1025 results about "Magnification" patented technology

The invention discloses an electrostatic induction and optical imaging principle-fused online monitoring device and method for wear particles of a water-lubricated bearing, and belongs to the field of state monitoring of mechanical equipment. The device comprises a square insulation detection cavity, a detection electrode array, an electromagnetic shielding shell, a high-speed optical imaging module and a signal processing unit, the square insulation detection cavity is installed in a bearing lubrication water loop. The detection electrode array is fixed to the outer wall of the cavity and used for capturing electrostatic signals generated when the abrasion particles pass through. The electromagnetic shielding shell wraps the detection cavity and is grounded through a wire to eliminate environmental electromagnetic interference. The high-speed optical imaging module integrates a high-magnification microscope lens and a CMOS sensor, is coaxially mounted with the detection cavity, and obtains the morphology characteristics of the wear particles in real time; and the signal processing unit performs multi-modal data fusion analysis on the electrostatic signal and the optical image. Through cooperative detection of electrostatic induction and optical imaging, the monitoring precision and reliability of the wear particles of the water-lubricated bearing are remarkably improved.

The invention relates to the technical field of pathological image analysis and mining, and particularly discloses an ovarian cancer subtype classification method based on prototype learning and multi-view deep embedding clustering, and the method comprises the following steps: S1, collecting a tissue pathological image of an ovarian cancer patient and a corresponding full-view digital pathological image; and S2, generating a multi-view data set. According to the ovarian cancer subtype classification method based on prototype learning and multi-view deep embedding clustering, the problem that in the prior art, patch-level labels are generally lacked in the field of multi-instance pathological images, so that many natural image processing methods cannot be applied to the field of pathological images is solved. A ResNet backbone network is used for extracting features of pathological images under the maximum magnification, a small number of pathology prototypes are introduced to guide deep embedded clustering through pathology expert priori knowledge, a pathology image spectrogram is introduced to serve as a reference view, and the accuracy and stability of clustering are enhanced.

The invention discloses a method for optimizing micro-crack segmentation based on deep learning and super-resolution reconstruction, and the method comprises the steps: cutting an image in real time, obtaining an image block which takes a component as a target main body, and synchronously recording a homography matrix for geometric mapping; selecting an amplification strategy to improve the resolution, and recording a scale mapping relation; inputting the enhanced image block into a double-flow network; adaptive fusion and reconstruction are carried out on the two branch features, and a high-resolution texture image is output; generating a geometrically corrected ortho-image, fusing the geometrically corrected ortho-image with original illumination information, and outputting a corrected image with a known pixel size; identifying cracks, spalling and honeycomb diseases in parallel; generating a unified defect confidence map; calculating real geometric parameters of the BIM in a BIM global coordinate system through coordinate back projection; and generating quantitative defect reports and maintenance suggestions. The method has the advantage that seamless connection between the detection result and the BIM global coordinates is realized.

The invention relates to a cloth flaw detection method, device and equipment and a storage medium, and the method comprises the following steps: carrying out the multi-angle light source irradiation of the surface of cloth, obtaining a texture image, and carrying out the grid segmentation of the texture image into detection units; and extracting a gray value sequence of each unit, calculating an edge difference by using a gradient operator, generating a texture edge change curve to identify an abnormal wave crest, and determining a defect candidate region. And carrying out local amplification imaging based on the candidate region coordinates, and extracting defect shape feature parameters. The defect types are determined according to the parameters, quality grade division is performed on the cloth according to the parameters, and a quality grade report is finally generated, so that the technical problems of low defect identification precision and easy missing detection of fine defects caused by uneven illumination and texture interference in the existing cloth defect detection method are solved.

The invention discloses a semiconductor defect detection method and device, and the detection method comprises the steps: controlling the bright field illumination and the objective magnification, and obtaining the surface microstructure morphology of a to-be-detected sample; determining the process type of the sample to be detected based on the surface microstructure morphology, and automatically determining dark field illumination light intensity parameters of at least two groups of dark field light sources according to a preset mapping relation between the process type and the dark field illumination light intensity parameters; according to the tissue morphology of the sample, at least two dark field light sources with different incident angles are controlled to carry out dark field illumination on the sample to be detected from different directions, and scattered signal images corresponding to different dark field angles are obtained through at least two detectors respectively; and analyzing defect information of the to-be-detected sample based on the scattered signal images at the dark field angles. The detection method can be adaptive to defect detection of different process sheet types, can effectively improve the detection precision of defect diversity and directivity, improves the detection signal-to-noise ratio, and efficiently detects multiple different types of defects at the same time.

The invention relates to the technical field of digital pathology acquisition, and discloses a digital pathology picture acquisition method. The method comprises the following steps: acquiring sample characteristic data such as thickness, dyeing degree and structural characteristics of a tissue sample to be detected, and determining initial image acquisition parameters including exposure time, image resolution and optical magnification; and meanwhile, environment condition data such as temperature, humidity and environment illumination intensity of a scanning environment are collected, so that whether the initial parameters are adjusted or not is judged. When adjustment is needed, collecting preliminary image data, extracting quality features including image definition, color accuracy and detail retention degree, calculating feature values, and comparing the feature values with historical image quality feature values in a historical database; and if the same characteristic value does not exist in the historical database, calculating the similarity, and adjusting the initial image acquisition parameters according to the comparison result or the similarity. According to the method, sample characteristics and environmental conditions are comprehensively considered, and the quality of the digital pathological picture is effectively improved.

The invention discloses an underwater measurement method based on a zoom camera and a laser diode, which adopts the zoom camera to measure a laser spot image and greatly expands the application scene of equipment. The lasers A, B and C are manufactured based on laser diodes, the linearity of power adjustment can be well guaranteed, and measurement errors caused by too bright or too dark laser spots in images shot by the camera can be effectively avoided. According to the underwater measurement method provided by the invention, not only can the distance of the target object be measured, but also the feature size of the target object can be measured; in the installation process of the underwater measurement device, an error measurement link of the installation position of the laser is added, and the error is fully considered when the feature size of the target object is measured, so that the measurement precision is improved. During calibration, the average value of the height of the triangle and the corresponding bottom edge ratio in the maximum magnification and minimum magnification states of the zoom camera is taken as an independent variable, so that the influence of magnification change on calibration precision is reduced.

The invention belongs to the technical field of infrared optics, and discloses a long-wave infrared continuous zooming microscope lens. The lens is provided with two lenses, namely a first lens and a second lens which are sequentially and coaxially arranged between an object plane and an image plane; the first lens is a meniscus positive lens of which the convex surface faces the image side, and the second lens is a meniscus positive lens of which the convex surface faces the image side; the first lens and the second lens can move between an object plane and an image plane so as to carry out high and low magnification switching. The long-wave infrared continuous zooming microscope lens can realize multi-magnification switching, and also has the characteristics of small number of lenses, large target surface and clear imaging; the working wave band is 8-12 [mu] m, the magnification factor is 0.2-0.6, the F number of the image space is 1.5, the number of pixels is 1280 * 1024, and the size of the pixels is 12 [mu] m.

The invention provides a method for correcting the layout of a photomask, and is applied to the technical field of semiconductors. According to the method and the device, a plurality of pixel graphs of which the interval lengths do not meet a preset range are screened out based on the interval lengths between adjacent pixel graphs, and then the key sizes of the screened pixel graphs are multiplied by N times according to different proportions, so that a plurality of first test photomasks are constructed; and then determining the optimal magnification ratio of the initial photomask based on the combination of the wafer data, the incremental limit suboptimal solution and the two-side clamping theorem, namely obtaining the target photomask, so that the unexpected effects are that the optimal magnification ratio of each pixel graph in the initial photomask can be rapidly determined only by using a small part of pixel graphs in the initial photomask, and the target photomask is obtained. The manufacturing efficiency and quality of the photomask and the space utilization rate of the photomask and the wafer are improved, and the manufacturing cost of the photomask is reduced.

The invention relates to the technical field of visual inspection in the optical module industry, and provides a method and a device applied to AOI (Automatic Optic Inspection). A low-magnification microscopic imaging module of the fixed shooting vision subsystem is controlled to carry out fixed shooting on a detection object on the object carrying platform to obtain a global image, and each flying shooting point position coordinate is positioned according to the global image; controlling a motion shaft to drive a flying shooting vision subsystem to move according to the coordinates of the flying shooting point positions, and performing flying shooting on the flying shooting point positions to obtain a plurality of local high-definition images; taking the global image as a background, and splicing the acquired multiple local high-definition images into a complete to-be-detected image; performing region cutting on the to-be-detected image according to the category of the to-be-detected object to obtain each region image; and judging the defect category of each regional image according to the defect characteristics, and generating a defect detection result. According to the method, the problem that the actual extraction of large-area defects is incomplete is solved, and the comprehensiveness and accuracy of detection are ensured.

The invention relates to the field of visual processing, and provides a super-resolution image real-time processing method and device fusing an attention mechanism. The method comprises the following steps: acquiring a to-be-processed low-resolution image; performing initial feature coding on the low-resolution image to obtain a shallow feature map; performing adaptive modeling on the feature contribution degree of each spatial position and each feature channel in the shallow feature map in combination with a mixed attention mechanism, and generating an attention-enhanced depth feature map; converting a feature map channel number of the depth feature map into a spatial resolution, converting image feature information in the depth feature map according to a feature contribution degree and re-projecting the image feature information to a target image space corresponding to the spatial resolution, and generating a high-resolution feature map corresponding to a target magnification in the target image space through a pixel rearrangement mode; and reconstructing the high-resolution feature map into a target high-resolution image. Efficient real-time processing of the super-resolution image is achieved, and the image reconstruction definition and the detail reduction degree are improved.

The invention relates to the technical field of semiconductors, and provides an amplification factor calibration method of a scanning electron microscope. The method comprises the following steps: in a TEM imaging mode, TEM measurement data of a key structure of a TEM sample is determined, and the TEM sample is a TEM sample with a known process structure size or clear lattice fringes; in an SEM imaging mode, determining an SEM measurement data set of the key structure of the TEM sample under different SEM amplification factors; each SEM magnification of the scanning electron microscope is calibrated based on the TEM measurement data and the SEM measurement data set. The method is easy and convenient to operate, does not need to depend on a standard sample, and is lower in calibration cost and higher in calibration accuracy.

The invention discloses a microbial spatial distribution monitoring method and system based on a multi-level microscopic scanning image, relates to the technical field of image processing, and is used for carrying out multi-level grid traversal type scanning image acquisition on an observation area of microscopic examination data. Identifying and counting the number of each target microorganism in each image and the position information of each target microorganism in the corresponding hierarchical grid, and storing the information into a to-be-identified hierarchical data set corresponding to each target microorganism; and according to the ecological type of each target microorganism, respectively inputting the corresponding to-be-identified hierarchical data set into the corresponding trained multi-organism distribution probability density model to obtain a spatial distribution rule of each microorganism in the microscopic examination data. By adopting multi-stage magnification grading scanning, the interaction and distribution rules among microbial species are respectively described according to microbial ecological types, and the accuracy of microbial distribution observation is improved.

The utility model relates to a double-objective-lens three-pressure-head visual brinell hardness tester which comprises a shell, a turntable housing is arranged at the inner top of the shell, and a rotatable five-functional-position turret mechanism is arranged in the turntable housing. According to the utility model, by adopting the five-functional position turret mechanism, the rapid switching of the objective lens and the pressure head is realized, so that the test efficiency is greatly improved, meanwhile, the design of the double objective lenses enables the hardness tester to observe indentations under different magnification times, the measurement accuracy and flexibility are improved, and the test efficiency is improved. The design of the three detection pressure heads enables the durometer to easily adapt to different test requirements without replacement, the arrangement of the camera mechanism enables the test process to be recorded in real time and facilitates subsequent data analysis and processing, the host is used as the core of the control system and can realize automatic control of the whole test process, and the display is embedded in the face frame, so that the whole test process is more convenient. Therefore, the user can visually see real-time data in the testing process, and the operation is more convenient.

The invention provides a circuit for automatically adjusting magnification times and realizing synchronous sampling, and belongs to the technical field of power electronics. The circuit comprises an amplifying circuit, a resistance switching circuit, a phase locking circuit and an acquisition circuit, the amplifying circuit is used for receiving and processing an original signal, obtaining a voltage signal and analyzing an amplification factor required by the voltage signal, and an amplifier is correspondingly connected to a resistor in the resistance switching circuit according to the required amplification factor and is used for acquiring the voltage signal. And amplifying the voltage signal according to the amplification factor, receiving the amplified voltage signal by the phase-locked loop, analyzing the amplified voltage signal to obtain an average voltage, and adjusting the output frequency of the phase-locked loop according to the average voltage to lock the phase. And the acquisition circuit is used for synchronously sampling the amplified voltage signal according to the locked phase. In an electric power system data acquisition application, the amplification factor can be automatically adjusted, phase synchronization can be realized, and signal acquisition and data analysis of different capacitive devices of a power grid can be satisfied.

The invention discloses a 3D Gaussian splash rendering optimization method based on a Unity engine in VR, and relates to the technical field of computer graphics. PLY point cloud files are converted into SOG high-compression formats containing multi-level LOD information, after low-transparency Gaussian points are removed, Morton coding sorting is carried out on the center coordinates of the Gaussian points, and then the 3D Gaussian splash rendering optimization method based on the Unity engine in VR is realized. The method comprises the following steps: constructing an octree spatial index containing a spatial bounding box and multiple LOD data, removing Gaussian points in a grading manner according to a camera distance, selecting an LOD hierarchy, carrying out deep barrel sorting on visible Gaussian points, executing drawing by taking a barrel as a unit, and combining near-to-far sorting, an improved mixed equation and screen space edge removal and amplification operation to obtain a target image. According to the method, through multi-dimensional optimization such as loading, space elimination and rendering, the loading efficiency of the VR equipment is improved, the rendering burden is reduced, Tile-Based hardware is adapted, and smooth operation of 3D Gaussian splashing on the VR all-in-one machine is realized.

An electronic device is provided. The electronic device includes a display, an image sensor, an image signal processor for processing frames transmitted from the image sensor, a scaler arranged between an output end of an image pipeline and an input end of the display, memory, comprising one or more storage media, storing instructions, one or more processors operatively connected to the display, the image sensor, the image signal processor, the scaler, and the memory, wherein the instructions, when executed by the one or more processors individually or collectively, cause the electronic device to acquire, from the image sensor, a first frame of a first zoom magnification, control that a second frame to Nth frames are image-processed at the first zoom magnification through the image signal processor while the first frame of the first zoom magnification processed through the image signal processor is output to the display, receive a user input for requesting the display of a second zoom magnification, which differs from the first zoom magnification at the time of N+1 frame acquisition, request the image signal processor to process the N+1 frame, set to transmit, to the scaler, a second zoom magnification request at the time of N+1 frame acquisition, and allow the scaler to scale, in a second frame output order, at the second zoom magnification requested at the time of N+1 frame acquisition, a second frame processed at the first zoom magnification in the image signal processor so as to transmit same to the display.

The invention relates to an improved cage type light field imaging system and a debugging method, and belongs to the technical field of light field imaging, and the system comprises a main lens which is used for collecting light spots on an object surface, and enabling the light emitted by the light spots to be imaged on a micro lens; the micro lens is used for separating the light collected by the main lens into light beams in different directions and imaging the light beams on a virtual image plane; the relay lens is used for carrying out secondary imaging on the light beams in different directions to different pixels of a CCD detector of the camera; the relay lens comprises a first lens and a second lens, the focal lengths of the first lens and the second lens are positive, the focal length of the first lens is smaller than that of the second lens, and the magnification of the relay lens is larger than 1: 1. In the debugging process of the system, parallel light beams are arranged in front of the micro lens, and the position of the micro lens is determined in the mode that the parallel light beams vertically enter the micro lens. The system is not influenced by vignetting and distortion generated by the relay lens any more, and the debugging method improves the positioning precision of the micro lens.

The invention relates to a continuous zoom cycle-scan television system based on a zoom collimation scanning field lens structure and application thereof. Light reflected by a target image horizontally passes through the focusing group, the zooming group, the compensation group and the collimating field lens group in sequence along an optical axis, is obliquely reflected by 45 degrees by the galvanometer group and then vertically passes through the fixed group, is obliquely reflected by 45 degrees by the reflector group again and then horizontally passes through the optical filter switching group leftwards, and finally is imaged on a detector photosensitive surface of the high-definition imaging module; and the high-definition imaging module carries out photoelectric conversion and image processing and then outputs a high-definition video or image. According to the invention, the problem that the image quality is reduced during the swing scanning of the peripheral scanning television is solved, the turn-back of the light path is realized through the cooperation between the galvanometer group and the reflector group, and the galvanometer group rapidly swings the reflector to control the direction of the light beam to realize image motion compensation, so that the peripheral scanning detection function is realized. The system can be used for panoramic dead-corner-free monitoring and detailed reconnaissance of key targets, and is widely applied to the fields of intelligent monitoring, military reconnaissance, automatic driving and the like.

The invention provides a pollen image rapid scanning method under a high-magnification microscope based on retrieval guidance of a low-magnification microscope. The method comprises the following steps: firstly, rapidly scanning a 1000 mm < 2 > region under a whole cover glass through a low-magnification microscope, identifying pollen particles possibly existing in the region, and establishing a prior distribution diagram; and then, in a high-power microscope scanning stage, fine imaging is only carried out on the pollen of the potential target areas, and the areas which are confirmed to be blank are quickly skipped. Compared with a traditional full-area high-power microscope scanning scheme, the intelligent scanning method based on low-power microscope guidance can remarkably reduce invalid imaging time and improve the overall detection efficiency.

The invention provides an image high-definition amplification method and system for generating a planning intention graph. The method belongs to the technical field of image processing and territorial space planning. The method comprises the following steps: acquiring an original planning intention map by using image acquisition equipment, and carrying out image preprocessing on the acquired original planning intention map; adopting a feature extraction network in a deep learning model to perform feature extraction on the pre-processed planning intention graph; professional knowledge in the territorial space planning field is collected and sorted and converted into rules and models which can be processed by a computer, and a planning knowledge base is constructed; constructing a feature optimization model in combination with the feature quantification result and the planning knowledge base; by combining professional knowledge in the territorial space planning field, a planning knowledge base is constructed, and the knowledge is introduced into the training of a deep learning model, so that the generated planning intention map not only is improved in visual quality, but also can better meet the planning requirements, and the reasonability and availability of each element in the image are ensured.

The invention relates to the technical field of medical image processing and artificial intelligence cross application, in particular to a medical image detection method based on a cross-channel and cell density adaptive mechanism. According to the method, on the basis of a YOLO backbone architecture, a cell density adaptive attention module, a cross-channel feature enhancement module and a multi-magnification detection head are introduced, and a multi-dimensional cooperative enhancement detection network model is constructed and formed; and accurate detection and semantic feature enhanced characterization of medical targets in scenes with different tissue cell densities, different target scales and different image magnification factors are realized. According to the technical scheme, through core mechanisms of cell density adaptive modeling, cross-channel feature interaction, hierarchical feature fusion and the like, the technical problems of insufficient detection stability, weak model generalization ability, insufficient target semantic feature expression and the like in the existing medical image detection technology are effectively solved; finally, high-precision, low-delay and high-expandability pathological image automatic detection is realized.

The invention discloses an objective lens for wafer surface defect detection, and relates to the technical field of optical devices, the objective lens comprises three lens groups which are sequentially arranged according to the light incident direction, and the focal powers are respectively positive, negative and positive; the first lens group comprises a first lens with positive focal power, a second lens with negative focal power and a third lens with positive focal power, and the second lens group comprises a fourth lens with positive focal power and a fifth lens with negative focal power. The third lens group comprises a sixth lens with negative focal power, a seventh lens with positive focal power and an eighth lens with positive focal power, and the objective lens formed by arranging the lenses can correct various imaging differences, especially distortion, field curvature, astigmatism, axial chromatic aberration and chromatic aberration of magnification in the process of wafer detection imaging, so that the imaging quality is improved. The high resolution ratio and the large view field are achieved, the view field reaches 40 mm, the theoretical resolution ratio sigma is 3 microns, and the wafer detection efficiency can be greatly improved.

The invention relates to a display method and device, equipment and a chip. The method comprises the following steps: receiving layer information of a to-be-processed layer sent by a graphics processing unit (GPU); determining a target super-resolution multiple according to the layer information; determining a rendering resolution according to the target super-resolution multiple and the display resolution; sending the rendering resolution to a GPU, so that the GPU generates a rendered image according to the rendering resolution and the to-be-processed layer; and performing super-magnification display on the rendered image based on the target super-resolution multiple. By adopting the method, the optimal balance between the performance and the display effect is realized.

A method for adjusting a position of a substrate, includes: acquiring primary positional data indicating the positions of the edge portions (S31); acquiring secondary positional data indicating the positions of the edge portions after a stage has been moved (S33); calculating, using the primary positional data and the secondary positional data, difference amounts between the positions of the edge portions before the stage has been moved and the positions of the edge portions after the stage has been moved; and calculating an optical magnification ratio of each of the edge portions from each of the difference amounts and an amount of movement of the stage and correcting each of the positions of the edge portions of the primary positional data based on the calculated optical magnification ratio of each of the edge portions, thereby acquiring corrected positional data (S34).

The invention provides a fan blade background region adaptive segmentation method and system oriented to a complex environment. The fan blade background region adaptive segmentation method comprises the steps of extracting channels and edge feature operators of various color spaces; establishing illumination non-deformation transformation; detecting a sky area through a superpixel segmentation method, and performing adaptive adjustment; generating a blade probability graph by integrating multiple features; segmenting the blade probability graph to obtain a preliminary segmentation result; optimizing initial segmentation result energy by minimizing an energy function; and introducing a sub-pixel positioning method to perform edge refinement on the optimized preliminary segmentation result, and outputting a segmentation result. According to the invention, high-precision detection of the foreground and background areas of the fan blade is realized under the working conditions of a field open environment, various light environments, complex blade surface textures and the like; the problems that the background segmentation precision of an existing method in a complex field environment is insufficient, and the contradiction exists between the amplification factor and the small-size defect distinguishing capacity in fan blade non-stop detection are solved.

The invention discloses a focal length dynamic regulation and control method and system for target secondary confirmation, and relates to the technical field of computer vision and image processing. The focal length dynamic regulation and control method and system for the secondary confirmation of the target comprises the following steps: S1, taking over a real-time video stream of a dome camera, and collecting and preprocessing image structure basic data; s2, based on the image structure basic data, target attributes are recognized, and state fluctuation is judged; s3, by taking the focusing mark as a control basis, calculating a focusing magnification by combining spatial characteristics and state fluctuation; and S4, constructing an initial abnormal behavior sample library, and executing similarity evaluation of abnormal structures in the abnormal behavior sample library based on the behavior feature sequence extracted from the focusing image. The problems that secondary confirmation cannot be carried out and related information cannot be preserved when the suspicious target recognition confidence coefficient is insufficient are solved.

The invention relates to a method for operating a particle beam device for imaging, processing and / or analyzing an object, and to a computer program product and to a particle beam device for carrying out the method. The method comprises the steps of: providing control data for a relative positioning of a particle beam of the particle beam apparatus with respect to the object, the control data comprising information on a magnification value and on a velocity value; transforming the provided control data into actuation data for actuating the movable object vehicle or actuating the deflection device to deflect the particle beam, the actuation data comprising information about magnification values and about actuation speed values; a relative movement of the object and the field of view of the particle beam device relative to each other is performed using the actuation data.

The invention discloses a magnification lens and an imaging system. The magnification lens comprises a system front group and a system rear group. The system front group comprises a first lens, a second lens, a third lens, a fourth lens, a fifth lens, a sixth lens, a seventh lens and an eighth lens; the system rear group comprises a ninth lens, a tenth lens, an eleventh lens and a twelfth lens; wherein the combined focal length of the front group of the system is fA, the combined focal length of the rear group of the system is fB, and fA / fB is larger than or equal to 2.83 and smaller than or equal to 3.00. By reasonably setting the number of lenses included in the system front group and the system rear group in the zoom lens and the focal length matching mode of the system front group and the system rear group, the magnification of the zoom lens can be improved, and finally, the magnification of the zoom lens reaches 2.8 * or above, and application requirements are met; meanwhile, the reasonable focal length matching of the system front group and the system rear group can also improve the total length of the optical system, so that the total length of the optical system is within 80mm.

This application discloses a focusing system, semiconductor device, and focusing control method, relating to the field of semiconductor detection technology. The magnification of the first imaging module is less than that of the second imaging module, and the first defocus amount of the object under test determined based on the first optical signal from the first detection module is greater than the second defocus amount of the object under test determined based on the second optical signal from the second detection module. Therefore, wide-range coarse focusing is achieved based on the first branch, and high-precision fine focusing is achieved based on the second branch, satisfying various focusing accuracy requirements. That is, different focusing accuracy modes share some optical elements, simplifying the system structure; moreover, based on the first optical signal received by the first detection module, the reflectivity of the object under test at a first position is determined, and the gain of the second detection module and / or the output power of the illumination module are adjusted in real time according to the reflectivity, ensuring that the photodetector in the second imaging module always operates in a high signal-to-noise ratio state, improving focusing accuracy.