Calibration relation determination method, and adjustment method and device among multiple devices

Abstract

The invention relates to the technical field of semiconductor detection, provides a semiconductor machine vision system adjusting method, and particularly relates to a calibration relation determining method and an adjusting method and device among multiple devices. The calibration relation of each light source in each device and machine vision system can be determined, and the mapping relation between the real-time light source and the light source under the standard condition can be constructed according to the relation, so that the state of the current light source can be objectively reflected; moreover, the method can be used for a plurality of machine vision systems with the same configuration parameters, the adjustment parameters among a plurality of devices are determined by obtaining key parameter expression differences between any device and other devices, and the adjustment amount of the corresponding device is determined based on the real-time adjustment amount of any device and the adjustment parameters of the corresponding device. And unified key parameter adjustment of multiple devices is realized based on the adjustment quantity. According to the method provided by the embodiment of the invention, the consistency of image effects among multiple devices can be ensured, the compatibility of the devices is improved, and the detection difficulty of a software algorithm is reduced.

Description

Technical Field

[0001] The present application relates to the field of semiconductor detection technology, and is a method for adjusting a semiconductor machine vision system, specifically a method for determining a calibration relationship, and a method and apparatus for adjusting multiple devices. Background Art

[0002] During the manufacturing process for mass-produced equipment, lenses and cameras rarely undergo changes once they're locked in. However, these products inherently vary. For example, variations in aperture size, lens coating, and camera chip sensitivity can lead to image variations, and these subtle differences can't be adjusted during use. Differences in the design of the light source's LEDs and circuits, along with the light's attenuation over time, can also affect image quality and are difficult to control. Even if the relative positions of the light source, lens, and camera are mechanically guaranteed, subtle differences between products can still lead to image variations between devices.

[0003] In many cases, these image differences between devices caused by hardware and installation are not addressed, or software algorithms are forced to be compatible. This often results in the inability to use the same set of parameters across all devices for production. After replacing new hardware, the original parameters become unusable. The same piece of production material can produce multiple inspection results on multiple devices. These significant differences between devices lead to numerous missed and false detections, impacting production yield. Summary of the Invention

[0004] To address the issues of light attenuation in a single device and consistency of image effects and brightness between devices, this application provides a calibration relationship determination method, a multi-device adjustment method, and an apparatus. These methods can correct light source brightness to compensate for light source attenuation, while also ensuring uniform calibration of image effects and brightness across multiple devices, minimizing differences in image effects and brightness between devices. Even after replacing visual hardware, the original detection program remains usable. To achieve the above objectives, the technical solutions employed in the embodiments of the present invention are as follows:

[0005] In a first aspect, a calibration relationship determination method is provided, the method comprising: sequentially acquiring images of a standard grayscale card based on a height change of an image acquisition device, obtaining a height position corresponding to an image with the highest clarity as a standard height position; adjusting an integration time of the image acquisition device based on the standard height position and standard light source brightness conditions to acquire multiple images of the standard grayscale card and corresponding multiple grayscale values, and determining an integration time corresponding to a target grayscale value as a standard integration time; sequentially adjusting the brightness of the light source based on the standard integration time and obtaining corresponding real-time grayscale values, and establishing a calibration relationship based on the brightness and the real-time grayscale values.

[0006] In some specific implementations, the height of the image acquisition device is relative to the height of the standard grayscale card.

[0007] In some specific implementations, the standard light source brightness is 220, and the target grayscale value is 255.

[0008] In some specific implementations, sequentially adjusting the brightness of the light source includes: sequentially adjusting the brightness of the light source based on an adjustment step size.

[0009] In some specific implementations, the brightness change of the adjustment step is 1.

[0010] In some specific implementations, the real-time grayscale value is an average of multiple grayscale values.

[0011] In a second aspect, a calibration relationship determination device is provided, the device comprising: a standard height position determination module, for sequentially capturing images of a standard grayscale card based on the height change of an image acquisition device, and obtaining a height position corresponding to an image with the highest clarity as the standard height position; a standard integration time determination module, for adjusting the integration time of the image acquisition device based on the standard height position and standard light source brightness conditions to obtain multiple images of the standard grayscale card, and determining the integration time corresponding to a grayscale value of a target grayscale value as the standard integration time; a calibration relationship construction module, for sequentially adjusting the brightness of the light source based on the standard integration time and obtaining a corresponding real-time grayscale value, and constructing a calibration relationship based on the brightness and the real-time grayscale value.

[0012] In a third aspect, a method for adjusting multiple devices is provided, the method comprising: retrieving the calibration relationship of multiple devices determined based on any one of the above methods; determining the adjustment coefficients between the multiple devices based on the multiple calibration relationships; determining the corresponding adjustment amount based on the real-time adjustment variable of any one of the devices and the corresponding adjustment coefficient, and adjusting the device based on the adjustment amount.

[0013] In some specific implementations, the adjustment coefficient is the brightness difference between devices, and the real-time adjustment variable is the light source brightness adjustment value; determining the corresponding adjustment amount based on the real-time adjustment variable of any of the devices and the corresponding adjustment coefficient includes: determining the brightness difference between any of the devices and multiple devices, and determining the adjustment amount of the current device by adding the light source brightness adjustment value and the brightness difference.

[0014] In a fourth aspect, a device for adjusting multiple devices is provided, the device comprising: a calibration relationship calling module for calling the calibration relationship of multiple devices; an adjustment coefficient determination module for determining the adjustment coefficient between multiple devices based on multiple calibration relationships; an adjustment amount determination module for determining the corresponding adjustment amount based on the real-time adjustment variable of any one of the devices and the corresponding adjustment coefficient, and adjusting the device based on the adjustment amount.

[0015] The technical solution provided in the embodiment of the present application can determine the calibration relationship of each device and each light source in the machine vision system. Based on this relationship, a mapping relationship can be constructed between the real-time light source and the light source under standard conditions, so as to objectively reflect the current state of the light source; and it can be used for multiple machine vision systems with the same configuration parameters. By obtaining the key parameter expression differences between any device and multiple other devices, the adjustment parameters between the multiple devices are determined, and the adjustment amount of the corresponding device is determined based on the real-time adjustment amount of any device and the adjustment parameters of the corresponding device, and the unified key parameter adjustment of the multiple devices is achieved based on the adjustment amount. The method provided in this embodiment can ensure the consistency of image effects between multiple devices, improve the compatibility of devices, and reduce the detection difficulty of software algorithms. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] The methods, systems, and / or programs in the accompanying drawings will be further described according to exemplary embodiments. These exemplary embodiments will be described in detail with reference to the drawings. These exemplary embodiments are non-limiting exemplary embodiments, wherein example numerals represent similar structures in the various views of the drawings.

[0018] Figure 1 It is a schematic diagram of the calibration system structure provided in an embodiment of the present application.

[0019] Figure 2 This is a schematic diagram of the server structure provided in an embodiment of the present application.

[0020] Figure 3 This is another structural diagram of a calibration system provided in an embodiment of the present application.

[0021] Figure 4 It is a flow chart of the calibration relationship determination method provided in an embodiment of the present application.

[0022] Figure 5This is a simulation diagram of the calibration relationship function provided in an embodiment of the present application.

[0023] Figure 6 It is a structural diagram of the calibration relationship determination device provided in an embodiment of the present application.

[0024] Figure 7 This is a flow chart of the multi-device adjustment method provided in an embodiment of the present application.

[0025] Figure 8 This is a schematic diagram of the structure of the adjustment device between multiple devices provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to better understand the above technical solution, the technical solution of the present application is described in detail below through the accompanying 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 solution of the present application, rather than limitations on the technical solution of the present application. In the absence of conflict, the embodiments of the present application and the technical features in the embodiments can be combined with each other.

[0027] In the following detailed description, numerous specific details are set forth by way of example in order to provide a thorough understanding of the relevant teachings. However, it will be apparent to one skilled in the art that the present application can be practiced without these details. In other instances, well-known methods, procedures, systems, compositions, and / or circuits have been described at a relatively high level, without detail, to avoid unnecessarily obscuring aspects of the present application.

[0028] Flowcharts are used in this application to 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 may not be executed in sequence. Instead, these execution processes may be executed in reverse order or simultaneously. In addition, at least one additional execution process may be added to the flowchart. One or more execution processes may be deleted from the flowchart.

[0029] Before further explaining the embodiments of the present invention in detail, the nouns and terms involved in the embodiments of the present invention are explained. The nouns and terms involved in the embodiments of the present invention are subject to the following interpretations.

[0030] (1) In response to, it is used to indicate the conditions or states on which the executed operations depend. When the dependent conditions or states are met, one or more operations executed may be in real time or with a set delay. Unless otherwise specified, there is no restriction on the order in which the multiple operations executed are executed.

[0031] (2) Based on, used to indicate the conditions or states on which the executed operations depend. When the dependent conditions or states are met, one or more operations executed may be in real time or with a set delay. Unless otherwise specified, there is no restriction on the order in which the multiple operations executed are executed.

[0032] The core of a machine vision system is image acquisition and processing. All information comes from images, and image quality is crucial to the entire vision system. The camera and lens must work together with a light source to illuminate the feature locations and capture the corresponding images. This ensures that image quality is not affected by changes in ambient light, ensuring that the captured features are distinct and have a certain contrast, which facilitates the software algorithm's subsequent image processing.

[0033] Light sources for machine vision include, but are not limited to, LEDs, xenon lamps, and halogen lamps. As light sources age, their brightness decreases, a phenomenon known as light decay. Therefore, the brightness of the light source needs to be compensated after a period of use. When the accumulated usage reaches a certain length, the compensation may have satisfied the project requirements and requires replacement. Image quality and brightness are not only affected by the light source itself, but also by the camera and lens. When a vision system is configured, the selection of its light source, lens, and camera is also locked in. The working distance, angle, and brightness of the light source, the working distance and aperture value of the lens, and the camera's parameter configuration are also determined. Any change to these locked-in variables will alter the image quality and brightness, and the software algorithm's detection results will also change. Therefore, the stability of the detection system depends on the stability of each system.

[0034] In real-world business scenarios, multiple machine vision systems are typically deployed on the same production line. Hardware and installation issues can lead to image differences between these devices. These differences are typically not addressed in real-world scenarios or are made compatible through algorithms. This approach can lead to the inability to use a unified set of parameters across devices. After replacing new hardware, the original parameters become unusable, and the same piece of production material can produce multiple inspection results on multiple devices. These significant differences between devices can lead to numerous missed and false detections, impacting production yield.

[0035] In order to solve the above technical problems, an embodiment of the present application provides an adjustment method between multiple devices, which is used to uniformly adjust multiple machine vision systems and eliminate the differences between multiple devices.

[0036] The machine vision system referred to as the device in this embodiment can be a machine vision system used in detection and measurement, and further can be a machine vision system used in the detection and measurement of semiconductor products. Among them, semiconductor products include wafer products, packaging structures, packaged chip products, and system-level semiconductor products. In other embodiments, it can also be applied to other precision component products. The machine vision system is used to project an illumination beam onto the surface of the above-mentioned product, and to capture the surface image of the product based on the illumination beam through an image acquisition device, and to analyze the captured surface image and determine whether the surface of the above-mentioned product has visible defects, damage or other undesirable features.

[0037] The machine vision system in this embodiment includes at least a light source and a camera. The light source provides an illumination environment for the object to be captured, and the camera uses the illumination environment to capture an image of the object to be captured. Furthermore, to adjust the machine vision system, a controller is provided, electrically connected to the light source and camera, respectively, for controlling the light source and camera. Control of the light source and camera includes turning them on and off.

[0038] For the multiple machine vision systems in this embodiment, the adjustment object is specifically the light source, and the adjustment parameter is the light source brightness. The logic is to obtain the light source brightness expression result of each machine vision system, determine the reference machine vision system among the multiple machine vision systems and the light source brightness expression difference between this reference system and other systems, and adjust the light source brightness in the multiple machine vision systems based on this light source brightness expression difference, so that the light source brightness expression in the multiple machine vision systems is unified.

[0039] The light source brightness expression result for each machine vision system is the functional relationship between the actual light source brightness and the displayed brightness, where the displayed brightness is determined by the image grayscale corresponding to the standard grayscale card image. Furthermore, the light source in the machine vision system has a brightness range, so the actual light source brightness should include the overall brightness range, where the overall brightness range is 0 to 255. The functional relationship between the actual light source brightness and the displayed brightness refers to the corresponding displayed brightness result under the control of the actual light source brightness point.

[0040] Based on this, before performing multi-device adjustment, each machine vision system needs to be calibrated to obtain the corresponding light source brightness expression result. In this embodiment, calibration is achieved by configuring a standard grayscale card in the machine vision system to build a calibration system.

[0041] It is understood that the multiple devices in this embodiment should have the same configuration. The relative positions of the cameras, lenses, and light sources should be mechanically consistent across the devices, with consistent lens aperture adjustments and consistent camera image integration times. Devices with different configurations or those with different configurations and parameter settings during use are not subject to adjustment in this embodiment.

[0042] In one embodiment, a calibration system 100 is provided for calibrating the above-mentioned multiple devices and establishing relationships between the multiple devices. For the specific structure of the calibration system, please refer to Figure 1 , including a machine vision system 10 and a standard grayscale card 20, wherein the machine vision system includes at least one light source 11 and an image acquisition device 12. In this embodiment, the light source is a coaxial point light source, and the image acquisition device includes a camera 121 and a lens 122. A standard grayscale card is disposed below the image acquisition device, and the image acquisition device is capable of acquiring images from the standard grayscale card.

[0043] The system further includes a controller 30 , which is electrically connected to the camera and the light source and is used to adjust the brightness of the light source and control the camera to capture images.

[0044] The server 40 is also included. For the structure of this server, please refer to Figure 2 As shown, the server may include components such as 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, and a communication module 405. The memory is used to obtain the captured image and the control parameters generated by the controller; the processor is used to retrieve data from the storage unit and process the data to obtain a processing result. Furthermore, the processing unit also communicates with the controller to issue control instructions to the controller for execution by the controller. The processing result in this embodiment refers to the calibration result, that is, the functional relationship between the actual brightness of the light source and the display brightness.

[0045] Among them, those skilled in the art can understand that Figure 2 The server structure shown in the figure does not constitute a limitation on the server, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0046] Processor 401 is the server's processing center, connecting various components of the server using various interfaces and circuits. By running or executing software programs and / or modules stored in memory 402 and accessing data stored in memory 402, it executes various server functions, processes data, and issues control instructions to the controller. In some embodiments, processor 401 may include one or more processing cores. In some embodiments, processor 401 may integrate an application processor and a modem processor. The application processor primarily handles the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 401.

[0047] In one embodiment, the server further includes a power supply 403 for supplying power to various components. In some embodiments, the power supply 403 can be logically connected to the processor 401 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. The power supply 403 can also include any of one or more DC or AC power supplies, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and other components.

[0048] In one embodiment, the server may further include an input module 404, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0049] In one embodiment, the server may further include a communication module 405. In some embodiments, the communication module 405 may include a wireless module. The server may use the wireless module of the communication module 405 to perform short-range wireless transmission, thereby providing users with wireless broadband Internet access. For example, the communication module 405 may be used to help users send and receive emails, browse web pages, and access streaming media.

[0050] In order to further improve the machine vision system's ability to acquire three-dimensional information, in another embodiment, the machine vision system 10 is improved by adding a light source capable of capturing three-dimensional image information. Based on this change in the machine vision system, in another embodiment, the calibration system is also changed accordingly. Figure 3In another embodiment, another calibration system 100a includes a machine vision system 10a, a standard grayscale card 20, a controller 30a, and a server 40. Unlike the previous embodiment, the machine vision system 10a in this embodiment includes a coaxial point light source 11a and a multi-layer ring light source 13. The multi-layer ring light source includes an image acquisition channel that enables the image acquisition device 12a to capture images of the standard grayscale card.

[0051] In one possible implementation, the multi-layer ring light source in this embodiment is configured from top to bottom with multiple independently controlled light source layers, including a four-layer structure. It is worth noting that the four-layer structure is only one possible implementation; the number of light source layers in the multi-layer structure can be adjusted based on actual detection needs. For example, other embodiments can also adopt a five-layer structure or a three-layer structure. The choice of a four-layer structure in this embodiment is determined based on the light source configuration required by the lighting environment.

[0052] Specifically, each light source layer in this multi-layer light source can be configured with different light-emitting devices with multiple control channels. For example, the first light source layer can be equipped with multiple blue light-emitting devices and multiple yellow light-emitting devices. Independent control channels for the blue and yellow light-emitting devices are electrically connected to the controller 30a, and the controller 30a controls the light emission of the blue and / or yellow light-emitting devices. It can be understood that this configuration of light-emitting devices can achieve three lighting modes: simultaneous blue and yellow light emission, or selectively emitting either blue or yellow light. The specific control of the lighting mode can be configured according to actual detection needs. Different color light sources have different levels of sensitivity to different defects, and this will not be further described in this embodiment.

[0053] It's worth noting that the light source brightness expression results provided in this embodiment are for each light source, and that the multi-layer ring light source in this embodiment can be configured with light-emitting devices controlled by multiple channels. This means that when calibrating a multi-light source machine vision system, it's necessary to determine the light source brightness expression results for each control channel. Specifically, when there are multiple control channels, the memory sequentially stores the image and process data corresponding to each control channel, and the processor sequentially determines the light source brightness expression results for each control channel.

[0054] The above calibration system can be used to calibrate the brightness of the light source in the machine vision system. As for how to implement the calibration, this embodiment provides a calibration relationship determination method, which can achieve the light source brightness expression result corresponding to the light source in each control channel of each machine vision system. This method can be configured in the processor for process execution. The processing process can be referred to in Figure 4 , including the following steps:

[0055] Step S41: based on the height change of the image acquisition device, the images of the standard grayscale card are acquired in sequence, and the height position corresponding to the image with the highest definition is obtained as the standard height position.

[0056] In this embodiment, the height change of the image acquisition device is achieved by the controller controlling the mechanical device corresponding to the image acquisition device, or it can be achieved by manual adjustment. The means for achieving the height change will not be described in detail in this embodiment.

[0057] In one implementation, the height of the image acquisition device is the height of the image acquisition device relative to the standard grayscale card. Specifically, the height adjustment of the image acquisition device is the relative height adjustment between the image acquisition device and the standard grayscale card. The location where the standard grayscale card is placed is the location where the material will be placed during the subsequent inspection process.

[0058] Furthermore, the standard height position is the height position corresponding to the image with the highest clarity. Image clarity can be determined using a clarity assessment method known in the art. For example, in this embodiment, a gradient-based method is used for assessment. This method is a conventional assessment method and will not be further described in this embodiment.

[0059] By continuously adjusting the height of the image acquisition device relative to the standard grayscale card to obtain the corresponding clarity evaluation results, and selecting the position height with the highest clarity as the standard position height, the optimal position of the image acquisition device can be determined. This position is also the standard position for image acquisition in subsequent detection processes.

[0060] Step S42. Based on the standard height position and standard light source brightness conditions, adjust the integration time of the image acquisition device to obtain multiple images of the standard grayscale card and corresponding multiple grayscale values, and determine the integration time corresponding to the target grayscale value as the standard integration time.

[0061] In one embodiment, for a standard light source brightness of 220, the target grayscale value is 255.

[0062] This process first determines the integration time for each light source control channel and adjusts the camera's corresponding integration time so that the light source corresponding to that control channel captures multiple images of a standard grayscale card at a brightness of 220. The camera integration time corresponding to an image grayscale value of 255 is then determined as the standard integration time. This standard integration time is the camera's standard integration time under that light source. This process is understood as being used for camera calibration, minimizing the camera's influence on the calibration results.

[0063] It is worth noting that the camera's standard integration time corresponds to the light source, meaning that different light sources have different standard integration times. Therefore, for light sources with multiple control channels, the standard integration time corresponding to each control channel should be determined separately during camera calibration to obtain the corresponding relationship between the camera's standard integration time and multiple light sources in the machine vision system.

[0064] Step S43: adjusting the brightness of the light source in sequence based on the standard integration time and obtaining the corresponding real-time grayscale value, and establishing a calibration relationship based on the brightness and the real-time grayscale value.

[0065] In this embodiment, the adjustment of the light source brightness is determined based on the adjustment step size, where the brightness change corresponding to the adjustment step size is 1. That is, when adjusting the light source brightness, the light source brightness is first set to 0, and the real-time grayscale value corresponding to the acquired image is determined based on this light source condition. Then, the light source brightness is gradually increased to 1 according to the adjustment step size, and a second acquisition is performed. Similarly, the light source brightness is gradually increased to 255, thereby obtaining the real-time grayscale value distribution results during the change from 0 to 255.

[0066] The real-time grayscale value can represent the brightness of the light source, and this brightness can be understood as the brightness displayed by the device software. In this embodiment, a functional relationship can be formed between the light source brightness and the real-time grayscale value. This functional relationship is the calibration file of the light source. That is, when there is a deviation between the two, it indicates that the light source has a brightness deviation.

[0067] In another embodiment, to more completely obtain the functional relationship, the real-time grayscale value can be the average of multiple grayscale values. Specifically, when capturing images under a single light source brightness condition, multiple images can be captured, and the grayscale values corresponding to the multiple images can be averaged to obtain the grayscale average for the current light source brightness condition. For example, 10 images can be captured for each light source condition, and the real-time grayscale values of the 10 images can be averaged to obtain the grayscale average. This grayscale average is then fitted to the actual light source brightness to obtain the functional relationship between the actual brightness and the displayed brightness, and a calibration file for the light source corresponding to this control channel is generated. For details on the functional relationship between the actual brightness and the displayed brightness, please refer to 5.

[0068] It is worth noting that for a multi-light source machine vision system, this process requires determining the functional relationship between each control channel and the light source, and integrating the functional relationships of the light sources corresponding to all channels to form the final calibration result.

[0069] In this embodiment, the calibration relationship of each device and each light source in the machine vision system can be obtained through steps S41 to S43. Based on this relationship, a mapping relationship between the real-time light source and the light source under standard conditions can be constructed, thereby objectively reflecting the status of the current light source.

[0070] With respect to the calibration relationship determination method provided in step S41-step S43, a calibration relationship determination device 60 is further provided for executing the above-mentioned processing process. This device is a virtual device provided in the controller. For details about this device, please refer to Figure 6 As shown, it includes the following components:

[0071] A standard height position determination module 61 is configured to sequentially capture images of a standard grayscale card based on the height change of the image capture device, and to obtain a height position corresponding to the image with the highest definition as the standard height position;

[0072] A standard integration time determination module 62 is configured to adjust the integration time of the image acquisition device based on the standard height position and standard light source brightness conditions to obtain multiple images of the standard grayscale card and corresponding multiple grayscale values, and determine the integration time corresponding to the grayscale value of the target grayscale value as the standard integration time;

[0073] The calibration relationship building module 63 is used to adjust the brightness of the light source in sequence based on a standard integration time and obtain the corresponding real-time grayscale value, and to build a calibration relationship based on the brightness and the real-time grayscale value.

[0074] The calibration relationship determination method and device provided in the above embodiment can completely determine the calibration relationship of the light source corresponding to each control channel corresponding to each machine vision system, which is used to indicate the functional relationship between the actual brightness of the light source corresponding to each control channel and the display brightness, that is, to indicate the current state of the light source through the objective standard of display brightness.

[0075] Regarding the scenario provided by this embodiment, for the adjustment between multiple devices, the applicant believes that the above calibration relationship can be used as the basic scalar for adjusting the differences between multiple machine vision systems. That is, for each light source, the same objective parameter, namely the image grayscale, is evaluated. Then, the objective parameter can be used to associate the light sources with the same control channel between different devices, thereby determining the difference between the light sources with the same control channel between different devices. This difference is a fixed difference. Moreover, based on the fixed difference, the adjustment amount of multiple devices can be obtained based on the adjustment amount of only one device, which can reduce the adjustment cost of multiple devices.

[0076] Specifically, regarding the above method, this embodiment also provides a method for adjusting multiple devices, which is used to determine whether there is a deviation between multiple visual machine systems and adjust the multiple devices based on the deviation. This adjustment method is also configured in the processor, see Figure 7 This adjustment method specifically includes the following steps:

[0077] Step S71: Retrieve the calibration relationship of multiple devices.

[0078] For steps S41-S43, the calibration relationship corresponding to any light source in any machine vision system can be determined, and this relationship is stored in the memory. The processor calls the calibration file of the relevant target device in the memory through instructions, thereby obtaining the calibration file corresponding to one or more light sources in at least two devices.

[0079] Step S72: Determine adjustment coefficients between multiple devices based on multiple calibration relationships.

[0080] Based on the obtained calibration file, the difference between the displayed brightness and the actual brightness of each light source in each device can be determined. Based on this difference, a fixed difference between the devices for this light source is determined. This fixed difference is used to indicate the brightness difference between the corresponding light sources between the devices. For example, if the calibration file for the first device records that the displayed brightness of the first light source is 200, the actual brightness of the light source is 189. If the calibration file for the second device records that the displayed brightness of the first light source is 200, the actual brightness of the light source is 186, then there is a fixed difference of 3 between the first and second devices for the first light source. This fixed difference serves as the adjustment coefficient for the first and second devices for the first light source.

[0081] The first device can be set as the reference device, and other devices, such as the second and third devices, can be set as the regulated devices. In other embodiments, the reference device can also be the second or third device. Here, the terms "first," "second," and "third" are used only to distinguish different devices and do not represent a ranking between the devices. Based on this, it can be understood that the adjustment coefficient between multiple devices in this embodiment refers to the fixed difference between the regulated device and the reference device.

[0082] Step S73: Determine an adjustment amount for the corresponding device based on the real-time adjustment variable of any of the devices and the adjustment coefficient of the corresponding device, and adjust the corresponding device based on the adjustment amount.

[0083] The real-time adjustment variable in this embodiment refers to the brightness adjustment amount of the light source corresponding to the reference device. The brightness adjustment amount of the corresponding light source of the adjusted device can be determined through this light source brightness adjustment amount and the fixed difference between the adjusted device and the reference device, and this brightness adjustment amount can be used to adjust the adjusted device.

[0084] The light source brightness adjustment amount refers to the adjustment of the light source brightness corresponding to the reference device, which is used to adjust the actual brightness of the light source to the display brightness.

[0085] It is worth noting that after multiple light sources in multiple devices have been used for a period of time, attenuation may occur and the attenuation of light sources in different light source channels may be different. At this time, it is necessary to re-calibrate the corresponding calibration coefficient using the standard grayscale card, and at the same time calculate the difference in attenuation corresponding to multiple light sources in multiple devices. The original production parameters are updated based on the difference and the new calibration coefficient to ensure that previously produced materials can be produced with consistent results.

[0086] In summary, the multi-device adjustment method provided in steps S71-S73 is applicable to multiple machine vision systems with identical configuration parameters. By obtaining the differences in key parameter expressions between any one device and multiple other devices, the adjustment parameters between the multiple devices are determined. The adjustment amount of the corresponding device is determined based on the real-time adjustment amount of any one device and the adjustment parameters of the corresponding device. Unified key parameter adjustment is then achieved for multiple devices based on the adjustment amount. The method provided in this embodiment can ensure consistency in image effects across multiple devices, improve device compatibility, and reduce the detection difficulty of software algorithms.

[0087] Similarly, for steps S71 to S73, a regulating device 80 is provided for executing the above-mentioned processing process. This device is a virtual device provided in the controller. For details about this device, please refer to Figure 8 As shown, it includes the following components:

[0088] The calibration relationship retrieving module 81 is used to retrieve the calibration relationships of multiple devices;

[0089] an adjustment coefficient determination module 82, configured to determine adjustment coefficients between a plurality of the devices based on a plurality of the calibration relationships;

[0090] The adjustment amount determination module 83 is configured to determine a corresponding adjustment amount based on the real-time adjustment variable of any of the devices and the corresponding adjustment coefficient, and adjust the device based on the adjustment amount.

[0091] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0092] To this end, an embodiment of the present application provides a computer-readable storage medium storing a plurality of instructions that can be loaded by a processor to execute the steps of any of the calibration relationship determination methods and / or adjustment methods provided in the embodiments of the present application. For example, the instructions can execute the following steps:

[0093] Based on the height change of the image acquisition device, the images of the standard grayscale card are sequentially acquired, and the height position corresponding to the image with the highest definition is the standard height position;

[0094] Based on the standard height position and standard light source brightness conditions, adjusting the integration time of the image acquisition device to acquire multiple images of the standard grayscale card, and determining the integration time corresponding to the grayscale value of the target grayscale value as the standard integration time;

[0095] The brightness of the light source is adjusted in sequence based on a standard integration time and a corresponding real-time grayscale value is obtained, and a calibration relationship is established based on the brightness and the real-time grayscale value.

[0096] or / and,

[0097] Retrieve calibration relationships based on multiple devices;

[0098] determining adjustment coefficients between a plurality of the devices based on a plurality of the calibration relationships;

[0099] An adjustment amount for the corresponding device is determined based on the real-time adjustment variable of any of the devices and the adjustment coefficient of the corresponding device, and the corresponding device is adjusted based on the adjustment amount.

[0100] The storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0101] According to one aspect of the present application, a computer program product or computer program is provided, comprising a computer program / instructions stored in a computer-readable storage medium. A processor of an electronic device reads the computer program / instructions from the computer-readable storage medium and executes the computer program / instructions, causing the electronic device to perform the methods provided in various optional implementations of determining calibration relationships and adjusting between multiple devices provided in the above-described embodiments.

[0102] Since the instructions stored in the storage medium can execute the steps of any calibration relationship determination method or / and the adjustment method between multiple devices provided in the embodiments of the present application, the beneficial effects that can be achieved by any calibration relationship determination method or / and the adjustment method between multiple devices provided in the embodiments of the present application can be achieved. Please see the previous embodiments for details and will not be repeated here.

[0103] In this application, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or plural.

[0104] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0105] The above is a detailed introduction to a calibration relationship determination method, an adjustment method between multiple devices, a storage medium and a program product provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for determining a calibration relationship, characterized in that: The method comprises: Based on the height change of the image acquisition device, the images of the standard grayscale card are sequentially acquired, and the height position corresponding to the image with the highest definition is the standard height position; Based on the standard height position and standard light source brightness conditions, adjusting the integration time of the image acquisition device to obtain multiple images of the standard grayscale card and corresponding multiple grayscale values, and determining the integration time corresponding to the grayscale value of the target grayscale value as the standard integration time; The brightness of the light source is adjusted in sequence based on the standard integration time and the corresponding real-time grayscale value is obtained, and a calibration relationship is established based on the brightness and the real-time grayscale value.

2. The method for determining a calibration relationship according to claim 1, wherein: The height of the image acquisition device is relative to the height of the standard grayscale card.

3. The method for determining a calibration relationship according to claim 1, wherein: The standard light source brightness is 220, and the target grayscale value is 255.

4. The method for determining a calibration relationship according to claim 1, wherein: The step of sequentially adjusting the brightness of the light source includes: sequentially adjusting the brightness of the light source based on an adjustment step.

5. The method for determining a calibration relationship according to claim 4, wherein: The brightness change amount of the adjustment step is 1.

6. The method for determining a calibration relationship according to claim 5, wherein: The real-time grayscale value is an average value of multiple grayscale values.

7. A calibration relationship determination device, characterized in that: The device comprises: A standard height position determination module is used to sequentially capture images of the standard grayscale card based on the height change of the image acquisition device, and the height position corresponding to the image with the highest definition is taken as the standard height position; a standard integration time determination module, configured to adjust the integration time of the image acquisition device based on the standard height position and standard light source brightness conditions to obtain multiple images of the standard grayscale card and corresponding multiple grayscale values, and determine the integration time corresponding to the target grayscale value as the standard integration time; The calibration relationship building module is used to adjust the brightness of the light source in sequence based on the standard integration time and obtain the corresponding real-time grayscale value, and build a calibration relationship based on the brightness and the real-time grayscale value.

8. A method for adjusting multiple devices, characterized in that: The method comprises: Retrieving a calibration relationship of multiple devices determined based on the method according to any one of claims 1 to 6; determining adjustment coefficients between a plurality of the devices based on a plurality of the calibration relationships; An adjustment amount for the corresponding device is determined based on the real-time adjustment variable of any one of the devices and the adjustment coefficient of the corresponding device, and the corresponding device is adjusted based on the adjustment amount.

9. The method for adjusting multiple devices according to claim 8, wherein: The adjustment coefficient is the brightness difference between devices, and the real-time adjustment variable is the light source brightness adjustment value; The determining of the corresponding adjustment amount based on the real-time adjustment variable of any of the devices and the corresponding adjustment coefficient includes: determining the brightness difference between any of the devices and multiple devices, and determining the adjustment amount of the current device by the sum of the light source brightness adjustment value and the brightness difference.

10. A multi-device adjustment device, characterized in that: The device comprises: The calibration relationship retrieval module is used to retrieve the calibration relationships of multiple devices; an adjustment coefficient determination module, configured to determine adjustment coefficients between a plurality of the devices based on a plurality of the calibration relationships; The adjustment amount determination module is used to determine the corresponding adjustment amount based on the real-time adjustment variable of any of the devices and the corresponding adjustment coefficient, and adjust the device based on the adjustment amount.

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