Optical system position calibration method, optical detection system and electronic equipment

Abstract

The invention relates to a dark field defect detection method, in particular to an optical system position calibration method, an optical detection system and electronic equipment. The method comprises the following steps: screening defect signals corresponding to a plurality of channels based on an intensity distribution relationship and a coordinate position relationship to obtain anchor point defects, extracting local features of each anchor point defect, matching anchor point defect pairs of which the similarity meets a threshold in the plurality of channels, performing position transformation mapping on a matching result to obtain a transformation matrix, and updating the transformation matrix to a real-time coordinate transformation module to obtain a target coordinate transformation module, thereby realizing position transformation of multiple channels. Real-time automatic calibration of a multi-PMT channel system can be achieved, the problem that production efficiency is reduced due to traditional shutdown calibration is avoided, the utilization rate and production efficiency of equipment are improved, online real-time calibration can be achieved, the calibration process and the normal production process are seamlessly connected, and the automation degree and the intelligent level of production are improved.

Description

TECHNICAL FIELD

[0001] The application relates to the field of dark field defect detection, and particularly relates to a position calibration method of an optical system, an optical detection system and electronic equipment. BACKGROUND

[0002] A multi-PMT channel system is widely applied in the fields of semiconductor detection and industrial flaw detection. However, in a long-term use process, the system inevitably has a position offset phenomenon. This is a known and serious engineering problem in high-end detection equipment. The offset does not refer to a large-scale movement of a physical position of a PMT, but refers to a slight misalignment of an optical acquisition path of the PMT, thereby causing a systematic error of a detection signal.

[0003] At present, the position offset needs to be calibrated, so as to ensure the accuracy of a signal strength acquired by the PMT system. A traditional position calibration method mainly calibrates by stopping and using a standard wafer. This method is not only complicated to operate, but also causes a long-time stop of equipment, thereby seriously reducing production efficiency and increasing production cost. Therefore, a method capable of realizing real-time automatic calibration in a normal production process, accurately screening feature defect points and reliably performing registration is urgently needed to solve the problems in the prior art. SUMMARY

[0004] In order to solve the above problems, the application provides a position calibration method of an optical system and an optical system. By means of steps such as anchor point defect screening, feature descriptor construction, cross-channel anchor point matching, weighted robust registration and dynamic compensation updating, the problems such as a reduction of production efficiency caused by a stop calibration of a traditional method, and an incomplete defect detection caused by a sensitivity difference between different channels are solved, and calibration accuracy and production efficiency are improved.

[0005] In order to achieve the above purpose, the technical scheme adopted by the embodiments of the application is as follows: In a first aspect, an optical system position calibration method is provided, which is applied to a multi-channel system, each channel being used to acquire defect data of each defect under different conditions, the defect data including optical signal intensity and defect position coordinates of the defect, the method comprising: determining a signal intensity vector corresponding to each defect in each channel, constructing a signal intensity vector set of multiple channels corresponding to each defect, and screening multiple defects based on the signal intensity vector set and distance relationship between defects to obtain anchor point defects; extracting local features of each anchor point defect; the local features including geometric features and intensity features, the geometric features being used to reflect the relative position relationship of the anchor point defects in space, and the intensity features being used to reflect the relative size of the signal intensity of the anchor point defects in each channel; matching anchor point defect pairs in multiple channels with a similarity meeting a threshold, and performing position transformation mapping on the matching result to obtain a transformation matrix, and updating the transformation matrix to a real-time coordinate conversion module to obtain a target coordinate conversion module.

[0006] In some specific implementations, screening multiple defects based on the signal intensity vector set comprises: screening multiple defects based on the defect position coordinates corresponding to each channel through a spatial constraint condition to obtain initial candidate anchor point defects; screening defects with stable signal performance in the initial candidate anchor point defects based on signal intensity distribution in the initial candidate anchor point defects to obtain intermediate candidate anchor point defects; and screening the intermediate candidate anchor point defects based on distance correlation of multiple intermediate candidate anchor point defects to obtain anchor point defects.

[0007] In some specific implementations, multiple defects are spatially clustered based on a density clustering method, distribution values of each cluster in each channel position coordinate are calculated, and the dispersion degree of the defect position in the cluster is calculated, and defects in a cluster with a dispersion degree less than a set threshold are retained as initial candidate anchor point defects.

[0008] In some specific implementations, the signal intensity distribution of the initial candidate anchor point defects is obtained by: calculating the dispersion degree of the initial candidate anchor point defects relative to each channel; and screening defects with stable signal performance in the initial candidate anchor point defects, which comprises: screening anchor point defects in the initial candidate anchor point defects with a dispersion degree less than a preset value threshold in each channel as intermediate candidate anchor point defects.

[0009] In some specific implementation manners, the screening of the intermediate candidate anchor defects based on the spatial correlation of the intermediate candidate anchor defects comprises: determining a distance matrix of each intermediate candidate anchor defect and other intermediate candidate anchor defects, determining a fluctuation state of a distance of each intermediate candidate anchor defect and other intermediate candidate anchor defects based on a distance fluctuation threshold and the distance matrix, and screening intermediate candidate anchor defects with a distance fluctuation less than the distance fluctuation threshold as the anchor defects.

[0010] In some specific implementation manners, the extraction of the geometric feature of each anchor defect comprises: calculating a distance vector of each anchor defect and adjacent anchor defects.

[0011] In some specific implementation manners, the extraction of the intensity feature of each anchor defect comprises: performing normalization processing on a signal intensity vector set of multiple channels to obtain a normalized multi-channel intensity vector, and screening a maximum value in signal intensity of all candidate anchor defects in each channel as the intensity feature.

[0012] In some specific implementation manners, the matching of anchor defect pairs with a similarity meeting a threshold in multiple channels and the position transformation mapping of a matching result to obtain a transformation matrix comprises: determining anchor defect pairs meeting a requirement in bidirectional matching, and obtaining the transformation matrix by using weighted least squares fitting on all the anchor defect pairs.

[0013] In a second aspect, an optical detection system is provided, comprising: a bearing table configured to place a to-be-detected object; an incident light source configured to form an incident light version on a surface of the to-be-detected object and form a scattered light beam based on scattering of the surface of the to-be-detected object; at least two optical signal receiving channels, each of the optical signal receiving channels being provided with a detector assembly configured to correspond to a scattered light beam with a different scattering angle and obtain an optical signal intensity and an optical position coordinate corresponding to the scattered light beam; and a processing device configured to receive the optical signal intensity and the optical position coordinate in each of the optical signal receiving channels, determine whether the optical signal is a defect optical signal based on an expression of the optical signal intensity, and perform the method of any one of the preceding aspects on the defect optical signal.

[0014] In a third aspect, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the optical system position calibration method of any one of the preceding aspects.

[0015] The embodiments of the present application have the following beneficial effects: The technical scheme provided in the embodiment of the application adopts an anchor point defect automatic screening mechanism, ensures the accuracy and reliability of the feature points on which calibration is based, and thus improves the calibration precision; and fuses geometric and intensity information and a weighted robust registration method, enhances the robustness of matching, reduces the influence of noise and outliers, and further improves the precision and stability of position calibration. Real-time automatic calibration of a multi-PMT channel system can be realized, the problem of reduced production efficiency caused by traditional shutdown calibration is avoided, the utilization rate and production efficiency of the equipment are improved, online real-time calibration is realized, the calibration process and the normal production process are seamlessly connected, manual intervention is not needed, labor cost is reduced, and the automation degree and intelligent level of production are improved.

[0016] Other features and advantages of the present disclosure will be set forth in the following description, or will be apparent from the description, or can be learned by practice of the present disclosure.

[0017] In order to make the above-mentioned purposes, features and advantages of the present disclosure more obvious and easy to understand, the following preferred embodiments are specifically described below, and the accompanying drawings are described in detail as follows. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0019] The methods, systems and / or programs in the drawings will be further described according to the exemplary embodiments. These exemplary embodiments will be described in detail with reference to the drawings. These exemplary embodiments are non-limiting exemplary embodiments, in which the example numbers represent similar mechanisms in each view of the drawings.

[0020] Figure 1 is a schematic structural diagram of an optical detection system provided by the embodiment of the present application.

[0021] Figure 2 is a schematic flow diagram of an optical system position calibration method provided by the embodiment of the present application.

[0022] Figure 3 is a schematic structural diagram of a processing device provided by the embodiment of the present application.

[0023] Figure 4 is a schematic structural diagram of a server provided by the embodiment of the present application. DETAILED DESCRIPTION

[0024] For better understanding of the above technical solutions, the technical solutions of the present application are described in detail below through the drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solutions of the present application, and not limitations of the technical solutions of the present application. In the case of no conflict, the technical features in the embodiments of the present application and the embodiments can be combined with each other.

[0025] In the following detailed description, many specific details are set forth in order to provide a thorough understanding of the relevant teachings. However, it will be apparent to one of ordinary skill in the art that the present application can be practiced without these details. In other instances, well-known methods, procedures, systems, components, and / or circuits have been described at a relatively high level, without detail, in order to avoid unnecessarily obscuring aspects of the present application.

[0026] The flowcharts in the present application illustrate the execution processes performed by the system according to the embodiments of the present application. It should be clearly understood that the execution processes of the flowcharts can not be executed in sequence. On the contrary, these execution processes can be executed in reverse order or simultaneously. In addition, at least one other execution process can be added to the flowchart. One or more execution processes can be deleted from the flowchart.

[0027] Before the embodiments of the present application are further described in detail, the terms and phrases involved in the embodiments of the present application are explained, which are applicable to the following explanations.

[0028] (1) In response to, used to indicate the condition or state on which the executed operation depends, when the dependent condition or state is met, one or more operations performed can be real-time or have a set delay; in the absence of special instructions, there is no restriction on the execution order of multiple operations performed.

[0029] (2) Based on, used to indicate the condition or state on which the executed operation depends, when the dependent condition or state is met, one or more operations performed can be real-time or have a set delay; in the absence of special instructions, there is no restriction on the execution order of multiple operations performed.

[0030] Reference Figure 1The embodiment of the present application provides a kind of optical detection system 10, including support platform 11, incident light source 12 and optical signal receiving channel.Therein, for the support platform used to place the object to be detected, incident light source is used to transmit incident light to the surface of the object to be detected and form incident light spot on the surface of the object to be detected, the surface of the object to be detected generates scattering based on incident light beam and forms scattered light.Further, scattered light is collected by optical collector, and scattered light beam with different scattering angle range is formed.Therein, for the optical receiver in the embodiment ellipsoidal mirror 13, for the scattering angle range in the embodiment includes at least two, and is received by corresponding optical signal receiving channel.So, for the optical signal receiving channel in the embodiment, at least two are correspondingly provided, and each optical signal receiving channel is provided with detector assembly 14, and each detector assembly is used to obtain the optical signal intensity and optical position coordinates corresponding to scattered light beam.

[0031] Wherein, for the detector assembly is PMT (photomultiplier tube), for the optical collector includes ellipsoidal mirror and at least one mirror, mirror is set in a scattering angle range for the scattering light in this scattering angle range is transmitted to the detector assembly in an optical signal receiving channel.

[0032] In the embodiment, the object to be detected is a wafer to be detected.Therein, "wafer" in the embodiment generally refers to substrate formed by semiconductor or non-semiconductor material.Examples include (but not limited to) single crystal silicon, gallium arsenide, gallium nitride and indium phosphide.Such substrate can be found and / or processed in semiconductor manufacturing facility.In some cases, wafer can only include substrate (i.e. bare chip).Alternatively, wafer can include one or more layers of different materials formed on substrate.One or more layers formed on wafer can be "patterned" or "unpatterned".For example, wafer can include a plurality of dies with repeatable pattern features.

[0033] For the optical detection system in the embodiment, especially multi-PMT channel system, position deviation phenomenon will inevitably occur during long-term use.It is a known and serious engineering problem in precision detection equipment, which is not a large-scale movement of PMT physical position, but a small misalignment of its optical acquisition path, which will cause systematic error of the optical signal obtained.The root cause is a multi-physical field coupling, time-evolving systematic problem.The causes of position deviation mainly include the following four points: Thermal deformation is the most common and the most important cause. Because the light source and electronic components of the system itself will continue to produce heat. In the long-term cycle start-stop or power changes, heat is not evenly accumulated and dissipated in the system. Even with temperature control facilities, the diurnal or seasonal environmental temperature fluctuations will still affect the large detection system. Different materials (such as metal brackets, optical lenses, adhesives) have different thermal expansion coefficients. This mismatched expansion and contraction will directly cause the brackets that fix the optical elements (such as mirrors, lenses, fiber joints) to deform by microns or even nanometers. This deformation will directly change the optical path, causing the actual receiving area of the PMT to shift.

[0034] Mechanical stress relaxation and creep. When the device is assembled, the screws and clamps are tightened, exerting a pre-tightening force on the structural members and optical elements. Over a long period of time (months to years), the internal microstructure of the metal or composite material will rearrange, causing the pre-tightening force to slowly decrease, i.e. "stress relaxation". Small changes in pre-tightening force will release the previously "locked" deformation, causing the position of the optical element or its bracket to slowly and irreversibly drift.

[0035] Cumulative effect of environmental vibration and impact. Even if the device is installed on a vibration isolation platform, micro-vibrations from the ground, the building itself, and the internal system still exist. These continuous, low-intensity vibrations will gradually cause the fixing screws to loosen and the contact surfaces to wear slightly, resulting in small displacements. Although the single impact is negligible, the long-term cumulative effect is significant.

[0036] Aging of the optical elements themselves. Optical glass has internal stress during manufacturing and ring pressing. Over time, the stress will slowly release, causing the lens surface to change slightly, affecting the optical path. Anti-reflection film, optical film, and other optical films may change slowly due to long-term light (especially ultraviolet) and environmental effects, affecting their transmittance and reflectance, indirectly changing the system sensitivity and equivalent optical path.

[0037] Currently, the position shift caused by the above reasons needs to be calibrated to ensure the accuracy of the signal strength collected by the PMT system. Therefore, the optical detection system in the embodiment also has a processing device 15 for correcting the position shift, wherein the processing device is used to receive the optical signal strength and the optical position coordinates in each optical signal receiving channel, and determine whether it is a defective optical signal based on the expression of the optical signal strength; and perform an optical system position calibration method on the defective optical signal.

[0038] The specific processing process of the optical system position calibration method can be referred to Figure 2 , including the following steps: Step S21. Determine the signal intensity vector corresponding to each defect in each channel, construct the signal intensity vector set of each defect corresponding to multiple channels, and screen multiple defects based on the signal intensity vector set and the distance relationship between defects to obtain anchor point defects.

[0039] In the embodiment, at least two channels are included, and each channel is used to acquire optical signal intensity of each incident light spot in different scattering angle ranges and position coordinates corresponding to each incident light spot. Further, according to the defect detection method, the judgment of defects can be realized through optical signal intensity, and then the defect data is screened. Wherein, the defect data includes optical signal intensity and defect position coordinates of the defect. Specifically, the defect detection can be realized based on the method in the prior art, which will not be described in detail in the embodiment.

[0040] For the signal intensity corresponding to each acquired defect, the signal intensity vector under each channel is calculated, and a candidate defect pool is constructed. Then, the defects in the candidate defect pool are screened to obtain anchor point defects. Wherein, the anchor point defect refers to a defect having a matching relationship in different channels.

[0041] Specifically, the matching relationship includes three kinds of relationships, which are spatial relationship, signal intensity distribution relationship and distance relationship. Wherein, the spatial relationship refers to determining the spatial positions between multiple defects based on the defect position coordinates through the defect data collected by each channel, and screening multiple defect data based on the spatial positions to obtain initial candidate anchor point defects. For the signal intensity distribution relationship, the correlation of the signal intensity of multiple channels in the initial candidate anchor point defects is screened, and the initial candidate anchor point defects satisfying the signal intensity distribution are screened again to obtain intermediate candidate anchor point defects. The distance relationship refers to calculating the distance matrix between the intermediate candidate anchor point defects, and screening the intermediate candidate anchor point defects satisfying the requirements to obtain anchor point defects.

[0042] Wherein, the screening of anchor point defects is used to select the defects that can best represent the position relationship in the current optical detection system, so as to reduce the problem of high calibration cost under the condition of massive data.

[0043] Specifically, for the screening based on the spatial relationship, the spatial clustering of the defect position coordinates corresponding to the plurality of defects is performed based on a density clustering algorithm to obtain a plurality of clustering clusters. Then, the mean standard deviation of the defects in the clustering cluster at each channel position coordinate is calculated, and it is further judged whether the dispersion degree of the defect positions in the cluster is less than a set threshold value. Only the defects in the clustering cluster with a small dispersion degree are retained as the initial candidate anchor point defects to form an initial candidate anchor point defect set. In this embodiment, the defects with relatively concentrated and stable positions in space can be screened out by this method to avoid misjudgment caused by dispersed positions. The density clustering algorithm can be implemented by using the algorithm in the prior art, including but not limited to the DBSCAN algorithm.

[0044] Specifically, for the screening based on the signal intensity distribution relationship, the coefficient of variation of the signal intensity corresponding to each defect in the plurality of channels in the initial candidate anchor point defect set is calculated, and the relationship between the coefficient of variation and the coefficient of variation threshold value is determined. In this embodiment, the coefficient of variation is used to represent the dispersion degree of the initial candidate anchor point defect relative to each channel, and the coefficient of variation is based on the ratio of the standard deviation to the mean of the optical signal intensity corresponding to the defect. Further, when the coefficient of variation of the signal intensity of the defect in each channel is less than the coefficient of variation threshold value, it indicates that the signal intensity distribution of the defect in each channel is relatively consistent, which satisfies the signal intensity distribution consistency condition. Based on this condition, defects with stable signal performance in different channels can be effectively screened out, and defects with large signal fluctuations caused by channel sensitivity differences can be excluded.

[0045] In this embodiment, the coefficient of variation is calculated by the ratio of the standard deviation to the mean of the optical signal intensity corresponding to the defect.

[0046] Specifically, for the screening based on the distance relationship, the distance matrix between the plurality of intermediate candidate anchor point defects is calculated. A distance fluctuation threshold value is set, and the fluctuation of the distance between the defect and other intermediate candidate anchor point defects in a certain number of adjacent defect detection results is counted. If the distance fluctuation is less than the set threshold value, it is considered that the relative position relationship between the defect and other defects is stable, which satisfies the defect distance stability condition. For this condition, it further ensures that the screened defects have stability in the spatial structure.

[0047] In this embodiment, by using the spatial clustering constraint, the signal intensity distribution consistency and the defect distance stability condition, the stable and reliable anchor point defects are accurately screened out from multiple dimensions such as spatial position, signal performance and structural relationship in the complex scene with real-time calibration and different scanning results each time.

[0048] Step S22. Extracting the local features of each anchor point defect.

[0049] In the embodiment, the local features include geometric features and intensity features. The geometric intensity is determined by calculating the distance vector of the anchor point defect and the adjacent anchor point defect where di represents the distance of the i-th nearest adjacent anchor point defect, and the nearest k points are selected for calculation. The geometric features reflect the relative position relationship of the anchor point defects in space.

[0050] The determination of the intensity features is normalized by a multi-channel intensity vector, and the maximum value of the signal intensity of all candidate anchor point defects in each channel is selected as the intensity feature, which is represented by the following formula: where max(i,j) represents the maximum value of all anchor point defect signal intensities in the j-th channel, and the intensity features reflect the relative size of the signal intensity of the anchor point defects in each channel.

[0051] The embodiment combines the geometric features and intensity features to obtain F = [geometric features, intensity features], which combines the geometric and intensity information of the anchor point defects, and provides rich feature basis for subsequent cross-channel anchor point matching. The constructed feature descriptor combines the geometric features and intensity features of the anchor point defects, which can more comprehensively describe the characteristics of the anchor point defects compared with the traditional single feature method, enhances the robustness of cross-channel anchor point matching, and improves the accuracy and stability of matching.

[0052] Step S23. Matching the anchor point defects pairs in multiple channels that meet the threshold similarity, and mapping the position transformation of the matching results to obtain a transformation matrix, and updating the transformation matrix to the real-time coordinate conversion module to obtain a target coordinate conversion module.

[0053] In the embodiment, the matching process finds the corresponding anchor point defects in other channels based on a certain channel.

[0054] The matching is implemented by a bidirectional matching strategy, including forward matching and reverse matching. For the forward matching process, for each anchor point defect of a channel, for example, PMT1, find the candidate point with the closest features in another channel PMTx. Specifically, the similarity between the features corresponding to each anchor point defect in the two channels is calculated, and the point with the highest similarity is selected as the candidate point. The similarity calculation can be implemented by any similarity calculation method in the prior art, such as Euclidean distance, cosine similarity.

[0055] After the corresponding candidate points are determined after the forward matching, the candidate points determined in the PMTx are reversely matched to the PMT1, and the corresponding points in the PMT1 are determined by calculating the feature similarity. Only when the bidirectional matching results are consistent and the geometric feature similarity is greater than a predetermined threshold, the matching is considered successful. The matching conditions in this embodiment ensure the accuracy of the matching, and avoid false matching caused by single matching error.

[0056] An anchor point pair set is formed after the matching is successful wherein represents the i-th anchor point in the PMT1, represents the corresponding anchor point in the PMTx.

[0057] A weighted least squares fitting is used to calculate the transformation matrix corresponding to the anchor point defects in the anchor point pair set, and the objective function of the weighted least squares fitting is wherein the weight Further, the geometric feature difference is realized by determining the geometric feature difference value corresponding to the two anchor point defects, and the intensity consistency factor is realized by determining the intensity feature difference value corresponding to the two anchor point defects. The geometric feature difference reflects the similarity of the geometric features between the anchor point pairs, and the intensity consistency factor is used to measure the consistency degree of the anchor point pairs in the intensity of each channel signal.

[0058] The above processing can obtain a transformation matrix, wherein the transformation matrix is used to guide the conversion between coordinates to realize calibration, so that the subsequent detected defect data can be accurately converted according to the calibration result.

[0059] In this embodiment, by using a weighted registration method based on distance consistency, different anchor point pairs are weighted and processed by introducing weights, which reduces the influence of unstable feature points on the calibration accuracy, effectively resists the interference of noise and outliers, and improves the accuracy and reliability of the position calibration.

[0060] In summary, the present embodiment provides an optical system position calibration method, which uses an anchor point defect automatic screening mechanism to ensure the accuracy and reliability of the feature points on which the calibration is based, thereby improving the calibration accuracy. The geometric and intensity information are fused, and a weighted robust registration method is used to enhance the robustness of the matching, reduce the influence of noise and outliers, and further improve the accuracy and stability of the position calibration. Real-time automatic calibration of a multi-PMT channel system can be realized, avoiding the problem of reduced production efficiency caused by traditional shutdown calibration, improving the utilization rate and production efficiency of the equipment, and realizing online real-time calibration, so that the calibration process and the normal production process are seamlessly connected, without manual intervention, reducing labor costs, and improving the automation and intelligence level of production.

[0061] To better implement the above method, for the processing device can be configured in the electronic device in any one detection system, the electronic device can be as terminal, server and so on. Among them, the terminal can be mobile phone, tablet computer, smart Bluetooth device, notebook computer, personal computer and so on; the server can be single server, or server cluster composed of multiple servers.

[0062] For example, in the embodiment, the measurement device is specifically integrated in the electronic device, and the method of the embodiment of the application is described in detail.

[0063] For example, as shown in the figure, Figure 3 The processing device 30 includes: The anchor point defect screening unit 31 is configured to determine a signal intensity vector corresponding to each defect in each channel, construct a signal intensity vector set of multiple channels corresponding to each defect, and screen multiple defects based on the signal intensity vector set to obtain candidate anchor point defects. The feature extraction unit 32 is configured to extract local features of each anchor point defect. The calibration unit 33 is configured to match anchor point defect pairs with a similarity that meets a threshold in multiple channels, perform position transformation mapping on the matching result to obtain a transformation matrix, and update the transformation matrix to a real-time coordinate conversion module to obtain a target coordinate conversion module.

[0064] The electronic device can be a terminal, a server, and the like. The terminal can be a mobile phone, a tablet computer, a smart Bluetooth device, a notebook computer, a personal computer, and the like. The server can be a single server, or a server cluster composed of multiple servers, and the like.

[0065] In some embodiments, the measurement device can also be integrated in multiple electronic devices, for example, the measurement device can be integrated in multiple servers, and the multiple servers can implement the light source radiant illuminance measurement method and / or the radiant efficiency measurement method of the application.

[0066] In the embodiment, the electronic device of the embodiment is taken as an example to be described in detail, for example, as shown in the figure, Figure 4 The figure shows a structure schematic diagram of the server related to the embodiment of the application. Specifically, The server can include a processor 401 with one or more processing cores, a memory 402 with one or more computer readable storage media, a power supply 403, an input module 404, a communication module 405, and the like. Those skilled in the art can understand that, Figure 4The server structure shown in the figure is not intended to limit the server, and can include more or fewer components than shown, or combine some components, or arrange different components. Among them: The processor 401 is the control center of the server, which connects various parts of the server through various interfaces and lines, and performs various functions of the server and processes data by running or executing software programs and / or modules stored in the memory 402 and calling data stored in the memory 402. In some embodiments, the processor 401 can include one or more processing cores; in some embodiments, the processor 401 can integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application program, etc., and the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor can also not be integrated into the processor 401.

[0067] The memory 402 can be used to store software programs and modules, and the processor 401 executes various functions and data processing by running the software programs and modules stored in the memory 402. The memory 402 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application program required by a function (such as an image playing function, etc.), etc.; the data storage area can store data created according to the use of the server, etc. In addition, the memory 402 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state memory device. Accordingly, the memory 802 can also include a memory controller to provide access for the processor 401 to the memory 402.

[0068] The server also includes a power supply 403 for powering various components, and in some embodiments, the power supply 403 can be logically connected to the processor 401 through a power management system, so as to realize functions such as management of charging, discharging, and power consumption management through the power management system. The power supply 403 can also include one or more direct current or alternating current power supplies, recharging systems, power failure detection circuits, power converters or inverters, power state indicators, and any other components.

[0069] The server can also include an input module 404, which can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0070] The server can also include a communication module 405, which in some embodiments can include a wireless module, through which the server can perform short-range wireless transmission, thereby providing the user with wireless broadband Internet access. For example, the communication module 405 can be used to help the user send and receive emails, browse web pages, and access streaming media, etc.

[0071] Although not shown, the server can also include a display unit, etc., which will not be described here. In particular, in the present embodiment, the processor 401 in the server will load the executable file corresponding to the process of one or more application programs into the memory 402 according to the following instructions, and run the application program stored in the memory 402 by the processor 401, thereby implementing the steps in the method of the embodiments of the present application.

[0072] The specific implementation of the above operations can refer to the previous embodiments, which will not be described here.

[0073] As can be seen from the above, the parts similar to the original object in each simulation object can be reserved in a targeted manner, and the target parts corresponding to each part are combined, so that the final target simulation object is more similar to the original object as a whole compared to the multiple simulation objects, and it is ensured that the generated target simulation object can accurately retain the core features and style of the original object. Thus, the quality of content stylization migration is improved.

[0074] Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructions, or by instructions controlling related hardware, which can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0075] To this end, the embodiments of the present application provide a computer-readable storage medium, which stores a plurality of instructions capable of being loaded by a processor to execute the steps in any of the light source radiation illuminance measurement methods provided by the embodiments of the present application. For example, the instructions can perform the following steps: Determine the signal intensity vector corresponding to each defect in each channel, construct the signal intensity vector set of each defect corresponding to multiple channels, and filter multiple defects based on the signal intensity vector set and the defect distance relationship to obtain anchor point defects; Extract local features of each of the anchor point defects; Match anchor point defect pairs in multiple channels with a similarity that meets a threshold, perform position transformation mapping on the matching results to obtain a transformation matrix, and update the transformation matrix to a real-time coordinate conversion module to obtain a target coordinate conversion module.

[0076] The storage medium can include a read-only memory (ROM), a random access memory (RAM), a magnetic disk, an optical disk, or the like.

[0077] According to an aspect of the present application, a computer program product or computer program is provided, which includes computer programs / instructions stored in a computer readable storage medium. A processor of an electronic device reads the computer programs / instructions from the computer readable storage medium, and the processor executes the computer programs / instructions, so that the electronic device performs the method provided in any of the various optional implementations of the light source radiant intensity measurement aspect provided in the above embodiments.

[0078] Due to the instructions stored in the storage medium, the steps in any of the optical system position calibration methods provided in the embodiments of the present application can be executed, and thus the beneficial effects that can be achieved in the methods provided in the embodiments of the present application can be achieved. Details are described in the above embodiments, and thus will not be described here.

[0079] In the present application, “at least one” means one or more, and “multiple” means two or more. “At least one of the following” or the like means any combination of the items, including any combination of single item or multiple items. For example, at least one of a, b, or c can represent a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0080] It should be understood that, in various embodiments of the present application, the size of the sequence number of each process does not mean the order of execution, and the execution order of each process should be determined according to its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0081] The above describes in detail the optical system position calibration method, optical detection, electronic device, and program product provided in the embodiments of the present application. The principles and implementation manners of the present application are described by applying specific examples in this paper, and the above embodiment descriptions are only used to help understand the method of the present application and its core idea; at the same time, for those skilled in the art, according to the idea of the present application, the specific implementation manner and application range will be changed, and the above description should not be understood as a limitation on the present application.

Claims

1. A method for calibrating the position of an optical system, characterized in that, Applied to a multi-channel system, each channel is used to acquire defect data for each defect under different conditions. The defect data includes the optical signal intensity and location coordinates of the defect. The method includes: Determine the signal intensity vector corresponding to each defect in each channel, construct a set of signal intensity vectors for multiple channels corresponding to each defect, and filter multiple defects based on the set of signal intensity vectors and the distance relationship between defects to obtain anchor point defects; Local features are extracted for each anchor point defect; the local features include geometric features and intensity features, the geometric features are used to reflect the relative positional relationship of the anchor point defect in space, and the intensity features are used to reflect the relative signal strength of the anchor point defect in each channel; Anchor point defect pairs with similarity meeting a threshold are matched in multiple channels, and the matching results are mapped to obtain a transformation matrix. The transformation matrix is ​​then updated to the real-time coordinate transformation module to obtain the target coordinate transformation module.

2. The optical system position calibration method according to claim 1, characterized in that, The process of filtering multiple defects based on the signal strength vector set includes: filtering multiple defects based on the defect location coordinates corresponding to each channel using spatial constraints to obtain initial candidate anchor point defects; filtering out defects with stable signal performance among the initial candidate anchor point defects based on the signal strength distribution among the initial candidate anchor point defects to obtain intermediate candidate anchor point defects; and filtering the intermediate candidate anchor point defects based on the distance correlation among multiple intermediate candidate anchor point defects to obtain anchor point defects.

3. The optical system position calibration method according to claim 2, characterized in that, Spatial clustering is performed on multiple defects based on density clustering method. The distribution value of the position coordinates of each channel within each cluster is calculated, and the dispersion of the defect position within the cluster is calculated. Defects in clusters with dispersion less than a set threshold are retained as initial candidate anchor point defects.

4. The optical system position calibration method according to claim 2, characterized in that, Obtaining the signal intensity distribution in the initial candidate anchor point defects includes: calculating the dispersion of the initial candidate anchor point defects relative to each channel; and selecting defects with stable signal performance among the initial candidate anchor point defects, including: selecting anchor point defects whose dispersion in each channel is less than a preset threshold as intermediate candidate anchor point defects.

5. The optical system position calibration method according to claim 2, characterized in that, Based on the spatial correlation of multiple intermediate candidate anchor point defects, the intermediate candidate anchor point defects are screened to obtain anchor point defects, including: determining the distance matrix of each intermediate candidate anchor point defect and other intermediate candidate anchor point defects, and determining the fluctuation state of the distance between each intermediate candidate anchor point defect and other intermediate candidate anchor point defects based on the distance fluctuation threshold and the distance matrix, and screening intermediate candidate anchor point defects with distance fluctuation less than the distance fluctuation threshold as anchor point defects.

6. The optical system position calibration method according to claim 1, characterized in that, Extracting the geometric features of each anchor point defect includes: calculating the distance vector between each anchor point defect and its adjacent anchor point defects.

7. The optical system position calibration method according to claim 1, characterized in that, Extracting the intensity features of each anchor point defect includes: normalizing the signal intensity vector set of multiple channels to obtain a normalized multi-channel intensity vector, and selecting the maximum value among all anchor point defect signal intensities in each channel as the intensity feature.

8. The optical system position calibration method according to claim 1, characterized in that, Matching anchor point defect pairs with similarity meeting a threshold in multiple channels and performing position transformation mapping on the matching results to obtain a transformation matrix includes: determining anchor point defect pairs that meet the bidirectional matching requirements, and using weighted least squares fitting on all the anchor point defect pairs to obtain the transformation matrix.

9. An optical detection system, characterized in that, include: A support platform, used to place the object to be tested; An incident light source is used to form an incident light spot on the surface of the object to be tested, and to form a scattered light beam based on the scattering from the surface of the object to be tested; At least two optical signal receiving channels, each of which is equipped with a detector assembly for scattering beams corresponding to different scattering angles, and obtains the optical signal intensity and optical position coordinates corresponding to the scattered beams; A processing device is configured to receive the optical signal intensity and the optical position coordinates in each of the optical signal receiving channels, and determine whether it is a defective optical signal based on the expression of the optical signal intensity; and perform the method according to any one of claims 1-8 on the defective optical signal.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the optical system position calibration method according to any one of claims 1 to 8.

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