focusing position as a search center, collecting a preset number of sample images according to the current fine focusing search parameter, and performing a fine focusing search according to definition evaluation results of the preset number of collected sample images, so as to obtain a focusing result. By means of the present application, coarse focusing during an automatic focusing process of an electron beam measurement device is performed in a variable-step manner, such that a coarse focusing search step used during coarse focusing is more flexible, thereby ultimately effectively improving the automatic focusing efficiency of the electron beam measurement device.

Description

Autofocus method and device, device and storage medium based on electron beam measuring equipment

technical field

The present application relates to the technical fields of automatic control and image processing, and in particular to an automatic focusing method and device, device and storage medium based on electron beam measuring equipment.

Background technique

Nano-scale electron beam measurement equipment mainly uses the principle of scanning electron microscope to realize nano-scale imaging, and based on image measurement and analysis, to realize the monitoring of key process parameters, which is the key equipment for quality control in the chip manufacturing process. There are generally two ways to focus the electron beam measurement equipment, one is to focus by adjusting the size of the Z-axis of the stage, and the other is to focus by adjusting the current of the electromagnetic lens. Among them, the automatic focusing process is to automate the process, and finally realize the automatic focusing process of the scanning electron microscope by automatically adjusting the size of the Z coordinate or the size of the current value.

The existing autofocus process is mainly divided into two core parts, one is image sharpness evaluation, and the other is search strategy. Among them, the focus search strategy directly affects the speed of auto focus. In related technologies, a hill-climbing algorithm search strategy is usually used for auto-focusing. The search strategy of the hill-climbing algorithm is based on image definition, and its essence is a problem of image definition optimization. Among them, the automatic focus hill-climbing search is divided into two steps: coarse focus and fine focus. The autofocus takes a long time, which affects the speed of autofocus.

Contents of the invention

In view of this, the present application proposes an autofocus method based on electron beam measurement equipment, which can effectively improve the autofocus speed of electron beam measurement equipment.

According to an aspect of the present application, an automatic focusing method based on an electron beam measuring device is provided, including:

Obtain multiple detection images collected by the current channel in the electron beam measurement device;

Adaptively adjust the coarse focus search step according to the sharpness evaluation results of the plurality of detected images, and perform coarse focus on the electron beam measuring device according to the adjusted coarse focus search step to determine the best coarse focus Location;

Taking the best coarse focus position as the search center, collect a preset number of sample images according to the current fine focus search parameters, and perform fine focusing according to the sharpness evaluation results of the collected preset number of sample images Search for the focused results.

In a possible implementation manner, the coarse focus search step size is adaptively adjusted according to the sharpness evaluation results of the plurality of detection images, including:

unifying the contrast of each of the detected images, and performing median filtering on each of the detected images;

Carrying out sharpness evaluation on each of the detected images after median filtering to obtain a sharpness evaluation result;

The coarse focus search step size is determined according to the sharpness evaluation result.

In a possible implementation manner, unifying the contrast of each of the detection images is performed by performing a histogram definition process on each of the detection images.

In a possible implementation manner, the sharpness evaluation is performed on each of the detected images after median filtering, and the sharpness evaluation result is obtained, including:

performing Fourier transform on each of the detected images after median filtering to obtain a spectrum histogram of each of the detected images;

performing multi-interval normalization on each of the spectrum histograms, and performing logic operations on the normalized spectrum histograms to obtain the evaluation curves of each of the detection images;

Based on the evaluation curve of each of the detected images, the definition evaluation result is obtained.

In a possible implementation manner, performing a logical operation on the normalized spectrum histogram also includes performing a high-frequency and low-frequency amplification operation on the image content in the spectrum histogram.

In a possible implementation manner, performing a logic operation on the normalized spectrum histogram includes performing weighted sum processing on the normalized spectrum histogram.

In a possible implementation manner, after performing median filtering on each of the detection images, further comprising: calculating an average local variance curve of the detection images after median filtering;

Correspondingly, the evaluation results of the sharpness are obtained based on the evaluation curves of each of the detected images, including:

calculating a correlation of each of said evaluation curves with said mean local variance curve, respectively;

The sharpness evaluation result is obtained according to each of the calculated correlations.

In a possible implementation manner, when the image sharpness evaluation result is obtained according to each of the calculated correlations, the evaluation curve with the highest correlation is selected from each of the correlations as the sharpness evaluation result .

In a possible implementation manner, the fine-focus search parameter includes at least one of a fine-focus search range and a fine-focus search step.

In a possible implementation manner, when the fine-focus search is performed according to the sharpness evaluation results of the collected sample images of the preset number to obtain the focus result, the search is performed in a variable step size manner.

In a possible implementation manner, when using a variable step size method to perform a fine-focus search based on the sharpness evaluation results of the collected sample images of the preset number of sheets to obtain the focus result, it includes:

Updating the fine-focus search parameters according to the sharpness evaluation results of the preset number of sample images currently obtained, and re-acquisition of the preset number of sample images with the updated fine-focus search parameters, Until the number of re-acquisitions reaches the preset number of iterations.

In a possible implementation manner, when the fine-focus search is performed according to the collected sharpness evaluation results of the preset number of sample images, changes in the sharpness evaluation results based on the preset number of sample images the trend goes on;

Wherein, the change trend of the sharpness evaluation results of the preset number of sample images includes at least one of monotonically increasing, monotonically decreasing, and quadratic fitting of the sharpness curve;

When the change trend of the sharpness evaluation results of the preset number of sample images is monotonically increasing, perform a forward search, update the search range and re-acquire the preset number of sample images based on the updated search range ;

Perform a backward search when the change trend of the definition evaluation results of the preset number of sample images is monotonically decreasing, update the search range and re-acquire the preset number of sample images based on the updated search range ;

When the change trend of the sharpness evaluation results of the preset number of sample images is that the sharpness curve is quadratic fitting, the fine focus search parameters are updated according to the opening direction of the fitted curve, and based on the updated fine focus search parameter to perform reacquisition of the preset number of sample images.

According to another aspect of the present application, there is also provided an automatic focusing device based on electron beam measuring equipment, including an image acquisition module, a coarse focusing module and a fine focusing module;

The image acquisition module is configured to acquire multiple detection images collected by the current channel in the electron beam measurement device;

The coarse focus module is configured to adaptively adjust the coarse focus search step size according to the sharpness evaluation results of the plurality of detection images, and adjust the electron beam measurement device according to the adjusted coarse focus search step size Carry out coarse focus and determine the best coarse focus position;

The fine focusing module is configured to take the best coarse focus position as the search center, collect a preset number of sample images according to the current fine focus search parameters, and collect samples according to the preset number of samples collected. The sharpness evaluation result of the image is subjected to a fine focus search to obtain the focus result.

According to another aspect of the present application, an autofocus device based on an electron beam measurement device is also provided, including:

processor;

memory for storing processor-executable instructions;

Wherein, the processor is configured to implement any one of the aforementioned methods when executing the executable instructions.

According to another aspect of the present application, there is also provided a non-volatile computer-readable storage medium on which computer program instructions are stored, and when the computer program instructions are executed by a processor, any one of the aforementioned methods is implemented.

By acquiring multiple detection images collected by the current channel of the electron beam measurement equipment, and then adaptively adjust the coarse focus search step according to the sharpness evaluation results of the multiple detection images, and adjust the coarse focus search step according to the adjusted coarse focus search step Electron beam measuring equipment performs coarse focusing to determine the best coarse focus position. Then take the best coarse focus position as the search center, collect a preset number of sample images according to the current fine focus search parameters, and finally perform a fine focus search according to the sharpness evaluation results of the collected preset number of sample images The focus result is obtained, which realizes the coarse focus in the autofocus process of the electron beam measurement equipment by adopting a variable step size, which makes the coarse focus search step used in the coarse focus more flexible, and finally effectively improves the electron beam. Autofocus efficiency of the beam measurement device.

Other features and aspects of the present application will become apparent from the following detailed description of exemplary embodiments with reference to the accompanying drawings.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the application and, together with the specification, serve to explain the principles of the application.

Fig. 1 shows the flow chart of the autofocus method based on the electron beam measurement equipment of the embodiment of the present application;

Fig. 2 shows the flow chart of image sharpness evaluation in the autofocus method based on electron beam measuring equipment according to the embodiment of the present application;

Fig. 3 shows another flow chart of the autofocus method based on the electron beam measuring equipment of the embodiment of the present application;

Fig. 4 shows the structural block diagram of the autofocus device based on the electron beam measurement equipment of the embodiment of the present application;

FIG. 5 shows a structural block diagram of an autofocus device based on an electron beam measurement device according to an embodiment of the present application.

Detailed ways

Various exemplary embodiments, features, and aspects of the present application will be described in detail below with reference to the accompanying drawings. The same reference numbers in the figures indicate functionally identical or similar elements. While various aspects of the embodiments are shown in drawings, the drawings are not necessarily drawn to scale unless specifically indicated.

The word "exemplary" is used exclusively herein to mean "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior or better than other embodiments.

In addition, in order to better illustrate the present application, numerous specific details are given in the following specific implementation manners. It will be understood by those skilled in the art that this application may be practiced without certain of the specific details. In some instances, methods, means, components and circuits well known to those skilled in the art have not been described in detail in order to highlight the gist of the present application.

FIG. 1 shows a flowchart of an autofocus method based on an electron beam measuring device according to an embodiment of the present application. As shown in FIG. 1 , the method includes: Step S100 , acquiring a plurality of detection images collected by a current channel in an electron beam measurement device. Here, it should be noted that the electron beam measurement equipment in the embodiment of the present application mainly refers to nanoscale electron beam measurement equipment, such as a scanning electron microscope, specifically a CD-SEM (Critical Dimension SEM). CD-SEM is a key equipment for quality control in the chip manufacturing process. It can be used for the measurement and analysis of nano-scale silicon wafer patterns, and realizes the monitoring of key process parameters. Among them, those skilled in the art can understand that when electron beam measurement equipment is used to measure and analyze silicon wafer patterns, usually a certain channel of the detector in the electron beam measurement equipment is used to collect the image of the sample to be tested. , and then perform corresponding defect detection based on the collected images.

After the multiple detection images collected by the current channel of the electron beam measuring device are obtained, step S200 can be executed to adaptively adjust the coarse focus search step according to the sharpness evaluation results of the multiple detection images, and according to the adjusted coarse The focus search step performs coarse focus on the electron beam measuring equipment, and determines the best coarse focus position. Then, through step S300, take the best coarse focus position as the search center, collect a preset number of sample images according to the current coarse focus search parameters, and evaluate the result according to the sharpness of the collected preset number of sample images Perform a fine-focus search to get focused results.

Wherein, it should be noted that, in the method of the embodiment of the present application, the fine-focus search parameter includes at least one of a fine-focus search range and a fine-focus search step. Those skilled in the art can understand that the fine focus search step refers to the sampling frequency when sampling the image of the sample during the fine focus process, and the fine focus search range refers to the electron frequency when the sample is collected during the fine focus process. The value range of the current value of the beam measuring device.

Therefore, in the method of the embodiment of the present application, during the auto-focusing process of the electron beam measurement equipment, multiple detection images collected by the current channel of the electron beam measurement equipment are obtained, and then according to the clarity of the multiple detection images The evaluation results adaptively adjust the coarse focus search step, and perform coarse focus on the electron beam measuring equipment according to the adjusted coarse focus search step, and determine the best coarse focus position. Then take the best coarse focus position as the search center, collect a preset number of sample images according to the current fine focus search parameters, and finally perform a fine focus search according to the sharpness evaluation results of the collected preset number of sample images The focus result is obtained, which realizes the coarse focus in the autofocus process of the electron beam measurement equipment by adopting a variable step size, which makes the coarse focus search step used in the coarse focus more flexible, and finally effectively improves the electron beam. Autofocus efficiency of the beam measurement device.

It should be noted that when the coarse focus search step is adaptively adjusted according to the sharpness evaluation results of multiple detection images, it is necessary to perform sharpness evaluation on the multiple detection images first. In a possible implementation manner, it may be implemented in the following manner.

First, the contrast of each detected image is unified, and median filtering is performed on each detected image. Then, sharpness evaluation is performed on each detected image after median filtering to obtain a first sharpness evaluation result. Further, the coarse focus search step is determined according to the first sharpness evaluation result.

Specifically, unifying the contrast of each detection image can be realized by defining the histogram of each detection image. Wherein, the histogram specification of each detection image can be realized by conventional technical means in the field, and details will not be repeated here.

At the same time, each detection image after median filtering is evaluated for sharpness to obtain the sharpness evaluation result, then the spectral histogram of each detection image can be obtained by performing Fourier transform on each detection image after median filtering, and then Multi-interval normalization is performed on each spectrum histogram, and logical operation is performed on the normalized spectrum histogram to obtain the evaluation curve of each detection image. Finally, based on the evaluation curves of each detected image, the sharpness evaluation result is obtained.

Here, it should be noted that when the multi-interval normalization processing is performed on each spectrum histogram, the division of the intervals can be flexibly set according to the actual situation, which is not specifically limited here. Performing a logical operation on the normalized spectrum histogram may include performing weighted summation on the normalized spectrum histogram. That is, weighted summation is performed on the normalized results of each interval of the spectrum histogram. Wherein, the weighted summation of the normalized spectrum histograms may be implemented by using a conventional weighted summation algorithm in the field, which will not be repeated here.

In addition, it should also be noted that when performing logical operations on the normalized spectrum histogram, it also includes performing high-frequency and low-frequency amplification operations on image content in the spectrum histogram. By performing high-frequency and low-frequency amplification processing on the image information in the spectrum histogram of each detection image, the richness of image features is effectively extracted, making it more accurate to evaluate the sharpness of each detection image.

Further, after median filtering is performed on each detected image, the method further includes calculating an average local variance curve of the detected images after median filtering. Correspondingly, when the sharpness evaluation result is obtained based on the evaluation curves of each detected image, it includes: calculating the correlation between each evaluation curve and the average local variance curve, and then obtaining the image sharpness evaluation result according to the calculated correlations .

In a possible implementation manner, when the sharpness evaluation result is obtained according to the calculated correlations, an evaluation curve with the highest correlation may be selected from the correlations as the sharpness evaluation result.

In order to more clearly illustrate the coarse focusing process in the embodiment of the present application, a specific embodiment will be used to describe in more detail below.

Referring to Fig. 2, in the method of the embodiment of the present application, after obtaining the N detection images collected by the current channel of the electron beam measuring equipment through step S100, step S210 can be executed to perform the N detection images obtained Carry out the histogram specification respectively, then through step S220, carry out median filtering on the detection image with the histogram specification, then through step S231, perform Fourier transform on the detection image after the histogram specification processing and median filtering , to obtain the corresponding spectrum histogram, and through step S232 in turn, the spectrum in the spectrum histogram of each detection image obtained is normalized to a plurality of intervals respectively, and through step S233, the normalized spectrum histogram Weighted summation is performed, and then through step S234, an evaluation curve of each detected image is obtained.

At the same time, referring to FIG. 2 , after performing median filtering on the detection image after histogram specification, step S230' is also included to calculate the average local variance on the detection image after median filtering to obtain a corresponding reference score curve.

Then, through step S240, the obtained evaluation score curve and reference score curve are normalized, and through step S250, the correlation between each evaluation score curve and the reference score curve is calculated. Here, it should be pointed out that, when calculating the correlation between each evaluation score curve and the reference score curve, it can be realized by using a conventional correlation calculation method in the art, which will not be repeated here.

Further, through step S260, the evaluation score curve with the highest correlation is selected from the calculated correlations as the final image definition evaluation result. Finally, step S270 is executed again to output a set of evaluation score curves with the highest correlation.

Through the above steps, the sharpness evaluation of the collected N detection images can be completed, and a corresponding sharpness evaluation result can be obtained. Then, the corresponding coarse focus search step is determined according to the obtained sharpness evaluation result, and finally the coarse focus search is performed according to the determined coarse focus search step, so as to determine the best coarse focus position.

Here, it should be pointed out that the exhaustive search method can be used directly when performing the coarse focus search according to the determined coarse focus search step size, and details will not be described here.

Furthermore, after completing the coarse focusing process of the electron beam measuring equipment through any of the above methods, and determining the corresponding best coarse focusing position, the electron beam measuring equipment can be searched for fine focusing, so as to finally realize Automatic focusing of electron beam measuring equipment.

Specifically, in the method of the embodiment of the present application, after the optimal coarse focus position is determined, the process of fine-focusing the electron beam measurement equipment mainly includes: first, taking the best coarse focus position as the search center, according to the current The fine focus search parameter captures a preset number of sample images. Then, according to the sharpness evaluation results of the collected preset number of sample images, a fine focus search is performed to obtain the focus result.

Wherein, the process of performing the fine-focus search according to the sharpness evaluation results of the collected preset number of sample images can be carried out in a variable step size manner. Specifically, when the variable step size method is used to perform fine-focus search, it can be implemented in an iterative manner.

That is, according to the sharpness evaluation results of the preset number of sample images currently obtained, the fine-focus search parameters are updated, and the preset number of sample images are re-collected with the updated fine-focus search parameters until the number of re-acquisitions until the preset number of iterations is reached.

Meanwhile, according to the foregoing, in the method of the embodiment of the present application, the fine-focus search parameter includes at least one of a fine-focus search range and a fine-focus search step. When performing an update of the fine-focus search parameters, it is performed according to the sharpness evaluation results of the preset number of sample images currently obtained, so that in the method of the embodiment of the present application, when performing a fine-focus search on the electron beam measuring device It is also possible to adopt a variable step size method, which further improves the focusing speed of the device.

At the same time, it should also be noted that the sharpness evaluation method described above can be used when evaluating the sharpness of the collected sample images with a preset number of sheets, which will not be repeated here.

In addition, when the fine-focus search is performed according to the sharpness evaluation results of the collected preset number of sample images, it may be performed based on the change trend of the sharpness evaluation results of the preset number of sample images. Wherein, the change trend of the sharpness evaluation results of the preset number of sample images includes at least one of monotonically increasing, monotonically decreasing, and quadratic fitting of the sharpness curve.

Specifically, when the change trend of the definition evaluation results of the preset number of sample images is monotonously increasing, the forward search is performed, the search range is updated, and the preset number of sample images are re-acquired based on the updated search range.

When the change trend of the sharpness evaluation results of the preset number of sample images is monotonically decreasing, the backward search is performed, the search range is updated, and the preset number of sample images is re-acquired based on the updated search range.

When the change trend of the sharpness evaluation results of the preset number of sample images is that the sharpness curve is quadratic fitting, the fine focus search parameters are updated according to the opening direction of the fitted curve, and the fine focus search parameters are updated based on the updated fine focus search parameters. Reacquisition of a preset number of sample images.

Here, it should be noted that the opening direction of the fitting curve is divided into upward opening and downward opening. When the opening direction of the fitting curve is upward, the fine focus search range and the fine focus search step are updated with the currently evaluated clearest position as the center, and a preset number of sample images are collected again. When the opening direction of the fitting curve is downward, centering on the position of the symmetry axis of the quadratic function, the fine focus search range and the fine focus search step are updated to re-acquire a preset number of sample images.

For example, if the acquired image is 5, the sharpness evaluation curve opens upward, assuming that the clearest position is 2, and the current value at this position is L, then the current value of the second image is centered, and the search step is updated (generally Under the circumstances, take 1.5 times of the previous step size), and update the search range L±2*1.5*step.

Correspondingly, if the set image is 5, the sharpness evaluation curve opens downward, assuming that the clearest position is 3, and the current value at this position is L, then the current value of the third image is centered, and the search range L±step is updated , the update step size is 2*step/4.

Among them, those skilled in the art can understand that, when the change trend of the sharpness evaluation result is monotonically increasing, the forward search refers to the current value of the image corresponding to the position of the maximum value in the monotonically increasing curve. The starting point is along the increasing direction of the curve, and a preset number of sample images are collected again according to the updated fine focus search range and fine focus search step. Here, it should be noted that when updating the fine-focus search parameters, only the fine-focus search range needs to be updated, and the fine-focus search step remains unchanged from the initial step.

For example, if the number of collected images is 5, the sharpness evaluation curve increases monotonically, assuming that the clearest position is 5, and the current value at this position is L, then the current value of the fifth image is the starting point, with a fixed step size, and updates The search range is L～(L+4*step).

When the change trend of the definition evaluation result is monotonically decreasing, the backward search refers to the current value of the image corresponding to the position of the minimum value in the monotonically decreasing curve. The updated fine focus search range and fine focus search step are used to re-acquire a preset number of sample images. Here, it should be noted that when updating the fine-focus search parameters, only the fine-focus search range needs to be updated, and the fine-focus search step remains unchanged from the initial step. For example, if the number of captured images is 5 frames, and the sharpness evaluation curve is monotonically decreasing, assuming that the clearest position is 1, and the current value at this position is L, then the current value of the first frame image is the starting point, with a fixed step size, Update the search range: (L-4*step)～L.

In order to more clearly illustrate the auto-focus method based on the electron beam measurement device of the embodiment of the present application, a specific embodiment will be used as a more detailed and complete description below.

Referring to FIG. 3 , firstly, through step S001 , parameters are set, specifically including: the maximum number of iterations t, the initial search step size of the fine focus, and the search range of the fine focus.

Then, through step S100, a certain number of detection images collected by the current channel of the electron beam measuring device are acquired. Then, through step S200, the sharpness evaluation is performed on each of the collected detection images to obtain the corresponding sharpness evaluation results, and the corresponding coarse focus search step is determined according to the obtained sharpness evaluation results, and according to the determined coarse focus The search step size performs a coarse focus search operation. Specifically, based on the exhaustive search, the sharpness score of each frame sample image is performed, and according to the change rate of the sharpness score of adjacent images, the search step is adaptively adjusted to determine the best coarse focus position.

Then, through step S310, set the fine focus search range with the current best coarse focus position as the search center, and perform fine focus search within the set fine focus search range, and then execute step S320, and initialize the number of iterations t=0 .

Step S330, collect a preset number (nums) of sample images with the initially set fine-focus search step, and perform a sharpness evaluation on each frame of images through step S340 (see Figure 2 for the specific image sharpness evaluation process. shown), to obtain the clarity evaluation results.

Then, through step S351 , it is judged whether the obtained sharpness evaluation result (that is, the change curve of the sharpness results of each frame image according to the order of frames) shows a monotonous increasing trend. When it is determined that the obtained sharpness evaluation results show a monotonically increasing trend, step S361 is executed, and a forward search is performed starting from the maximum value among the monotonically increasing sharpness evaluation results. When it is judged that the obtained sharpness evaluation result is not in a monotonous increasing trend, then step S352 is used to determine whether the sharpness evaluation result is in a monotonous decreasing trend. When it is determined that the sharpness evaluation results show a monotonically decreasing trend, step S362 is executed, and a backward search is performed with the minimum of the monotonically decreasing sharpness evaluation results as the starting point. After the direction to perform the fine-focus search again is determined through the above steps, step S371 can be executed to update the fine-focus search range and keep the fine-focus search step unchanged.

When it is determined through step S352 that the sharpness evaluation result is a quadratic curve fitting, then through step S363 it is determined whether the opening of the quadratic fitting curve is upward. When it is judged that the opening is upward, step S373 is executed to update the fine focus search range centered on the clearest position, and at the same time update the fine focus search step. When it is judged that the opening is downward, step S372 is executed to update the fine focus search range centered on the position of the symmetry axis, and at the same time update the fine focus search step.

That is, according to the clarity evaluation results, it can be roughly divided into the following three situations:

case1. The sharpness curve increases monotonically, then search forward and update the search range;

case2. The sharpness curve is monotonically decreasing, then search backward and update the search range;

case3. Quadratic fitting of the sharpness curve. If the opening is upward, the currently evaluated clearest position will be the center, and the search range and search step will be updated. Otherwise, the search range and search will be updated based on the position of the symmetry axis of the quadratic function. step size.

Simultaneously, after updating the fine focus search parameters, and through step S380, the iteration number of the current count is judged, if t<maximum iteration number, then execute step S391, the iteration number t set is counted (t=t+ 1), and return to S330 to collect the sample image again and perform a fine focus search; otherwise, the iteration ends, through step S392, the iteration ends, and the focus result is output.

Therefore, the method of the embodiment of the present application proposes a brand-new autofocus method for electron beam measuring equipment by improving the image sharpness evaluation function and search strategy. The processing such as histogram specification and median filtering unifies the contrast of the image to a certain extent, filters out redundant noise of the image, and highlights the characteristics of the image. At the same time, the final evaluation result is corrected based on the local variance curve of the image, which effectively weakens the influence of image content diversity and contrast on the image sharpness score, and improves the reliability of the sharpness score. In the search strategy, the variable step length search strategy is adopted in both the coarse focusing and fine focusing processes, which effectively saves the search time and improves the search efficiency.

That is to say, since the image contrast may change due to the influence of the acquisition environment during the continuous acquisition process, directly calculating the sharpness of the filtered image will inevitably affect the final evaluation result. Therefore, in the autofocus method of the electron beam measuring equipment in the embodiment of the present application, firstly, the contrast of the image is unified, and the sharpness score is performed on this basis; secondly, the median filter is performed on the image to filter out noise, and the comprehensive Consider the information of each frequency band of the image to highlight the image features; finally, using the local variance as a reference, calculate its correlation with different intervals, and choose the best as the final definition evaluation result, which improves the accuracy of the evaluation results and reduces the image falling into the local maximum. excellent risk. At the same time, the automatic focus variable step length climbing mountain search also greatly saves the search time and improves the timeliness of automatic focus.

Correspondingly, based on any one of the foregoing autofocus methods based on electron beam measurement equipment, the present application also provides an autofocus device based on electron beam measurement equipment. Since the working principle of the autofocus device based on the electron beam measuring equipment provided in the present application is the same or similar to the principle of the autofocus method based on the electron beam measuring equipment of the present application, repeated descriptions will not be repeated here.

Referring to FIG. 4 , the autofocus device based on electron beam measurement equipment provided by the present application includes an image acquisition module, a coarse focus module and a fine focus module. Wherein, the image acquisition module is configured to acquire multiple detection images collected by the current channel in the electron beam measurement device. The coarse focus module is configured to adaptively adjust the coarse focus search step according to the sharpness evaluation results of the multiple detection images, and perform coarse focus on the electron beam measuring device according to the adjusted coarse focus search step to determine the best coarse focus. focus position. The fine focus module is configured to take the best coarse focus position as the search center, collect a preset number of sample images according to the current fine focus search parameters, and evaluate the result according to the sharpness of the collected preset number of sample images Perform a fine-focus search to get focused results.

Furthermore, according to another aspect of the present application, an auto-focus device 200 based on an electron beam measurement device is also provided. Referring to FIG. 5 , the autofocus device 200 based on the electron beam measuring device according to the embodiment of the present application includes a processor 210 and a memory 220 for storing instructions executable by the processor 210 . Wherein, the processor 210 is configured to implement any one of the aforementioned autofocus methods based on electron beam measurement equipment when executing executable instructions.

Here, it should be noted that the number of processors 210 may be one or more. Meanwhile, in the autofocus device 200 based on the electron beam measurement device in the embodiment of the present application, an input device 230 and an output device 240 may also be included. Wherein, the processor 210 , the memory 220 , the input device 230 and the output device 240 may be connected through a bus or in other ways, which are not specifically limited here.

The memory 220, as a computer-readable storage medium, can be used to store software programs, computer-executable programs and various modules, such as the programs or modules corresponding to the autofocus method based on the electron beam measurement device in the embodiment of the present application. The processor 210 executes various functional applications and data processing of the autofocus device 200 based on the electron beam measuring device by running the software programs or modules stored in the memory 220 .

The input device 230 can be used to receive input numbers or signals. Wherein, the signal may be a key signal related to user setting and function control of the device/terminal/server. The output device 240 may include a display device such as a display screen.

According to another aspect of the present application, there is also provided a non-volatile computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by the processor 210, any one of the aforementioned electron beam-based Measure the autofocus method of the device.

Having described various embodiments of the present application above, the foregoing description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and alterations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principle of each embodiment, practical application or improvement of technology in the market, or to enable other ordinary skilled in the art to understand each embodiment disclosed herein.

Claims

An automatic focusing method based on an electron beam measuring device, characterized in that it comprises:

Obtain multiple detection images collected by the current channel in the electron beam measurement device;

Adaptively adjust the coarse focus search step according to the sharpness evaluation results of the plurality of detected images, and perform coarse focus on the electron beam measuring device according to the adjusted coarse focus search step to determine the best coarse focus Location;

Taking the best coarse focus position as the search center, collect a preset number of sample images according to the current fine focus search parameters, and perform fine focusing according to the sharpness evaluation results of the collected preset number of sample images Search for the focused results.
The method according to claim 1, wherein, adaptively adjusting the coarse focus search step size according to the sharpness evaluation results of a plurality of said detected images, comprising:

unifying the contrast of each of the detected images, and performing median filtering on each of the detected images;

Carrying out sharpness evaluation on each of the detected images after median filtering to obtain a sharpness evaluation result;

The coarse focus search step size is determined according to the sharpness evaluation result.
The method according to claim 2, characterized in that unifying the contrast of each of the detected images is performed by performing a histogram definition process on each of the detected images.
The method according to claim 2, wherein the sharpness evaluation is performed on each of the detected images after median filtering to obtain a sharpness evaluation result, including:

performing Fourier transform on each of the detected images after median filtering to obtain a spectrum histogram of each of the detected images;

performing multi-interval normalization on each of the spectrum histograms, and performing logic operations on the normalized spectrum histograms to obtain the evaluation curves of each of the detection images;

Based on the evaluation curve of each of the detected images, the definition evaluation result is obtained.
The method according to claim 4, characterized in that, while performing logical operations on the normalized spectrum histogram, it also includes the operation of performing high-frequency and low-frequency amplification on the image content in the spectrum histogram.
The method according to claim 4, wherein the logic operation on the normalized spectrum histogram includes performing weighted sum processing on the normalized spectrum histogram.
The method according to claim 4, wherein after performing median filtering on each of the detected images, further comprising: calculating an average local variance curve of the detected images after median filtering;

Correspondingly, the definition evaluation result is obtained based on the evaluation curves of each of the detected images, including:

calculating a correlation of each of said evaluation curves with said mean local variance curve, respectively;

The sharpness evaluation result is obtained according to each of the calculated correlations.
The method according to claim 7, characterized in that, when the image definition evaluation result is obtained according to each of the calculated correlations, the evaluation curve with the highest correlation is selected from each of the correlations as the Clarity evaluation results.
The method according to any one of claims 1 to 8, wherein the fine focus search parameters include at least one of a fine focus search range and a fine focus search step size.
The method according to any one of claims 1 to 8, characterized in that, when performing a fine-focus search to obtain the focus result based on the sharpness evaluation results of the collected sample images of the preset number of sheets, variable steps are used Long way to search.
The method according to claim 10, characterized in that, when performing a fine-focus search according to the sharpness evaluation results of the collected sample images of the preset number of sheets by using a variable step size method to obtain the focus result, it includes:

Updating the fine-focus search parameters according to the sharpness evaluation results of the preset number of sample images currently obtained, and re-acquisition of the preset number of sample images with the updated fine-focus search parameters, Until the number of re-acquisitions reaches the preset number of iterations.
The method according to any one of claims 1 to 8, characterized in that when performing a fine-focus search based on the sharpness evaluation results of the collected sample images of the preset number, based on the preset number of The change trend of the sharpness evaluation results of the sample image is carried out;

Wherein, the change trend of the sharpness evaluation results of the preset number of sample images includes at least one of monotonically increasing, monotonically decreasing, and quadratic fitting of the sharpness curve;

When the change trend of the sharpness evaluation results of the preset number of sample images is monotonically increasing, perform a forward search, update the search range and re-acquire the preset number of sample images based on the updated search range ;

Perform a backward search when the change trend of the definition evaluation results of the preset number of sample images is monotonically decreasing, update the search range and re-acquire the preset number of sample images based on the updated search range ;

When the change trend of the sharpness evaluation results of the preset number of sample images is that the sharpness curve is quadratic fitting, the fine focus search parameters are updated according to the opening direction of the fitted curve, and based on the updated fine focus search parameter to perform reacquisition of the preset number of sample images.
An automatic focusing device based on electron beam measuring equipment, characterized in that it includes an image acquisition module, a coarse focusing module and a fine focusing module;

The image acquisition module is configured to acquire multiple detection images collected by the current channel in the electron beam measurement device;

The coarse focus module is configured to adaptively adjust the coarse focus search step size according to the sharpness evaluation results of the plurality of detection images, and adjust the electron beam measurement device according to the adjusted coarse focus search step size Carry out coarse focus and determine the best coarse focus position;

The fine focusing module is configured to take the best coarse focus position as the search center, collect a preset number of sample images according to the current fine focus search parameters, and collect samples according to the preset number of samples collected. The sharpness evaluation result of the image is subjected to a fine focus search to obtain the focus result.
An automatic focusing device based on an electron beam measuring device, characterized in that it comprises:

processor;

memory for storing processor-executable instructions;

Wherein, the processor is configured to implement the method according to any one of claims 1 to 12 when executing the executable instructions.
A non-volatile computer-readable storage medium on which computer program instructions are stored, wherein the computer program instructions implement the method according to any one of claims 1 to 12 when executed by a processor.