Brightness contrast adjustment method and device of metrology equipment, and metrology equipment

Abstract

The application provides a brightness contrast adjustment method and device of a measurement equipment and the measurement equipment. The brightness contrast adjustment method comprises the following steps: obtaining a target image and determining a target average gray value of the target image; obtaining a current measurement image and determining a measurement average gray value of the current measurement image; judging whether a first difference between the measurement average gray value of the current measurement image and the target average gray value meets a preset condition; when the first difference does not meet the preset condition, updating a current contrast based on a current iteration number and reacquiring a measurement image based on the updated contrast; judging whether the reacquired measurement image falls into a local optimum; when the reacquired measurement image does not fall into the local optimum, updating the current iteration number and returning to the steps of obtaining the current measurement image and determining the measurement average gray value of the current measurement image until the first difference meets the preset condition.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of semiconductor element detection, in particular to a brightness contrast adjustment method and device of a measurement equipment and the measurement equipment. BACKGROUND

[0002] In integrated circuit manufacturing, CD (Critical Dimension: the most critical and important size parameter in a chip or device) measurement is a very common and important step in a semiconductor manufacturing factory.

[0003] The most common CD measurement machine in current semiconductor manufacturing factories is an electron beam-based measurement device. In the measurement process, the device is affected by wafer material and photolithography process. Under the same scanning conditions of the same parameter indicators, the imaging effects of different positions in the same wafer image or different wafer images are quite different, mainly reflected in the difference in brightness and contrast of the image. The difference in brightness and contrast will have a certain impact on the measurement result. To reduce the impact of SEM image fluctuations on measurement, the brightness and contrast parameters of the detector need to be automatically adjusted to ensure the consistency of the SEM image.

[0004] The prior art usually determines the required brightness value according to the relationship between the target brightness and the image brightness indicator first, and then determines the required contrast value according to the relationship between the target contrast and the image contrast indicator after adjusting the brightness. The brightness and contrast are adjusted repeatedly until the final brightness and contrast meet the requirements. However, the prior art relies heavily on the accuracy of the relationship, and the diversity of different wafer types and photolithography processes will lead to inaccuracy of the relationship, thereby reducing the universality and stability of the method. Moreover, since brightness and contrast are two interrelated indicators that are nonlinearly related to each other, there may be interactive coupling during the adjustment process, leading to repeated cycle adjustment, code redundancy, and affecting the efficiency of the measurement process.

[0005] Based on the above, the present application is proposed. SUMMARY

[0006] To solve the technical problems existing in the prior art, the present application provides a brightness and contrast adjustment method and device of a measurement equipment with high universality and stability.

[0007] According to a first aspect of the present application, a brightness contrast adjustment method of a metrology device is provided, comprising: obtaining a target image, determining a target average gray value of the target image; obtaining a current metrology image, determining a metrology average gray value of the current metrology image; judging whether a first difference value between the metrology average gray value of the current metrology image and the target average gray value meets a preset condition; when the first difference value does not meet the preset condition, updating a current contrast based on a current iteration number and reacquiring a metrology image based on the updated contrast; judging whether the reacquired metrology image falls into a local optimum; when the reacquired metrology image does not fall into the local optimum, updating the current iteration number and returning to execute the steps of obtaining a current metrology image and determining a metrology average gray value of the current metrology image until the first difference value meets the preset condition.

[0008] In a further aspect of the present application, the updating of the current contrast based on the current iteration number and the reacquiring of the metrology image based on the updated contrast comprises: when the current iteration number is greater than or equal to an iteration number threshold, updating the current contrast based on a relationship between the metrology average gray value and the contrast and reacquiring the metrology image based on the updated contrast; when the current iteration number is less than the iteration number threshold, updating the current contrast based on the size of the first difference value and reacquiring the metrology image based on the updated contrast.

[0009] In a further aspect of the present application, the updating of the current contrast based on the current iteration number and the reacquiring of the metrology image based on the updated contrast comprises: when the current iteration number is less than the iteration number threshold, segmenting the first difference value into intervals according to the range of the first difference value; determining a mapped contrast variation according to the interval segmentation; and updating the current contrast according to the contrast variation.

[0010] In a further aspect of the present application, the updating of the current contrast based on the current iteration number and the reacquiring of the metrology image based on the updated contrast comprises: updating a prediction relationship between the metrology average gray value and the contrast according to the current contrast and the metrology average gray value of the current metrology image; determining a predicted contrast value according to the updated prediction relationship; and updating the current contrast based on the predicted contrast value.

[0011] In a further aspect of the present application, the relationship between the metrology average gray value and the contrast is:

[0012] C=k*X+b

[0013] Wherein, C is the contrast, k and b are a first adjustment coefficient and a second adjustment coefficient, and X is the metrology average gray value.

[0014] In a further aspect of the present application, the method further comprises: when the first difference value is less than a preset first threshold, determining that the first difference value satisfies the preset condition; when the first difference value is between the first threshold and a preset second threshold, determining that the first difference value does not satisfy the preset condition; and when the first difference value is greater than the second threshold, updating the current brightness according to the first difference value and reacquiring the measurement image based on the updated brightness until the first difference value is between the first threshold and the second threshold.

[0015] In a further aspect of the present application, the brightness and contrast adjustment method further comprises: when the current iteration number is greater than or equal to a preset maximum iteration number, determining that the brightness and contrast adjustment fails.

[0016] In a further aspect of the present application, the method further comprises: when the reacquired measurement image falls into a local optimum, updating the current contrast based on the size of the first difference value and reacquiring the measurement image based on the updated contrast until the reacquired measurement image does not fall into the local optimum.

[0017] In a further aspect of the present application, the method further comprises: obtaining a contrast value of the reacquired measurement image, comparing the contrast value of the reacquired measurement image with a contrast value of the acquired measurement image to obtain a contrast variation; comparing a measurement average gray value of the reacquired measurement image with a measurement average gray value of the acquired measurement image to obtain an average gray variation; and when the contrast variation is less than a preset contrast variation threshold for a preset number of times in succession and the average gray variation is less than a preset gray variation threshold for a preset number of times in succession, determining that the reacquired measurement image falls into the local optimum.

[0018] The second aspect of the present application also provides a brightness contrast adjustment device of a metrology device, comprising: a first determination module configured to obtain a target image and determine a target average gray value of the target image; a second determination module configured to obtain a current metrology image and determine a metrology average gray value of the current metrology image; a first judgment module configured to judge whether a first difference between the metrology average gray value of the current metrology image and the target average gray value meets a preset condition; a first calculation module configured to, when the first difference does not meet the preset condition, update a current contrast based on a current iteration number and reacquire a metrology image based on the updated contrast; a second judgment module configured to judge whether the reacquired metrology image falls into a local optimum; and a second calculation module configured to, when the reacquired metrology image does not fall into the local optimum, update the current iteration number and return to execute the steps of obtaining the current metrology image and determining the metrology average gray value of the current metrology image until the first difference meets the preset condition to obtain a target contrast.

[0019] Finally, the present application also provides a metrology device, comprising: an emission module configured to emit an electron beam to a wafer; an acquisition module configured to collect and process an electronic signal on the wafer to generate an image; and a host computer electrically connected to the emission module and the acquisition module, wherein the host computer comprises a processor and a memory storing computer program instructions; and the processor implements the brightness contrast adjustment method of the metrology device as described above when executing the computer program instructions.

[0020] In summary, the present application provides a brightness contrast adjustment method of a metrology device, which at least has the following technical effects:

[0021] The adjustment method adjusts the contrast parameter and uses the first difference as the judgment condition, that is, when the average gray value of the current metrology image is close to the target gray value of the target image, it is considered that the adjustment is successful. The two-dimensional adjustment is reduced to one-dimensional adjustment, which greatly reduces the adjustment time and improves the efficiency of automatic brightness contrast adjustment.

[0022] Different target images can be set for different processes, different lithography processes and different material wafers, which improves the flexibility of automatic brightness contrast setting. By introducing the local optimum mechanism, the iteration number is updated when the local optimum is not reached, and the main loop is exited after the first difference meets the preset condition, which avoids repeated adjustment and redundant operation and improves the efficiency.

[0023] The collected features and advantages of the embodiments of the present application will be described in the subsequent specific implementation part. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the description of the embodiments or the prior art. Obviously, the drawings described below are some embodiments of the present application, and the drawings collected by those skilled in the art without creative labor can also be obtained.

[0025] Figure 1 The total flow chart of the brightness contrast adjustment method of the measuring device provided by the embodiment of the present application;

[0026] Figure 2 The flow chart of step S400 in the brightness contrast adjustment method of the measuring device provided by the embodiment of the present application;

[0027] Figure 3 The flow chart of step S402 in the brightness contrast adjustment method of the measuring device provided by the embodiment of the present application;

[0028] Figure 4 The flow chart of step S401 in the brightness contrast adjustment method of the measuring device provided by the embodiment of the present application;

[0029] Figure 5 The flow chart of step S300 in the brightness contrast adjustment method of the measuring device provided by the embodiment of the present application;

[0030] Figure 6 The flow chart of step S500 in the brightness contrast adjustment method of the measuring device provided by the embodiment of the present application;

[0031] Figure 7 The control logic diagram of the brightness contrast adjustment method of the measuring device provided by the embodiment one of the present application;

[0032] Figure 8 The curve diagram of the contrast and the average gray value of the measuring in the updating contrast process of the embodiment of the present application; and

[0033] Figure 9 The module schematic diagram of the brightness contrast adjustment device provided by the embodiment of the present application.

[0034] Label description

[0035] 100, brightness contrast adjustment device;

[0036] 10, first determination module; 20, second determination module;

[0037] 30, first judgment module; 40, first calculation module;

[0038] 50, a second judging module; 60, a second calculating module. DETAILED DESCRIPTION

[0039] In order to make the above and other features and advantages of the present application more apparent, the present application will be further described below with reference to the accompanying drawings. It should be understood that the specific embodiments given herein are intended for explanatory purposes only and are not intended to limit the scope of the present application.

[0040] In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. It will be apparent, however, to one skilled in the art that the specific details need not be employed to practice the present application. In some instances, well-known steps or operations have not been described in detail in order to avoid obscuring the present application.

[0041] Reference will first be made to Figure 1 , Figure 1 A general flowchart of a brightness contrast adjustment method of a metrology device provided by an embodiment of the present application.

[0042] The general inventive concept of an embodiment of the present application provides a brightness contrast adjustment method of a metrology device, comprising the following steps:

[0043] Step S100, acquiring a target image and determining a target average gray value of the target image;

[0044] Step S200, acquiring a current metrology image and determining a metrology average gray value of the current metrology image;

[0045] Step S300, judging whether a first difference between the metrology average gray value and the target average gray value satisfies a preset condition;

[0046] Step S400, when the first difference does not satisfy the preset condition, updating the current contrast based on a current iteration number and reacquiring a metrology image based on the updated contrast;

[0047] Step S500, judging whether the reacquired metrology image falls into a local optimum;

[0048] Step S600, when the reacquired metrology image does not fall into the local optimum, updating the current iteration number and returning to execute the step of acquiring the current metrology image and determining the metrology average gray value of the current metrology image until the first difference satisfies the preset condition.

[0049] The metrology device is a device capable of acquiring image information of various parameters and features on a wafer, and is used for non-contact or semi-contact detection and measurement of the wafer, such as a CD measuring machine.

[0050] In steps S100-S200, the "target image" refers to an image sample pre-registered as a standard, and the "current measurement image" is an image collected in real time by the measurement device during operation.

[0051] First, the target image is pre-configured, and the target average gray value of the target image is calculated and recorded. Then, the measurement device is controlled to collect a current measurement image, and the measurement average gray value of the current measurement image is also calculated. In an exemplary scheme, obtaining the average gray value of the target image or the measurement image can include: after loading the measurement image / image image into a preset file path, respectively, converting the image into a gray image (if the image is not a gray image), and then calculating the average of the gray values of all pixels in the image, i.e., the average gray value, which is usually between 0 and 255, and can represent the overall brightness of the image.

[0052] Then, the target average gray value and the two-side average gray value are subtracted to obtain a first difference value, and it is determined whether the first difference value meets a preset condition. When the first difference value does not meet the preset condition, the contrast is updated in a loop, and the image is re-collected based on the updated contrast. Then, a judgment mechanism for falling into a local optimum is further added to the re-collected measurement image, and the iteration number is accumulated and returned to step S200 again when the measurement image jumps out of the local optimum. That is, steps S200-step S600 are looped.

[0053] Further in step S400, it is explained that the current iteration number is used as a counting loop condition, different contrast update models are selected, and the current contrast is updated using the selected contrast update model.

[0054] It can be understood that using the current iteration number as the loop condition can ensure that the contrast update model can change according to the current iteration number. By setting multiple methods for updating the current contrast, potential problems such as repeated iteration of the same contrast update model but always falling into a local optimum can be avoided, the algorithm can be fully executed, effective changes or convergence to the desired result can be generated, and the robustness and generalization ability of the entire adjustment method can be enhanced.

[0055] Further in steps S500-S600, the local optimum judgment is performed on the re-collected measurement image, the iteration number is counted when the local optimum is not fallen into, and the update is continuously looped until the first difference value meets the preset condition. In this way, falling into a local optimal solution can be avoided, and by jumping out of the local mechanism, the algorithm can escape from the limitation of the local optimal solution and continue to explore the search space, so as to speed up the convergence speed.

[0056] In summary, the brightness contrast adjustment method provided by the general inventive concept can greatly reduce the adjustment time and improve the efficiency of automatic brightness contrast adjustment by reducing the two-dimensional adjustment in the prior art to one-dimensional adjustment through cyclic updating of the current contrast.

[0057] Meanwhile, the local optimal judgment mechanism is used to determine whether the current measurement image is trapped in a local optimum, which is used as the condition for cyclic execution, so that the system can be prevented from being trapped in a local optimum to the greatest extent, the brightness contrast adjustment can find a global optimal solution, the efficiency is improved, the image quality can be improved more comprehensively and evenly, and the robustness and reliability of the system are improved.

[0058] In addition, the update contrast can be gradually optimized based on the selected update contrast based on the current iteration number, and the iteration adjustment based on real-time feedback can effectively reduce repeated adjustment and avoid redundant operation.

[0059] Based on the general inventive concept, each step is described in detail as follows:

[0060] Please refer to Figure 2 , Figure 2 The flowchart of step S400 in the brightness contrast adjustment method of the measurement device provided by the embodiment of the present application.

[0061] In a further scheme of the embodiment of the present application, the current contrast is updated based on the current iteration number in step S400, and the measurement image is reacquired based on the updated contrast, comprising:

[0062] Step S401, when the current iteration number is greater than or equal to the iteration number threshold, the current contrast is updated based on the relationship between the measurement average gray level and the contrast, and the measurement image is reacquired based on the updated contrast.

[0063] Step S402, when the current iteration number is less than the iteration number threshold, the current contrast is updated based on the size of the first difference, and the measurement image is reacquired based on the updated contrast.

[0064] It can be understood that in step S400, when the first difference satisfies the preset condition, the following two ways are provided to update the contrast based on the different iteration numbers:

[0065] When the current iteration number is greater than or equal to the iteration number threshold n, the following operations are performed:

[0066] 1) According to the relationship between the measurement average gray level and the contrast, the updated contrast is calculated.

[0067] 2) The contrast of the measurement device is reset using the updated contrast.

[0068] Conversely, when the current iteration number is less than the iteration number threshold n, the following operations are performed:

[0069] 1) Calculate the updated contrast according to the size of the first difference.

[0070] 2) Reset the contrast of the measurement device using the updated contrast.

[0071] It can be understood that based on the relationship of the current iteration number, the contrast is dynamically updated and the image is reacquired. When the iteration number is small, the contrast is updated according to the size of the first difference. When the iteration number is large, the contrast is dynamically adjusted based on the relationship between the measurement average gray value and the contrast. By using the first difference to update the contrast value in the initial iteration stage, the algorithm can quickly move towards the optimal solution. With the increase of the iteration number, the relationship between the measurement average gray value and the contrast is used to update the contrast, which can make the algorithm search more finely and improve the convergence speed. The dynamic adjustment search using the current iteration number can more effectively find the global optimal solution.

[0072] Please continue to refer to Figure 3 , Figure 3 The flowchart of step S402 in the brightness contrast adjustment method of the measurement device provided by the embodiment of the application.

[0073] In step S402, when the current iteration number is less than the iteration number threshold n, the current contrast is updated based on the size of the first difference, and the measurement image is reacquired based on the updated contrast, including:

[0074] Step S421, according to the range of the first difference, the first difference is interval segmented;

[0075] Step S422, according to the interval segmentation, the mapped contrast variation is determined;

[0076] Step S423, according to the contrast variation, the current contrast is updated.

[0077] Steps S421-S423 illustrate the method of determining the contrast variation according to the first difference, for example:

[0078] According to the size of the first difference, the interval segmentation corresponding to the first difference is determined:

[0079] The interval segmentation rule is defined in advance, for example, the first difference range is divided into m intervals, and the difference value of each interval is preset; for example, for the first difference of 20, it can be divided into four intervals of 5 / 10 / 15 / 20.

[0080] For each interval segment, a corresponding contrast change amount is predefined. For example, for the four intervals of 5 / 10 / 15 / 20, the contrast change amounts can be set to 0.05, 0.1, 0.15, and 0.2, respectively. Then, according to the interval segment to which the first difference value calculated in real time belongs, the corresponding contrast change amount is determined.

[0081] First, the current contrast value is obtained, and the current contrast is adjusted according to the contrast change amount determined above. For example, if the contrast change amount is 0.1, the current contrast is reduced by 0.1; if the contrast change amount is 0.2, the current contrast is reduced by 0.1. The updated contrast value is then applied to the contrast parameter of the system. The contrast change amount can also be understood as the step size selected in the contrast updating process.

[0082] In summary, the interval segment is determined according to the size of the first difference value, and the contrast change amount and the current contrast are updated accordingly, which can achieve dynamic adjustment and optimization of the contrast. Different first difference value ranges can correspond to different contrast change amounts, so that the appropriate contrast adjustment mode can be automatically selected according to the actual situation of the image, improving the accuracy and adaptability of the adjustment, and realizing adaptive contrast adjustment. Please note that the above steps are only examples, and the parameters need to be calibrated and optimized according to the specific application scenario.

[0083] Please continue to refer to Figure 4 , Figure 4 The flowchart of step S401 in the brightness contrast adjustment method of the measurement device provided by the embodiments of the present application.

[0084] In step S401 described above, the current contrast is updated based on the relationship between the measurement average gray value and the contrast, and the measurement image is reacquired based on the updated contrast, including:

[0085] Step S411, updating the relationship between the measurement average gray value and the contrast according to the measurement average gray value of the current measurement image;

[0086] Step S412, determining the predicted contrast value according to the updated relationship;

[0087] Step S413, updating the current contrast based on the predicted contrast value.

[0088] When the number of iterations is greater than or equal to the iteration threshold n, the preset prediction relationship is updated according to the measurement average gray value of the current measurement image, wherein the prediction relationship is the relationship between the measurement average gray value and the contrast value; then the prediction parameter is obtained using the updated prediction relationship, and the contrast parameter is updated through the prediction parameter.

[0089] It can be understood that based on the monotonic increasing characteristic between the contrast parameter and the measurement average gray value, a relationship between the contrast and the average gray can be established, and the contrast value can be predicted by continuously fitting the relationship.

[0090] It is assumed that some measurement images with different contrast parameters C have been collected, and the corresponding measurement average gray values X have been obtained, which are recorded as: X1=[a1, a2, a3, a4...]; C1=[b1, b2, b3, b4...];

[0091] In an exemplary manner, the prediction relationship is:

[0092] C=k*X+b

[0093] Wherein, C is the contrast parameter, k and b are the first and second adjustment coefficients, and X is the measurement average gray value of the current measurement image.

[0094] The above X1 and C1 data are substituted into the formula, and the prediction relationship is fitted by polynomial regression according to the data points. Finally, the values of the first and second adjustment coefficients of the relationship are obtained. With the increase of the data of the contrast parameter X and the measurement average gray value X, the continuously updated prediction relationship will be more and more close to the true relationship, and the fitting accuracy will be higher. Then, by substituting the measurement average gray value detected by the current measurement image into the prediction relationship, the required adjustment contrast parameter is predicted, and the measurement device is updated to the contrast parameter. In an exemplary scheme, specifically:

[0095] 1) Substitute the data points of X1 and C1 into the prediction relationship, such as C=k*X+b.

[0096] 2) Use a regression algorithm (such as least squares method) to fit the best first adjustment coefficient k and second adjustment coefficient b.

[0097] 3) Evaluate the accuracy of the fitting result, which can be evaluated using indicators such as fitting degree, mean square error, etc.

[0098] Once the regression fitting is completed and the values of the first adjustment coefficient k and the second adjustment coefficient b are obtained, the required contrast parameter can be predicted and controlled by the following steps, and the following steps are continued:

[0099] 1) Obtain the measurement average gray value X of the current measurement image.

[0100] 2) Substitute X into the prediction relationship C=k*X+b to calculate the predicted contrast parameter C.

[0101] 3) Apply the predicted contrast parameter C to the measurement device to update the contrast.

[0102] It should be noted that the regression fitting can only fit the relationship between the contrast parameter and the measurement average gray value to a certain extent, and the accuracy depends on the quality and distribution of the data. Therefore, when applying the fitting results for prediction and control, real-time adjustment and verification need to be made according to the actual scene of the process. In addition, the above C=k*X+b is only an example, in order to ensure the accuracy and stability of the measurement results, other factors (such as environmental light, device performance, etc.) that affect the measurement image need to be considered to establish a more complex prediction relationship, and the corresponding correction or calibration is made in the algorithm.

[0103] It can be understood that through polynomial regression fitting, the nonlinear relationship between the contrast parameter and the measurement average gray value can be captured, so that the relationship can adapt to different scenes and conditions. This means that even in varying wafer materials and process environments, the required contrast parameter can be accurately predicted according to the gray value of the current image, which has very high versatility and flexibility. At the same time, since the relationship used is fitted based on the collected data, with the number of iterations of the cycle, the relationship will be closer to the true relationship, thereby further improving the accuracy of the prediction and the authenticity of the fitting.

[0104] Please continue to refer to Figure 5 , Figure 5 The flowchart of step S300 in the brightness contrast adjustment method of the measurement device provided by the embodiment of the present application.

[0105] In the embodiment of the present application, the step S300 judges whether the first difference between the measurement average gray value of the current measurement image and the target average gray value meets the preset condition, comprising:

[0106] Step S301, when the first difference is less than the preset first threshold, it is determined that the first difference meets the preset condition;

[0107] Step S302, when the first difference is between the first threshold and the preset second threshold, it is determined that the first difference does not meet the preset condition;

[0108] Step S303, when the first difference is greater than the second threshold, the current brightness is updated according to the first difference, and the measurement image is reacquired based on the updated brightness until the first difference is between the first threshold and the second threshold.

[0109] It can be understood that step S300 increases the loop condition based on the first difference value, which is divided into three interval ranges of less than a first threshold (< threshold1), between the first threshold and a second threshold (≥ threshold1 and ≤ threshold2), and greater than the second threshold (> threshold2). When the first difference value is greater than the second threshold, it is proved that the current measurement image brightness is too high. When the first difference value is less than the first threshold, it is proved that the current measurement image has approached the target brightness, at which time it is considered that there is no need to adjust the contrast brightness. When the first difference value is between the first threshold and the second threshold, it is the time to start the loop to update the contrast, that is, only when the first difference value is between the first threshold and the second threshold, the first difference value does not meet the preset condition, at which time the loop is executed to update the contrast.

[0110] In step S303, when the first difference value between the measurement average gray value and the target average gray value exceeds the second threshold, at this time it represents that the measurement image is overexposed, first the brightness parameter of the measurement device is reduced as a whole; for example, when the first difference value is 50, the measurement device needs to adjust the brightness change amount of 25%, and the brightness value of the image is 0-255, and the brightness of the measurement device is 0-100%.

[0111] In the adjustment, step-by-step adjustment can be adopted, and the step-by-step adjustment of the brightness is achieved by gradually reducing the brightness value, for example, by increasing or decreasing the brightness value of the image by 1% each time, starting from the current brightness, increasing or decreasing a fixed step each time, the desired brightness effect can be gradually achieved until the target brightness value is reached, which can provide better control and accuracy. When the brightness of the measurement device is gradually adjusted until the first difference value enters between the first threshold and the second threshold, the adjustment is stopped.

[0112] In the embodiment of the present application, the brightness and contrast adjustment method further comprises:

[0113] Step S310, when the current iteration number is greater than or equal to the preset maximum iteration number, it is judged that the contrast and brightness adjustment fails.

[0114] It can be understood that the preset maximum iteration number can control the use of computing power, prevent dead loop, avoid excessive iteration, and provide controllability of final adjustment of brightness and contrast. In this way, the algorithm can ensure that the result is obtained within a reasonable time, and the stability and efficiency of the algorithm are guaranteed.

[0115] Further, the brightness and contrast adjustment method further comprises:

[0116] Step S700, when the re-acquired measurement image falls into a local optimum, based on the size of the first difference value, the current contrast is updated and the measurement image is re-acquired based on the updated contrast, and the updating is stopped when the re-acquired measurement image does not fall into a local optimum.

[0117] It can be understood that, due to the fact that the measured average gray and contrast in the prediction relationship are not in a completely linear relationship, there are local stable search segment data, and if the search is trapped in local optimization, the search according to the prediction relationship will cause redundant search, therefore, the first difference value is used to update the contrast in the present application, to help it jump out of the local optimization, so as to improve the operation efficiency and accelerate the convergence speed.

[0118] Please continue to refer to Figure 6 , Figure 6 The flow chart of step S500 in the brightness contrast adjustment method of the measuring device provided by the embodiment of the present application.

[0119] The judgment of whether the newly collected measuring image is trapped in local optimization in step 500 includes:

[0120] Step S501, the contrast value of the newly collected measuring image is obtained, the contrast value of the newly collected measuring image is compared with the contrast value of the collected measuring image, and the contrast change amount is obtained;

[0121] Step S502, the measured average gray value of the newly collected measuring image is compared with the measured average gray value of the collected measuring image, and the average gray change amount is obtained;

[0122] Step S503, when the contrast change amount is less than the preset contrast change amount threshold value for a continuous preset number of times, and the average gray change amount is less than the preset gray change amount threshold value for a continuous preset number of times, it is determined that the newly collected measuring image is trapped in local optimization.

[0123] In steps S501-S502, preferably, the newly collected measuring image is compared with the last collected measuring image, to obtain the change of the newly collected measuring image relative to the last collected measuring image.

[0124] When the contrast change amount is less than the preset contrast change amount threshold value for a continuous preset number of times, and the average gray change amount is less than the preset gray change amount threshold value for a continuous preset number of times, that is, the change amounts of the contrast value and the measured average gray value of the measuring image are both small, and the contrast is still updated for a plurality of times to still satisfy the condition of being less than the preset threshold value, it can be determined that the newly collected measuring image has been trapped in a local optimal state. In the current case, it is shown that the search speed is slow and the redundant search occurs when the measuring device updates the contrast.

[0125] In the further scheme of the present application, the brightness contrast adjustment method further includes:

[0126] Step S800, when the first difference value is lower than the first threshold value, the brightness characteristic is automatically adjusted successfully.

[0127] It can be understood that, with the cyclic updating of the current contrast, when the first difference is less than the first threshold, it is considered that the current contrast is close to the target contrast, and the image brightness is also close to the target brightness, so as to determine whether the adjustment process has reached the expected effect, and it is determined that the adjustment process has been completed. At this time, the whole contrast updating cycle is exited, and the brightness characteristic automatic adjustment is successfully displayed.

[0128] In summary, the embodiment of the present application provides a brightness and contrast adjustment method of a measurement device, which has at least the following technical effects: the adjustment of the contrast parameter is adopted, and the first difference is used as the determination condition, that is, when the average gray value of the current measurement image is close to the target gray value of the target image, it is considered that the adjustment is successful. The two-dimensional adjustment is reduced to one-dimensional adjustment, which greatly reduces the adjustment time and improves the efficiency of automatic adjustment of brightness and contrast. Different target images can be set for different processes, different photolithography processes and different material crystal sources, which improves the flexibility of automatic brightness and contrast setting. And by introducing the local optimal mechanism, the iteration number is updated when it is not trapped in the local optimum, and the main loop is exited after the first difference meets the preset condition, which avoids repeated adjustment and operation redundancy and improves the efficiency.

[0129] Please refer to Figure 7 and Figure 8 , Figure 7 the control logic diagram of the brightness and contrast adjustment method of the measurement device provided by the first embodiment of the present application, Figure 8 the curve diagram of the contrast and the measurement average gray value in the updating contrast process of the present application,

[0130] Based on the above brightness and contrast adjustment method, the present application provides a specific embodiment, which includes the following steps:

[0131] a. Create a recipe, register a target image, set the maximum iteration number and the preset gray range (0-255);

[0132] b. Obtain the target image and the target average gray value of the measurement image; enter c;

[0133] c. Obtain the measurement image and the measurement average gray value of the measurement image; enter d;

[0134] d. Calculate the first difference between the measurement average gray value and the target average gray value, and determine whether the first difference is greater than the second threshold; if yes, enter e, otherwise enter f;

[0135] e. Update the current brightness according to the first difference; enter f;

[0136] f. Determine whether the current iteration number is less than the maximum iteration number; if yes, enter g, otherwise enter p;

[0137] g. judging whether the first difference is less than the first threshold value; if yes, go to q, otherwise go to h;

[0138] h. judging whether the current iteration number is greater than or equal to the iteration number threshold value; if yes, go to i, otherwise go to m;

[0139] i. updating the prediction relationship of the average gray value and the contrast value of the collected measurement image; go to j;

[0140] j. predicting the contrast value according to the prediction relationship; go to k;

[0141] k. updating the contrast value and re-collecting the measurement image; go to l;

[0142] l. judging whether it falls into a local optimum; if yes, go to m, otherwise go to n;

[0143] m. updating the current contrast value based on the first difference; return to k;

[0144] n. calculating the image average gray value; go to o

[0145] o. updating the iteration number; return to f;

[0146] P. automatic brightness and contrast adjustment fails;

[0147] q. automatic brightness and contrast adjustment succeeds.

[0148] In the above embodiment, after the relevant configuration is performed, it is first judged whether the first difference is greater than the second threshold value to determine whether the current measurement image has too high brightness, and when the first difference is greater than the second threshold value, the current brightness is updated according to the size of the first difference. When the first difference is between the first threshold value and the second threshold value, and at the same time, the current iteration number is less than the maximum iteration number, the step of updating the contrast value is entered.

[0149] It can be understood that the first difference reflects the gray value difference between the measurement average gray value and the target average gray value. When the first difference exceeds the second threshold value, the brightness difference between the current measurement image and the target image is too large. When the first difference is between the first threshold value and the second threshold value, the contrast value is adjusted until the first difference is less than the first threshold value, and it is considered that the adjustment is successful.

[0150] When the first difference is between the first threshold value and the second threshold value, the way of updating the contrast value is selected according to the current iteration number, and the redundant search is eliminated by the local optimum judgment to avoid falling into a local optimum and improve the operation efficiency.

[0151] When the current iteration number is less than the iteration number threshold, the current contrast is updated based on the first difference value, and a plurality of groups of data of the contrast and the measurement average gray value are obtained; when the current iteration number is greater than or equal to the iteration number threshold, the contrast is updated by using an updated prediction relationship.

[0152] Since the prediction relationship is a nonlinear equation, after multiple iterations, the data in the local stable search section is searched according to the prediction relationship, which causes redundant search, therefore, at this time, a local optimal judgment is used, and the current contrast is updated based on the first difference value to help jump out of the local optimal, thereby accelerating the convergence and improving the operation efficiency.

[0153] When the final measurement average gray value and the target average gray value are within the first difference value range, the entire adjustment cycle is exited, and the automatic brightness contrast adjustment is successful.

[0154] When the current iteration number is greater than the maximum iteration number, the automatic brightness contrast adjustment fails.

[0155] The above step principle has been explained in the steps in the above general inventive concept, and the embodiment one will not be repeated.

[0156] Please refer to Figure 9 , Figure 9 A module schematic diagram of the brightness contrast adjustment device 100 provided by the embodiment of the present application;

[0157] The embodiment of the present application further provides a brightness contrast adjustment device 100 of a measurement equipment, which comprises:

[0158] The first determination module 10 is used for acquiring a target image and determining a target average gray value of the target image.

[0159] The second determination module 20 is used for acquiring a current measurement image and determining a measurement average gray value of the current measurement image.

[0160] The first judgment module 30 is used for judging whether a first difference value between the measurement average gray value of the current measurement image and the target average gray value satisfies a preset condition.

[0161] The first calculation module 40 is used for updating the current contrast based on the current iteration number and reacquiring the measurement image based on the updated contrast when the first difference value does not satisfy the preset condition.

[0162] The second judgment module 50 is used for judging whether the reacquired measurement image falls into a local optimal; and

[0163] The second calculation module 60 is configured to update the current iteration number and return to the step of acquiring the current measurement image and determining the measurement average gray value of the current measurement image until the first difference satisfies the preset condition to obtain the target contrast ratio when the reacquired measurement image does not fall into the local optimum.

[0164] The embodiment of the present application further provides a measurement device (not shown in the figure), which comprises an emission module configured to emit an electron beam to a wafer; an acquisition module configured to collect and process an electronic signal on the wafer to generate an image; and a host computer electrically connected with the emission module and the acquisition module, wherein the host computer comprises a processor and a memory storing computer program instructions; and the processor implements the brightness contrast adjustment method of the measurement device as described above when executing the computer program instructions.

[0165] Further, those skilled in the art should understand that if all or part of the sub-modules involved in each product of the brightness contrast adjustment device provided by the embodiment of the present application are combined, replaced, transformed, etc. by means of fusion, simple change, mutual transformation, etc., such as the movement of the positions of each component, or the integral setting of the products formed by the components, or the detachable design, as long as the combined components can form a device / system with a specific function, the device / system can replace the corresponding components of the present application and still fall within the protection scope of the present application.

[0166] It should be understood that the specific features, operations and details described above with respect to the method of the present application can also be applied to the device and system of the present application similarly, or vice versa. In addition, each step of the method of the present application described above can be performed by the corresponding components or units of the device or system of the present application.

[0167] The present application provides a computer readable storage medium, and the computer readable storage medium stores computer program instructions, and the computer program instructions are executed by a processor to implement the brightness contrast adjustment method described above.

[0168] Those skilled in the art can understand that the method steps of the present application can be instructed by a computer program to relevant hardware such as a measuring device or a processor, and the computer program for implementing the above brightness contrast adjustment method can be stored in a non-transitory computer readable storage medium, and the computer program is executed to cause the steps of the present application to be executed. According to the circumstances, any reference to memory, storage or other medium herein can include non-volatile or volatile memory. Examples of non-volatile memory include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk, etc. Examples of volatile memory include random access memory (RAM), external cache memory, etc.

[0169] The technical features described above can be combined arbitrarily. Although all possible combinations of these technical features are not described, any combination of these technical features should be considered to be covered by the present specification, as long as there is no contradiction in such a combination.

[0170] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. An adjusting method of a metrology apparatus for adjusting luminance and contrast, characterized by, The method comprises the following steps: acquiring a target image and determining a target average gray value of the target image; acquiring a current measurement image and determining a measurement average gray value of the current measurement image; determining whether a first difference between the measurement average gray value of the current measurement image and the target average gray value meets a preset condition, including: when the first difference is between a first threshold value and a preset second threshold value, determining that the first difference does not meet the preset condition; when the first difference is greater than the second threshold value, updating the current brightness according to the first difference and reacquiring the measurement image based on the updated brightness until the first difference is between the first threshold value and the second threshold value; when the first difference does not meet the preset condition, updating the current contrast based on a current iteration number and reacquiring the measurement image based on the updated contrast, the current iteration number serving as a counting loop condition; determining whether the reacquired measurement image falls into a local optimum; when the reacquired measurement image does not fall into the local optimum, updating the current iteration number and returning to the step of acquiring the current measurement image and determining the measurement average gray value of the current measurement image until the first difference meets the preset condition; the step of updating the current contrast based on the current iteration number and reacquiring the measurement image based on the updated contrast comprises: when the current iteration number is greater than or equal to an iteration number threshold value, updating the current contrast based on a relationship between the measurement average gray value and the contrast and reacquiring the measurement image based on the updated contrast; when the current iteration number is less than the iteration number threshold value, updating the current contrast based on the size of the first difference and reacquiring the measurement image based on the updated contrast.

2. The conditioning method of a metrology apparatus according to claim 1, wherein, the step of updating the current contrast based on the size of the first difference and reacquiring the measurement image based on the updated contrast when the current iteration number is less than the iteration number threshold value comprises: segmenting the first difference into intervals according to the range of the first difference; determining a mapped contrast variation according to the interval segmentation; updating the current contrast according to the contrast variation.

3. The conditioning method of the metrology apparatus according to claim 1, wherein, the step of updating the current contrast based on the relationship between the measurement average gray value and the contrast and reacquiring the measurement image based on the updated contrast comprises: updating a prediction relationship between the measurement average gray value and the contrast according to the current contrast and the measurement average gray value of the current measurement image; determining a predicted contrast value according to the updated prediction relationship; updating the current contrast based on the predicted contrast value.

4. A method of conditioning a metrology apparatus according to claim 3, wherein, the prediction relationship is: C=k*X+b wherein C is the current contrast, k and b are a first adjustment coefficient and a second adjustment coefficient, and X is the measurement average gray value.

5. The conditioning method of the metrology apparatus according to claim 1, wherein, the step of determining whether the first difference between the measurement average gray value of the current measurement image and the target average gray value meets the preset condition comprises: when the first difference is less than a preset first threshold value, determining that the first difference meets the preset condition.

6. The conditioning method of the metrology apparatus according to claim 1, wherein, the adjustment method further comprises: when the current iteration number is greater than or equal to a preset maximum iteration number, determining that the contrast and brightness adjustment fail.

7. The conditioning method of the metrology apparatus according to claim 1, wherein, The updating the current contrast based on the size of the first difference and reacquiring the measurement image based on the updated contrast includes: When the reacquired measurement image falls into a local optimum, the current contrast is updated based on the size of the first difference and the measurement image is reacquired based on the updated contrast until the reacquired measurement image stops updating when the reacquired measurement image does not fall into the local optimum.

8. A method of conditioning a metrology apparatus according to claim 1, wherein, The judging whether the reacquired measurement image falls into the local optimum includes: The contrast value of the reacquired measurement image is obtained, and the contrast value of the reacquired measurement image is compared with the contrast value of the acquired measurement image to obtain a contrast variation; The measurement average gray value of the reacquired measurement image is compared with the measurement average gray value of the acquired measurement image to obtain an average gray variation; When the contrast variation is less than a preset contrast variation threshold for a preset number of times in succession, and the average gray variation is less than a preset gray variation threshold for a preset number of times in succession, it is determined that the reacquired measurement image falls into the local optimum.

9. An adjusting device of a metrology apparatus for adjusting luminance and contrast, characterized in that, The method includes: The first determining module is configured to obtain a target image and determine a target average gray value of the target image; The second determining module is configured to obtain a current measurement image and determine a measurement average gray value of the current measurement image; The first judging module is configured to judge whether a first difference between the measurement average gray value of the current measurement image and the target average gray value satisfies a preset condition, including: when the first difference is between a first threshold and a preset second threshold, it is determined that the first difference does not satisfy the preset condition; when the first difference is greater than the second threshold, the current brightness is updated according to the first difference and the measurement image is reacquired based on the updated brightness until the first difference is between the first threshold and the second threshold; The first calculating module is configured to update the current contrast based on a current iteration number and reacquire the measurement image based on the updated contrast when the first difference does not satisfy the preset condition, the current iteration number serving as a counting loop condition; the updating the current contrast based on the current iteration number and reacquiring the measurement image based on the updated contrast includes: when the current iteration number is greater than or equal to an iteration number threshold, the current contrast is updated based on a relationship between the measurement average gray value and the contrast and the measurement image is reacquired based on the updated contrast; when the current iteration number is less than the iteration number threshold, the current contrast is updated based on the size of the first difference and the measurement image is reacquired based on the updated contrast; The second judging module is configured to judge whether the reacquired measurement image falls into the local optimum; and The second calculating module is configured to update the current iteration number and return to execute the step of obtaining the current measurement image and determining the measurement average gray value of the current measurement image when the reacquired measurement image does not fall into the local optimum until the first difference satisfies the preset condition.

10. A metrology apparatus for adjusting luminance and contrast, characterized in that, The method includes: The transmitting module is configured to transmit an electron beam to a wafer; The acquiring module is configured to collect and process an electronic signal on the wafer to generate an image; and The method includes: A host computer electrically connected with the transmitting module and the collecting module, the host computer comprising a processor and a memory storing computer program instructions; The processor executes the computer program instructions to implement the adjustment method of the metrology device according to any one of claims 1-8.

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