Optical crystal Vickers hardness and transmittance measuring system based on image processing

Abstract

The invention discloses an optical crystal Vickers hardness and transmittance measurement system based on image processing, particularly relates to the field of optical crystal measurement, and comprises an image collaborative acquisition module, an image preprocessing module, a feature extraction calculation module, a self-adaptive feedback module and a data output module. According to the optical crystal Vickers hardness and transmittance measuring system based on image processing, physical separation and synchronous acquisition of an indentation image and a transmission light field image are realized through an image collaborative acquisition module, the conflict between exposure parameters and focal length requirements of the same sensor is eliminated from a hardware architecture, and parameter adjustment caused by mode switching of a single sensor is avoided; repeated parameter adjustment caused by poor image quality is reduced through the image preprocessing module, and the measurement consistency is enhanced; an accurate optical crystal feature set is obtained through the feature extraction and calculation module, and invalid parameter adjustment is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of optical crystal measurement, and more particularly to an optical crystal Vickers hardness and transmittance measurement system based on image processing. BACKGROUND

[0002] With the wide application of optical crystals in high-end manufacturing fields, the accurate measurement of their mechanical properties and optical properties is particularly important. Existing measurement techniques have deficiencies in terms of automation level, measurement accuracy, and multi-parameter synchronous detection capability, making it difficult to meet the needs of modern industry for efficient and intelligent measurement systems.

[0003] Currently, Vickers hardness measurement typically relies on the traditional indentation method, which involves observing the indentation pattern under a microscope and calculating the hardness value. Crystal transmittance is usually measured using devices such as spectrophotometers. Although these devices can provide relatively accurate data, they may have calibration difficulties or data fluctuations in complex environments. By integrating structures and automating control, manual intervention is reduced, improving the testing efficiency and data consistency of single samples.

[0004] However, in actual use, there are still some shortcomings, such as the collection of indentation images and transmission light spots relying on the same image sensor. Since hardness testing requires high-resolution local imaging and transmittance detection requires global spot analysis, the exposure parameters and focal length requirements of the sensor in different modes conflict, resulting in insufficient imaging configuration adaptability, further causing the need to frequently adjust the position and parameters of optical components, causing interruptions in the measurement process, affecting real-time performance and measurement consistency. Especially when continuously detecting multiple samples, repeated positioning errors and parameter reset delays significantly reduce batch detection accuracy and efficiency. SUMMARY

[0005] To overcome the above-mentioned defects of the prior art, the present application provides an optical crystal Vickers hardness and transmittance measurement system based on image processing, which solves the problems raised in the background art by the following scheme.

[0006] To achieve the above-mentioned purposes, the present application provides the following technical solutions: The optical crystal Vickers hardness and transmittance measurement system based on image processing comprises: An image cooperative acquisition module is used to synchronously distribute the light beams of each measurement point in the optical crystal to a first image sensor and a second image sensor through an optical splitter to synchronously acquire a first imaging image set of the measurement points, wherein the first imaging image set at least includes a high-resolution indentation image obtained by the first image sensor and a transmission light field distribution image obtained by the second image sensor; An image preprocessing module is configured to perform a preprocessing operation on each image in the first imaging set to obtain a second imaging set with improved signal-to-noise ratio; A feature extraction computing module is configured to perform a feature extraction operation to obtain an optical crystal feature set corresponding to the second imaging set; An adaptive feedback module is configured to dynamically adjust imaging control parameters of the first image sensor and the second image sensor based on the optical crystal feature set, wherein the imaging control parameters at least include a first exposure parameter for controlling the first image sensor and a second exposure parameter for controlling the second image sensor; A data output module is configured to store and output the optical crystal feature set of the same measurement point.

[0007] Preferably, the image cooperative acquisition module, the optical splitter has a spectral splitting error less than 2% in a wavelength range of 400-700 nm. Preferably, the image cooperative acquisition module, the optical splitter has a spectral splitting error less than 2% in a wavelength range of 400-700 nm. .

[0008] Preferably, the image preprocessing module, obtaining the second imaging set with improved signal-to-noise ratio, specifically includes: A first preprocessing sub-flow, performing noise suppression and edge enhancement based on anisotropic diffusion filtering on the high-resolution indentation image; A second preprocessing sub-flow, performing light intensity distribution correction and effective area segmentation on the transmission light field distribution image.

[0009] Preferably, the feature extraction computing module, performing the feature extraction operation, specifically includes: An indentation analysis unit, performing sub-pixel level edge detection on the preprocessed high-resolution indentation image in the second imaging set, fitting out geometric features of the indentation profile, and calculating the Vickers hardness value of the measurement point based on the geometric features of the indentation profile; A light intensity analysis unit, performing light intensity distribution analysis on the preprocessed transmission light field distribution image in the second imaging set to obtain light intensity distribution features, and calculating the optical transmittance of the measurement point according to the light intensity distribution features.

[0010] Preferably, in the indentation analysis unit of the feature extraction computing module, the Vickers hardness value of the measurement point is calculated, specifically including: Extracting sub-pixel coordinate positions of indentation edges in the image; Fitting all extracted sub-pixel edge point sets into four straight line equations respectively using the least square method; Calculating sub-pixel coordinates of four indentation vertices by simultaneously solving equations of adjacent straight lines; According to the vertex coordinates, the first diagonal physical length and the second diagonal physical length are calculated using the Euclidean distance formula; The physical scale transmitted by the image preprocessing module is called to convert the pixel length into the physical length. The hardness value is automatically calculated according to the Vickers hardness calculation formula.

[0011] Preferably, the feature extraction calculation module calculates the optical transmittance of the measurement point in the light intensity analysis unit, and specifically includes: The arithmetic mean of the gray value of all pixels in the segmented effective light spot area is calculated as the transmitted light intensity measurement value of the measurement point ; The reference white field value transmitted by the image preprocessing module , that is, the standard light intensity value when the transmittance is 100%, is called to calculate the optical transmittance of the measurement point , which is specifically represented as: .

[0012] Preferably, the feature extraction calculation module further includes a data verification unit, and after the indentation analysis unit and the light intensity analysis unit are calculated, the following is executed: Check the residual sum of squares of the four straight lines fitted by the least square method, and if any residual is greater than a preset threshold, mark the Vickers hardness value of the measurement point with a low confidence flag; Check whether the calculated diagonal length is within a reasonable physical range based on the test force, and if it is out of range, mark it as invalid data; Check whether the transmitted light intensity measurement value is within the linear response interval of the sensor, and if not, mark the transmittance data with a suspicious flag; All data flag bits will be incorporated into the optical crystal feature set output.

[0013] Preferably, the adaptive feedback module dynamically adjusts the execution of the imaging control parameters of the first image sensor and the second image sensor, and specifically includes: A quality evaluator is configured to generate a quantitative index for evaluating image quality based on the optical crystal feature set or intermediate data thereof; A strategy decision maker is configured to generate a parameter adjustment instruction according to a preset control strategy based on the deviation of the quantitative index from a preset target range; A parameter mapper is configured to convert the parameter adjustment instruction into executable imaging control parameters.

[0014] The technical effects and advantages of the present application are: 1. The present application realizes the physical separation and synchronous acquisition of indentation images and transmission light field images through an optical splitter in the image cooperative acquisition module, eliminates the conflict between exposure parameters and focal length requirements of the same sensor from the hardware architecture, and avoids parameter adjustment caused by single sensor mode switching. 2. The present application improves the signal-to-noise ratio of high-resolution indentation images, improves the edge sharpness, improves the background uniformity of the transmission light field distribution image, reduces repeated parameter adjustment caused by poor image quality, enhances measurement consistency, and provides high-quality input for feature extraction. 3. The present application obtains accurate optical crystal feature set through the feature extraction calculation module, reduces invalid parameter adjustment, further improves measurement real-time performance and data reliability, and optimizes the pertinence and effectiveness of adaptive adjustment. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 A module block diagram of the optical crystal Vickers hardness and transmittance measurement system based on image processing according to the embodiments of the present application is provided. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0017] The terms used in the following embodiments of the present application are only for the purpose of describing the specific embodiments, and are not intended to be limiting to the present application. As used in the specification of the present application, the singular expression "one", "a", "said", "the above", "the", and "this" is intended to also include the plural expression, unless there is clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application means and includes any or all possible combinations of one or more listed items.

[0018] Hereinafter, the terms "first" and "second" are used only for the purpose of description, and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more features, and in the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0019] As shown in the accompanying Figure 1The image processing-based optical crystal Vickers hardness and transmittance measurement system shown comprises an image cooperative acquisition module, an image preprocessing module, a feature extraction and calculation module, an adaptive feedback module, and a data output module.

[0020] Specifically, the image cooperative acquisition module is configured to synchronously distribute light beams of each measurement point in an optical crystal to a first image sensor and a second image sensor through an optical splitter to synchronously acquire a first imaging graph set of the measurement point, wherein the first imaging graph set at least comprises a high-resolution indentation image acquired by the first image sensor and a transmitted light field distribution image acquired by the second image sensor.

[0021] It should be noted that the image cooperative acquisition module mainly comprises an optical splitter, a first image sensor, a second image sensor, a synchronous control unit, and a data interface, and through innovative optical path design and sensor configuration, indentation morphology and transmitted light field of the same measurement point are physically separated, synchronously acquired, and standardized output.

[0022] In a preferred embodiment, the optical splitter is configured to realize physical separation of light beams, and this embodiment adopts a cubic prism splitter structure, which is formed by two right-angle prisms through optical cementing along the hypotenuse, and a broadband medium splitter film with a specific splitting ratio is coated on the cementing surface. Meanwhile, the optical splitter is fixed on a six-dimensional adjustment frame to allow micron-level translation and milliradian-level deflection adjustment, so as to ensure that the centers of the two light spots after splitting coincide with the centers of the respective sensor target surfaces, thereby ensuring a flat spectral response characteristic with a splitting ratio error less than 0.5% in the 400-700 nm wavelength range of the first image sensor.

[0023] Further, the image cooperative acquisition module adopts a double-image sensor architecture, and the original light beams from the optical crystal are split to two sensors according to a preset optical path through the optical splitter. The first image sensor and the second image sensor are respectively located on two orthogonal light-out paths of the optical splitter. The first image sensor is a high-resolution CMOS sensor, which is configured to perform local macro imaging on the indentation area, has a pixel size less than 2.5 μm, and is equipped with a macro imaging lens group, so as to work in a local field of view with an object size less than 2 × 2 mm. The second image sensor is a high-dynamic-range CCD sensor, which is configured to acquire the overall intensity distribution of the transmitted light field passing through the sample, and is equipped with a telecentric lens, so as to work in a global field of view covering the entire optical crystal aperture.

[0024] ​​In a preferred embodiment, the synchronization control unit is implemented by an FPGA, which generates a unified TTL level hardware trigger signal, and distributes the signal to the external trigger interfaces of the first image sensor and the second image sensor through a coaxial cable; the FPGA internally integrates a delay compensation logic, which is based on the pre-calibrated inherent electrical delay difference between the two sensors, and performs a microsecond-level offset adjustment on the sending time of the trigger signal, to ensure that the exposure start time difference between the two sensors is less than 1 millisecond.

[0025] In a preferred embodiment, the data interface, when outputting, assigns the same globally unique timestamp and measurement point ID to the high-resolution indentation image and the transmission light field distribution image collected synchronously, and packs them into a data packet, i.e., the first imaging atlas, which is transmitted to the image preprocessing module downstream through the data interface.

[0026] Specifically, the image preprocessing module is configured to perform a preprocessing operation on each image in the first imaging atlas to obtain a second imaging atlas with improved signal-to-noise ratio.

[0027] It should be noted that the image preprocessing module is triggered and started by the image cooperative collection module, and reads the first imaging atlas data packet from the pre-allocated shared memory through a direct memory access mode; the second imaging atlas includes at least an indentation image with suppressed noise and enhanced edges, a light spot image with corrected background uniformity and accurately segmented effective area, a calibrated physical scale, a correction coefficient, a reference white field value, etc.; the physical scale is calibrated by shooting a standard micrometer scale image and calculating the number of pixels occupied by a known physical distance; the reference white field value is an average light intensity value calculated by the second preprocessing sub-flow after measuring a standard sample.

[0028] In a possible implementation, to generate a high-quality second imaging atlas, a double-pipeline processing architecture is adopted, which optimizes different characteristics of the first imaging atlas respectively: a first preprocessing sub-flow performs noise suppression and edge enhancement on the high-resolution indentation image based on anisotropic diffusion filtering; and a second preprocessing sub-flow performs light intensity distribution correction and effective area segmentation on the transmission light field distribution image.

[0029] Furthermore, the processing path of the first preprocessing sub-stream at least includes processing the original indentation image using an anisotropic diffusion filtering algorithm based on partial differential equations, and its diffusion coefficient will be adaptively adjusted according to the local gradient of the image, and strong smoothing will be performed in the smooth area with small gradient to filter out noise, while diffusion will be suppressed in the edge area with large gradient, thereby effectively smoothing the internal noise of the image while retaining and sharpening the real edge information of the indentation to the greatest extent; after noise suppression, the residual noise is further smoothed to locate the position where the grayscale changes drastically in the image, and the edge is identified by the zero crossing point of the second-order derivative.

[0030] Furthermore, the processing path of the second preprocessing sub-stream at least includes performing flat-field correction to compensate for various systematic, fixed-pattern noise and unevenness, thereby obtaining a corrected image with realistic light intensity distribution and uniform background; further filling tiny holes inside the light spot that may be caused by noise and smoothing its boundaries to extract the effective area where the light spot is located.

[0031] In a preferred embodiment, in the first preprocessing sub-stream, the noise suppression algorithm based on anisotropic diffusion filtering has a discrete iterative calculation formula as follows: , in, It is expressed as the number of iterations, Expressed as At the iteration, the gray value of the current pixel in the high-resolution indentation image is, It is expressed as the iteration step size, 、 Represented as the current pixel and its northern and southern neighbors in the Grayscale difference of iterations.

[0032] It should be noted that the number of iterations The value range is 1≤ ≤ , The adaptive feedback module is dynamically set according to the real-time noise estimation, with a typical value of 3 to 5; the iteration step size Used to control the grayscale variation allowed in a single iteration, the value range is ; In this embodiment, the iteration step size The adaptive feedback module is adaptively adjusted according to the signal-to-noise ratio estimation value, and the default value is defined as 0.2; in the discrete iterative calculation formula, the current pixel and its four neighbors in the north, east, south and west are included in the first The grayscale difference of the iterations, where is the edge stop function, defined as: , wherein, is expressed as the indentation contrast threshold, by calculating the gradient modulus histogram of the high-resolution indentation image, taking the first 70% quantile as the initial value.

[0033] In a preferred embodiment, in the second preprocessing sub-flow, based on the pre-acquired dark field image and flat field image , a flat field correction operation is performed on the transmitted light field distribution image, and the calculation formula is: , wherein, is expressed as the pixel value of the transmitted light field distribution image after flat field correction, is expressed as the pixel gray value of the transmitted light field distribution image directly output by the second image sensor at the current measurement point; after performing flat field correction, the Otsu method is used to automatically calculate the optimal gray threshold to distinguish the effective light spot area from the background dark edge, to perform effective area segmentation, and to binarize the image into foreground and background. A 3x3 pixel circular structure element is used on the binarized image to fill the holes, and the largest connected region is selected as the effective light spot area.

[0034] It should be noted that the dark field image required in the light intensity distribution correction is the average gray image output by the second image sensor under the condition of complete light shielding, which is obtained by averaging at least 10 images acquired under the condition of complete light shielding; the required flat field image is the average gray image output by the second image sensor when shooting a standard integrating sphere panel that emits light uniformly.

[0035] In the present embodiment, the physical scale, the reference white field value, and the default parameters in the discrete iterative calculation formula, etc. are stored in the non-volatile memory in the adaptive feedback module after initialization calibration; before the start of each measurement process, the adaptive feedback module is issued to the corresponding configuration register through the system bus for its call; after the first preprocessing sub-flow processing, the signal-to-noise ratio of the high-resolution indentation image should be improved by no less than 10 dB, and the edge sharpness should be improved by no less than 50%; after the second preprocessing sub-flow processing, the background uniformity of the light spot image should be better than 2%.

[0036] Specifically, the feature extraction calculation module is configured to perform a feature extraction operation to obtain an optical crystal feature set corresponding to the second imaging image set.

[0037] ​It should be noted that the feature extraction calculation module is triggered and started by an interrupt signal of the image preprocessing module, the interrupt signal includes a pointer to a shared memory address, and the shared memory address stores a packaged data packet of the second imaging atlas; and the optical crystal feature set at least includes consistent measurement point IDs, first diagonal physical lengths, second diagonal physical lengths, Vickers hardness values, average light intensity values and transmittance values in the first imaging atlas.

[0038] In a possible implementation, performing the feature extraction operation includes: a dent analysis unit performing sub-pixel level edge detection on the preprocessed high-resolution dent image in the second imaging atlas, fitting geometric features of a dent profile, and calculating the Vickers hardness value of the measurement point based on the geometric features of the dent profile; and a light intensity analysis unit performing light intensity distribution analysis on the preprocessed transmission light field distribution image in the second imaging atlas to obtain light intensity distribution features, and calculating the optical transmittance of the measurement point according to the light intensity distribution features.

[0039] Further, in the dent analysis unit, the sub-pixel level edge detection extracts sub-pixel coordinate positions of dent edges in the image , and is specifically represented as: , , wherein , are respectively unit normal vectors at edge points, is an integer pixel coordinate corresponding to the measurement point, is a sub-pixel offset in the normal direction to the extreme point; all the extracted sub-pixel edge point sets are fitted into four straight line equations respectively by using the least square method; the sub-pixel coordinates of four dent vertexes are calculated by simultaneously solving the equations of adjacent straight lines; the first diagonal physical length and the second diagonal physical length are calculated according to the vertex coordinates by using the Euclidean distance formula; the pixel length is converted into physical length by calling the physical scale transmitted by the image preprocessing module; and the hardness value is automatically calculated according to the Vickers hardness calculation formula.

[0040] It should be noted that the normal vector is approximately solved based on the preprocessed high-resolution dent image in the second imaging atlas, and is specifically represented as: , , wherein , are respectively gradient vectors of the preprocessed high-resolution dent image in x and y directions; and the calculation formula of the sub-pixel offset in the normal direction to the extreme point is specifically represented as: , wherein, , , are the second derivatives of the function , ; the gradient vector (Gx, Gy) and the second derivatives are directly obtained by convolving the pre-processed high-resolution indentation image with a built-in Gaussian differential filter called by the feature extraction and calculation module. Further, in the light intensity analysis unit, the arithmetic mean of the gray values of all pixels in the segmented effective light spot region is calculated, and the value is taken as the transmitted light intensity measurement value of the measurement point , i.e., the light intensity distribution feature; and the reference white field value

[0041] , i.e., the standard light intensity value when the transmittance is 100%, transmitted by the image preprocessing module is called to calculate the optical transmittance of the measurement point , which is specifically represented as: .

[0042] In a preferred embodiment, the feature extraction and calculation module further includes a data verification unit, and after the indentation analysis unit and the light intensity analysis unit are calculated, the following is performed: checking the residual sum of squares of the four straight lines fitted by the least squares method, and if any residual is greater than a preset threshold, marking the Vickers hardness value of the measurement point with a low confidence flag; checking whether the calculated diagonal length is within a reasonable physical range based on the test force, and if it is out of range, marking it as invalid data; checking whether the transmitted light intensity measurement value is within the linear response interval of the sensor, and if not, marking the transmittance data with a suspicious flag; all data flag bits will be incorporated into the optical crystal feature set output.

[0043] It should be noted that the preset threshold of the residual sum of squares of the indentation fitting is obtained by training and learning a large number of known qualified indentation image samples; the threshold of the standard deviation of the transmitted light intensity measurement value is set according to the noise model of the second image sensor and the photoelectric response linearity experiment; and the thresholds are stored in the adaptive feedback module and loaded when the corresponding module is started.

[0044] Specifically, the adaptive feedback module is used to dynamically adjust the imaging control parameters of the first image sensor and the second image sensor based on the optical crystal feature set; wherein the imaging control parameters at least include a first exposure parameter for controlling the first image sensor and a second exposure parameter for controlling the second image sensor.

[0045] ​​It should be noted that the working period of the adaptive feedback module is synchronized with the measurement period; after the feature extraction calculation at each measurement point is completed, the signal triggered by the feature extraction calculation module; the generated imaging control parameters will be issued and take effect through the driving interface of the image cooperative acquisition module before the acquisition of the next measurement point starts; the adaptive feedback module also receives a new sample start signal, when receiving the new sample start signal, the history accumulation value of the internal integrator of the strategy decision maker is cleared, and the imaging control parameters generated for the next measurement point are reset to a preset safe initial value, so as to avoid parameter interference between different samples.

[0046] In a possible implementation, dynamically cooperatively adjusting the imaging control parameters of the first image sensor and the second image sensor includes: a quality evaluator configured to generate a quantitative index for evaluating image quality based on the set of optical crystal features or intermediate data thereof; a strategy decision maker configured to generate a parameter adjustment instruction according to a preset control strategy according to a deviation of the quantitative index from a preset target range; and a parameter mapper configured to convert the parameter adjustment instruction into imaging control parameters executable by the first image sensor or the second image sensor.

[0047] It should be noted that the quality evaluator calculates, for the indentation image path, a quantitative index as an image contrast calculated by a Michelson contrast formula, and the quantitative index is specifically represented as: wherein, represents the indentation image contrast quantitative index, are a maximum gray value and a minimum gray value in an effective indentation area in the preprocessed indentation image, respectively, and the effective indentation area is an area within an indentation contour segmented by the feature extraction calculation module; for the light spot image path, a quantitative index is an average gray value obtained by calculating an arithmetic mean value of all pixels in the effective light spot area segmented after preprocessing.

[0048] Further, the strategy decision maker generates a parameter adjustment instruction using a PI control algorithm. For the first image sensor, a control error is a difference between a preset target contrast value and a currently measured contrast value, and an output is an adjustment amount of an exposure time of the first image sensor. In this embodiment, a proportional coefficient of the first image sensor contrast adjustment is , an initial value is 0.5-2.0, and an integral coefficient , an initial value is 0.1-0.5; for the second image sensor, a control error is a difference between a preset target average gray value and a current average gray value, and an output is an adjustment amount of a sensor gain of the second image sensor; in this embodiment, a proportional coefficient of the second image sensor gray adjustment is ​​The initial value is 0.3-1.5, and the integral coefficient The initial value is 0.05-0.3; the proportional coefficient And the integral coefficient Pre-set by historical data.

[0049] Further, the parameter mapper maintains a lookup table recording the minimum and maximum values of all adjustable parameters of the first and second image sensors, receives the output of the strategy decision maker to calculate a new exposure time value and determine whether the new exposure time value is within the allowable range; if not, limit it to the nearest limit value; the same operation is performed on the gain parameter; in this embodiment, the minimum value of the exposure time is not lower than the inherent delay time of the sensor, and the maximum value is not more than 50% of the measurement period; the minimum value of the gain parameter is 1x, and the maximum value is not more than 80% of the linear gain range of the sensor.

[0050] Specifically, the data output module is configured to store and output the optical crystal feature set of the same measurement point in association.

[0051] Secondly, in the drawings of the disclosed embodiments, only the structures involved in the disclosed embodiments are involved, other structures can be referred to the general design, and in the case of no conflict, the same embodiment and different embodiments of the present application can be combined with each other; Finally, the above only describes the preferred embodiments of the present application, and is not used to limit the present application, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An optical crystal Vickers hardness and transmittance measurement system based on image processing, characterized in that: include: An image collaborative acquisition module is configured to synchronously distribute the light beams at each measurement point in the optical crystal to a first image sensor and a second image sensor via an optical beam splitter, so as to synchronously acquire a first imaging atlas of the measurement point, wherein the first imaging atlas includes at least a high-resolution indentation image acquired by the first image sensor and a transmitted light field distribution image acquired by the second image sensor; An image preprocessing module is configured to perform a preprocessing operation on each image in the first imaging atlas to obtain a second imaging atlas with an enhanced signal-to-noise ratio; A feature extraction calculation module is used to perform a feature extraction operation to obtain an optical crystal feature set corresponding to the second imaging atlas; an adaptive feedback module configured to dynamically and collaboratively adjust imaging control parameters of the first image sensor and the second image sensor based on the optical crystal feature set; wherein the imaging control parameters include at least a first exposure parameter for controlling the first image sensor and a second exposure parameter for controlling the second image sensor; Data output module: used for associating, storing and outputting the optical crystal feature set of the same measurement point.

2. The optical crystal Vickers hardness and transmittance measurement system based on image processing according to claim 1, characterized in that: The image collaborative acquisition module, the optical splitter is between 400 and 700 The splitting ratio error within the wavelength range is less than .

3. The optical crystal Vickers hardness and transmittance measurement system based on image processing according to claim 1, characterized in that: The image preprocessing module obtains a second imaging atlas with enhanced signal-to-noise ratio, specifically comprising: A first preprocessing sub-stream is used to suppress noise and enhance edges of the high-resolution indentation image based on anisotropic diffusion filtering; The second preprocessing sub-flow performs light intensity distribution correction and effective area segmentation on the transmitted light field distribution image.

4. The optical crystal Vickers hardness and transmittance measurement system based on image processing according to claim 1, characterized in that: The feature extraction calculation module performs feature extraction operations, specifically including: an indentation analysis unit, performing sub-pixel edge detection on the preprocessed high-resolution indentation image in the second imaging atlas, fitting the geometric features of the indentation profile, and calculating the Vickers hardness value of the measurement point based on the geometric features of the indentation profile; The light intensity analysis unit performs light intensity distribution analysis on the preprocessed transmitted light field distribution image in the second imaging atlas to obtain light intensity distribution characteristics, and calculates the optical transmittance of the measurement point based on the light intensity distribution characteristics.

5. The optical crystal Vickers hardness and transmittance measurement system based on image processing according to claim 4, characterized in that: The feature extraction and calculation module calculates the Vickers hardness value of the measurement point in the indentation analysis unit, specifically including: Extract the sub-pixel coordinate position of the indentation edge in the image; All the extracted sub-pixel edge point sets are fitted into four straight line equations using the least squares method; By solving the equations of adjacent lines simultaneously, the sub-pixel coordinates of the four indentation vertices are calculated; According to the vertex coordinates, the physical length of the first diagonal and the physical length of the second diagonal are calculated using the Euclidean distance formula; Calling the physical scale transmitted by the image preprocessing module to convert the pixel length into a physical length; The hardness value is automatically calculated according to the Vickers hardness calculation formula.

6. The optical crystal Vickers hardness and transmittance measurement system based on image processing according to claim 4, characterized in that: The feature extraction and calculation module calculates the optical transmittance of the measurement point in the light intensity analysis unit, specifically including: For all pixels in the segmented effective spot area, calculate the arithmetic mean of their grayscale values ​​as the transmitted light intensity measurement value of the measurement point. ; Call the reference white field value transmitted by the image preprocessing module , that is, the standard light intensity value when the transmittance is 100%, calculate the optical transmittance of the measuring point , specifically expressed as: 。 7. The optical crystal Vickers hardness and transmittance measurement system based on image processing according to claim 4, characterized in that: The feature extraction calculation module further includes a data verification unit, which executes the following after the indentation analysis unit and the light intensity analysis unit complete the calculations: Checking the residual sum of squares of the four straight lines fitted by the least squares method, and if any residual is greater than a preset threshold, marking a low confidence flag for the Vickers hardness value of the measurement point; Check whether the calculated diagonal length is within the reasonable physical range based on the test force. If it is out of the range, mark it as invalid data; Check whether the measured value of the transmitted light intensity is within the linear response range of the sensor. If not, mark its transmittance data as suspicious. All data flags will be incorporated into the optical crystal feature set output.

8. The optical crystal Vickers hardness and transmittance measurement system based on image processing according to claim 1, characterized in that: The adaptive feedback module dynamically and collaboratively adjusts the imaging control parameters of the first image sensor and the second image sensor, specifically including: a quality assessor, configured to generate a quantitative index for assessing image quality based on the optical crystal feature set or intermediate data thereof; A strategy decision maker, configured to generate parameter adjustment instructions according to a preset control strategy based on the deviation between the quantitative indicator and a preset target range; A parameter mapper is used to convert the parameter adjustment instruction into executable imaging control parameters.

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