2976 results about "Optical imaging" patented technology

The invention discloses an AOI optical scheme automatic optimization method based on reinforcement learning, and belongs to the technical field of automatic optical detection. According to the method, a reinforcement learning technology is applied to automatic adjustment of optical schemes in a machine vision system, wafer images under different optical schemes are collected by using an AOI system, and scoring is performed by using a plurality of semantic segmentation models; constructing and training a non-reference image quality evaluation network, evaluating the optical imaging quality in real time, and designing a reward function on the basis; by using the Actor-Critic algorithm, the intelligent agent can autonomously learn an optimal parameter adjustment strategy, quickly adapt to different scenes, realize dynamic optimization of light source parameters and remarkably improve image quality, and an efficient and intelligent solution is provided for efficient application of a machine vision system in a complex industrial environment.

The invention discloses an acoustic-optical imaging semantic fusion detection method for underwater defects of a hydraulic structure, and the method comprises the steps: obtaining underwater acoustic and optical images of the hydraulic structure at the same time through underwater acoustic-optical imaging sensing for the underwater defects of the hydraulic structure; and on the basis, acoustic semantic features in the acoustic image are extracted through a semantic feature extraction module, optical image features in the optical image are processed by taking the acoustic semantic features as guidance, and a defect detection result is obtained when an underwater defect target exists in the image, so that underwater defect sound-light imaging semantic fusion detection is realized. The technology is suitable for health monitoring of various dam system hydraulic structures, and operation safety and water safety of hydraulic engineering are guaranteed.

The invention provides an evidence obtaining method and system based on image processing, and the method comprises the following steps: S1, generating a pixel-level depth-of-field distribution diagram of an input image through a multi-scale encoder-decoder network, employing an edge perception optimization layer in a decoding stage, and improving the depth-of-field boundary precision through minimizing a local gradient consistency loss function; s2, performing depth-of-field rationality verification based on an optical imaging physical model, and triggering a first-level tampering alarm by calculating a defocusing fuzzy radius and a gradient direction of a selected region when a difference between the defocusing gradient directions of a target region and a background region exceeds a preset threshold value; and S3, dynamically positioning a key pixel region, identifying a depth-of-field mutation boundary by using an edge detector, calculating by combining local texture complexity, screening a pixel set of which the entropy value is higher than a threshold value and which is located at the mutation boundary, correlating metadata to verify the rationality of the physical size and the spatial position of an object, and eliminating false detection caused by perspective transformation.

The invention relates to the technical field of smartphone surface defect detection, and discloses a smartphone defect detection method and system, and the method comprises the steps: firstly collecting defect detection image data through multi-dimensional optical imaging, and dividing the defect detection image data into a plurality of detection sub-regions; extracting surface defect features based on a texture enhancement technology, and extracting defect difference indexes in combination with pixel distribution and spatial correlation; then, the regularity of defect modes is analyzed and evaluated through multi-scale decomposition, the defect fluctuation amplitude is dynamically analyzed and evaluated through a sequential sequence, and the stability of defect difference indexes is judged by integrating the regularity and the fluctuation amplitude; and finally, comparing the stable defect difference index with reference data, and determining a detection result. According to the method, through multi-dimensional imaging, multi-scale analysis and dynamic evaluation, the recognition precision and reliability of complex surface defects are improved, the method is suitable for surface detection of smart phones of different materials and structures, and the high-quality detection requirement in large-scale production is met.

The invention discloses a nondestructive testing device for a steel profile and a testing method of the nondestructive testing device. According to the method disclosed by the invention, the ultrasonic technology is combined with optical imaging, so that synchronous detection of surface and internal defects can be completed at one time. Ultrasonic waves penetrate through the interior of the steel profile, and hidden defects such as cracks and air holes are accurately recognized; the optical camera module captures visible problems such as surface scratches and corrosion in real time. The integrated detection mode avoids the tedious process of step-by-step operation required by a traditional method, for example, magnetic powder detection of surface defects and ultrasonic scanning of an internal structure are not needed, the detection period is greatly shortened, and the method is especially suitable for steel structure buildings, bridge engineering and other scenes with high requirements for detection efficiency and has good application prospects. The full-process automatic design effectively reduces the influence of human intervention, and ensures the scanning continuity of the detection area; the intelligent algorithm automatically analyzes the ultrasonic echo signal and the optical image data, and judges the defect level according to the preset standard, thereby avoiding subjective misjudgment of manual visual inspection.

The invention relates to the technical field of chip optical detection, and discloses a high-precision defect detection method and system for a semiconductor chip. Initial detection data are obtained through laser scattering and photo-thermal microscopic detection, key visual features are extracted and converted into a multi-dimensional visual feature matrix, and the multi-dimensional visual feature matrix is used for detecting the defects of the semiconductor chip; according to the method, a fuzzy sensing area is positioned and potential defects are identified by using a map clustering algorithm, adaptive analysis of a supplementary visual angle is carried out and supplementary detection data is generated, and finally defect identification is carried out through the supplementary data and popularity information to obtain a chip defect result. The method effectively improves the precision and reliability of defect detection, especially has obvious advantages in recognition of complex and fuzzy regions, and solves the problem of insufficient precision of single-path optical imaging detection in the prior art.

The invention discloses a snapshot type hyperspectral imaging industrial online sorting system which comprises a support assembly, an optical imaging assembly and a motion control assembly. The bracket assembly consists of a bottom plate, and an adjustable bracket and a fixed bracket which are fixed on the bottom plate; the optical imaging assembly comprises a lighting unit, an imaging objective lens and a snapshot type hyperspectral camera, and can synchronously obtain space image information of a measured object and spectral information of a continuous wave band in a single exposure process; the motion control assembly realizes automatic transmission of the measured object through the transmission platform; the data processing module is integrated with an image preprocessing unit, a spectral analysis unit and a spectral database, and is used for end-to-end closed-loop control from original hyperspectral data generation to sorting decision making; the system adopts a metasurface light splitting structure to realize real-time decoding, performs material or category identification by using a pre-trained classification model, and finally automatically generates a sorting decision signal according to an identification result to drive a motion control assembly to complete sorting operation.

The invention discloses an optical imaging and coding hole technology fused optical imaging system and method, and aims to integrate scattered polarization components in a reflected light signal into coding light field data with clear layers by constructing a polarization coding modulation system, so as to highlight a coupling relationship among optical elements. A refocusing sequence and a focal plane chromatography technology are adopted, spatial geometric information and light intensity distribution characteristics of different depth layers are fully excavated, and a three-dimensional distribution rule of surface topography is disclosed; wavefront correction and deformable mirror control technologies are introduced, imaging parameters of an optical system are adjusted in a self-adaptive mode, and the application range of measurement precision is expanded; light intensity modulation analysis and phase unwrapping window processing are combined, the change trend of the surface curvature is depicted, and key feature points of morphology measurement are grasped; finally, multi-dimensional and multi-level optical measurement information is fused, three-dimensional measurement output with rich content and reliable precision is formed, and comprehensive and high-quality measurement technology resources can be provided for application scenes such as precision optical detection and surface quality evaluation.

In accordance with at least one aspect of this disclosure, there is provided an imaging agent, a including dye compound conjugated to an antigen specific targeting vector which can be particularly advantageous because their behavior in vivo can contribute to superior optical imaging properties, for example, by significantly increasing the target-to-background ratio of imaged tissues, leading to higher resolution imaging, and ultimately providing for better recognition of malignant tissue for resection and margin assessment and improved visualization during minimal invasive laparoscopic surgery, for example. A method of imaging tumor cells in a subject, can include, administering an imaging effective amount of an imaging agent according at least one embodiment of the invention; 2-4 hours after administration of the imaging agent, irradiating a region in the subject in which tumor cells are expected to be found with at a wavelength absorbed by the imaging agent; and detecting a signal from the imaging agent, thereby imaging the tumor cells, wherein the target-to-background ratio 2-4 hours after administration is from about 2.75 to about 15.

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 present invention relates to an in-situ micro-nano impact indentation testing instrument, falling within the technical field of material micromechanical testing. The instrument comprises a nitrogen generation module, an environmental chamber, a high / low temperature loading module, an “optical-infrared” in-situ monitoring module, an “electromagnetic-piezoelectric” coupling impact module, etc. After the nitrogen is introduced into the environmental chamber and the test area is determined by microscopic imaging, the “electromagnetic-piezoelectric” coupling impact module can drive an indenter to indent a specimen. An acoustic emission sensor embedded in the high / low temperature loading module can monitor the surface crack propagation of the specimen. The “optical-infrared” in-situ monitoring module can perform real-time high-speed optical imaging and infrared imaging on the impact indentation process. The present invention can perform micro-nano impact indentation testing on the material at high or low temperatures.

The invention discloses a melamine paper surface defect detection system based on optical detection, and relates to the technical field of industrial optical detection, and the melamine paper surface defect detection system comprises a polarized light signal generation module which employs a high color rendering index white light source to irradiate the surface of melamine paper, obtains a surface reflection light beam array carrying different polarization states, and modulates the surface reflection light beam array into eight groups of independent polarized light signals; the multispectral imaging and registering module inputs eight groups of independent polarized light signals into a free-form surface prism group and performs light splitting to generate a diffuse reflection texture image, a mirror reflection image and a near-infrared perspective image, and constructs a three-channel space registering image matrix; and the light path calibration module is used for extracting defect coordinate data and confidence score based on the pixel-level defect thermodynamic image, and performing light path compensation by adopting a real-time feedback regulation mechanism to obtain a dynamically calibrated stable optical imaging signal.

The invention provides an intrinsic solid-state ion diffusion coefficient test method and device based on optical imaging, and relates to the technical field of solid-state ion test.The method comprises the steps that a test sample is pretreated; carrying out a photoelectric test on the test sample; placing the electrochemical cell in an optical imaging system, connecting the electrochemical cell with an electrical testing system, applying a constant voltage deviating from a steady state to the monodisperse electrode plate, collecting the real-time change condition of the material under the modulation of the constant voltage in real time through an industrial camera, and outputting relational data of optical intensity and time; analyzing the diffusion path through in-situ characterization equipment, and obtaining an ion diffusion path corresponding to the to-be-detected ion battery electrode material particles in combination with dynamic information provided by an optical imaging system; and determining the characteristic time according to the relational data of the optical intensity and the time, and determining the intrinsic solid ion diffusion coefficient corresponding to the test sample by combining the characteristic time and the ion diffusion path corresponding to the to-be-tested ion battery electrode material particles.

The present invention provides an automatic focusing method, an electronic device, and a readable storage medium. The automatic focusing method comprises: using a target detection model to detect a target object in an image frame acquired at an initial focal length by an optical imaging device to be focused, so as to acquire a target object detection result; on the basis of the target object detection result, determining whether a target object is present in the image frame; if yes, determining an actual object distance on the basis of the target object detection result and the initial focal length, and on the basis of the actual object distance and a mapping relationship between the object distance and an optimal imaging focal length, determining the optimal imaging focal length; and if not, using a preset search algorithm to search for a focal length until an image having the highest definition value is found, and using a focal length corresponding to the image having the highest definition value as the optimal imaging focal length. The present invention primarily employs a deep learning-based automatic focusing method, supplemented by an image definition evaluation method. Compared with traditional passive focusing methods, the present invention greatly improves the focusing efficiency. Compared with traditional active focusing methods, the present invention eliminates a need for adding an additional optical ranging component, ensuring that the imaging device has a simple structure and a low cost.

The invention relates to a focusing control system and method based on sensor fusion and adaptive PID (Proportion Integration Differentiation). Belongs to the technical field of optical imaging and automatic control, and particularly relates to the technical field of optical imaging automatic focusing. The system comprises a Hall sensor group, a potentiometer, a focusing motor and a control processing unit, the Hall sensor group comprises two Hall sensors which are respectively arranged at two ends of a lens stroke and are respectively used for carrying out forward Hall limiting and reverse Hall limiting on the lens; the potentiometer is installed on a lens zoom gear shaft and used for collecting the AD value of a lens. The focusing motor is coupled with the lens focusing mechanism through a reduction gear and is used for controlling the movement of the lens; and the control processing unit is connected with the camera core, acquires an image definition value, receives data of the two Hall sensors and the potentiometer, and controls the motor driver. The problem that the final focusing position has deviation due to the fact that traditional PD control lacks integral terms and cannot completely eliminate steady-state errors is solved.

The invention discloses an LED chip appearance defect detection method based on image processing, and relates to the technical field of image processing, and the method comprises the following steps: S1, carrying out the multi-angle and multi-wavelength scanning of a defect-free reference LED chip under a stable exposure condition, extracting the dominant frequency vector and direction distribution information of the surface microstructure of the LED chip, and carrying out the detection of the appearance defect of the LED chip; an interference risk map is generated based on the dominant frequency vector and the direction distribution information. According to the method, dynamic adjustable optical imaging parameters and image processing results are deeply coupled, a closed-loop detection mechanism for adaptively inhibiting interference fringes is constructed, and accurate defect and interference distinguishing is realized through an interference risk map, a phase consistency index, discrimination subspace backstepping and optical adjustment, frequency domain notch and spatial domain detail recovery, so that the detection accuracy is improved. And in combination with confidence feedback and encryption sampling, the missing detection and false detection rate is remarkably reduced, and the detection stability and reliability are improved.

The invention discloses an optical imaging system tolerance correction method and device based on a neural network, and the method comprises the steps: building an optical imaging system degradation model under an assembly tolerance condition on the basis of considering a plurality of assembly working conditions; the optical imaging system degradation model is used for simulating the spatial change degradation process of the optical system under different assembly working conditions and generating a data set, each sample is an image pair composed of a clear image and a degraded image of a target, and the degraded image is marked with a working condition label; building a neural network model comprising a working condition estimation module and an image restoration module; and training the neural network model based on the data set and a preset loss function to obtain a trained working condition estimation-image restoration model which is used for restoring a clear image from the degraded image to be detected. The problem of imaging quality nonlinear degradation caused by eccentricity and inclination of the optical element in the assembling process is solved from the imaging end, the influence of assembling tolerance can be restrained, and the imaging quality is effectively improved.

The invention relates to the technical field of spectral analysis, and discloses a visible spectrum noise reduction and heavy metal ion detection method, which comprises the following steps: reacting a water sample to be detected with a color developing agent to generate a color developing system, obtaining a gray spectrum signal through optical imaging equipment, carrying out variational mode decomposition, optimizing the signal by adopting singular value decomposition, and calculating the noise of the heavy metal ions. And determining an optimal reconstruction order by using a particle swarm optimization algorithm and reconstructing a signal, finally extracting a feature value from the denoised spectral signal, and predicting the type and concentration of metal ions through a neural network model. Spectral global / local features are modeled through cooperation of multi-head self-attention and learnable position coding, signal frequency-time domain cross-modal fusion is realized in combination with variational mode decomposition and cross attention, training parameters are dynamically optimized by innovatively adopting a reinforcement learning strategy, classification and regression tasks are self-adaptively balanced based on a gradient diversity reward mechanism, and frequency-time domain cross-modal fusion is realized. And finally, dual precision improvement of ion type identification and concentration prediction and model robustness enhancement are realized in a complex noise scene.

The invention relates to the technical field of data signal processing, in particular to a distribution box electric spark monitoring method which has the advantages of not depending on optical imaging conditions, adapting to complex environments and being capable of effectively distinguishing difference between mechanical vibration and discharge signals. According to the invention, non-intrusive monitoring of electric sparks in the distribution box can be realized, and the limitation of a traditional visual method in a closed space is overcome. And the fusion of the multi-dimensional acoustic features improves the recognition accuracy and reduces the false alarm rate. The introduction of environmental parameters enables the system to adapt to different working conditions, and improves the robustness of monitoring. The method does not need to reform the structure of the distribution box, can be widely applied to state monitoring of various low-voltage distribution equipment, and effectively prevents equipment faults and safety accidents caused by electric sparks.

The invention discloses an underwater image de-scattering method, system and device for scattering field decoupling in the technical field of underwater optical imaging and computer vision, and the method comprises the steps: calculating an intensity graph and a scene linear polarization degree graph according to an obtained multi-scale underwater image; according to the intensity image, performing image signal decomposition by using a dynamically constrained background light separation model to obtain a background scattering component and a target feature component; according to the scene linear polarization degree map and the background scattering component, calculating fusion transmissivity according to a non-linear optical transmission equation; carrying out noise suppression processing on the fusion transmissivity by adopting a double-constraint optimization architecture to obtain the fusion transmissivity subjected to noise suppression processing; and performing image reconstruction through a reverse optical propagation model according to the fusion transmissivity and the target feature component subjected to noise suppression processing to obtain a scattering-removed underwater image. The method effectively breaks through the dependence of a traditional method on the uniform hypothesis of a scattered field, and provides high-precision visual restoration support for an underwater detection task.

The invention provides an optical imaging lens, the optical imaging lens has three lenses with focal power, and the optical imaging lens comprises a lens group, a bearing element group and a lens barrel, the axial distance T12 from the image side surface of the first lens to the object side surface of the second lens and the axial distance T23 from the image side surface of the second lens to the object side surface of the third lens meet the following conditions: 1.4 lt; t12 / T23lt; 2.0); the inner diameter d2m of the image side surface of the second bearing element, the inner diameter d1m of the image side surface of the first bearing element and the distance EP12 from the image side surface of the first bearing element to the object side surface of the second bearing element along the direction of the optical axis of the optical imaging lens meet the following conditions: 0.25 lt; (d2m-d1m) / EP12lt; and 1.5. The problem that miniaturization and high imaging quality of an optical imaging lens in the prior art cannot be considered at the same time is solved.

The invention discloses an optical imaging lens, which comprises a first lens group, a second lens group and a plurality of bearing pieces, the first lens group and the second lens group are sequentially arranged from an object side to an image side along an optical axis, and the first lens group is accommodated in a first lens barrel and comprises a first lens and a second lens; the second lens group is accommodated in the second lens barrel and comprises third to sixth lenses; the first to sixth lenses are sequentially arranged from the object side to the image side along the optical axis. A third bearing piece in contact with the object side face of the fourth lens is arranged between the third lens and the fourth lens, and a fourth bearing piece in contact with the object side face of the fifth lens is arranged between the fourth lens and the fifth lens. The maximum height LB of the second lens cone, the combined focal length F2 of the second lens group, the effective focal length f4 of the fourth lens and the distance EP34 of the third bearing piece and the fourth bearing piece on the optical axis; the on-axis distance SAG41 from the intersection point of the object side surface of the fourth lens and the optical axis to the vertex of the non-light-transmitting part of the object side surface of the fourth lens and the on-axis distance SAG42 from the intersection point of the image side surface of the fourth lens and the optical axis to the vertex of the non-light-transmitting part of the image side surface of the fourth lens meet the following conditions: 0.5 lt; lB / F2lt; 1.5, 1.6 lt, 1.5, 1.6 lt; f4 / F2lt; 1.8, and 0.5 lt; eP34 / SAG41 + SAG42lt, and SAG41 + SAG42 < 2.

The utility model discloses an optical imaging system. The optical imaging system comprises a lens cone, an imaging group and a second spacing element, wherein the imaging group and the second spacing element are arranged in the lens cone. The imaging group sequentially comprises a linear polarization film, a reflective polarization element, a quarter-wave plate, a first lens, a second lens, a third lens, a fourth lens and a partial reflection layer from the first side to the second side along the optical axis; wherein the first lens and the second lens are glued, and the third lens and the fourth lens are glued. The second spacer element is disposed on the second side of the second lens and is in contact with the second side of the second lens. Wherein the outer diameter D0m of the second side end face of the lens barrel and the outer diameter D2m of the second side face of the second spacing element meet the condition that D0m-D2m is larger than or equal to 4.51 mm and smaller than or equal to 5.8 mm; the inner diameter d2m of the second side surface of the second spacing element, the inner diameter d2s of the first side surface of the second spacing element, and the axial distance T23 from the second side surface of the second lens to the first side surface of the third lens satisfy the following formula: (d2m-d2s) / T23 is greater than or equal to 0.97 and less than or equal to 2.79.

The invention discloses a multi-optical fiber bundle imaging mode dimension space conversion plasma spectrum analysis system, which is characterized in that a two-dimensional optical fiber array comprising M * N optical fiber micropores is arranged on an optical fiber area array, a one-dimensional optical fiber array comprising M * N optical fiber micropores is arranged on an optical fiber linear array, and an optical fiber surface is connected by adopting M * N optical fibers according to a preset connection relation, the two-dimensional optical fiber array is converted into the one-dimensional optical fiber array, the optical grating disperses light transmitted by the optical fiber linear array, then the light is focused by the imaging lens and then is subjected to optical imaging by the CCD detector, and the spectral data conversion module converts a spectral image into a spectral data graph of each optical fiber channel. According to one-to-one correspondence of optical fibers in the two-dimensional optical fiber area array and the one-dimensional optical fiber linear array, the distribution state of elements in the plasma is reconstructed, and multi-optical-fiber sample element content detection is achieved.

The invention discloses an ultra-wide-spectrum endoscopic imaging device capable of being used for short-wave infrared fluorescence imaging, which is used for in-vivo minimally invasive imaging and comprises an illumination module, a wide-spectrum image transmission module, an imaging module and an image processing module. The illumination module consists of a light source and a light guide optical fiber, and is used for generating illumination light from ultraviolet to short wave infrared band and transmitting the illumination light to the wide-spectrum image transmission module; the wide-spectrum image transmission module consists of a few-interface optical imaging channel and a light guide illumination channel, and is used for illuminating an imaging target, exciting target fluorescence and collecting image signals from ultraviolet to short-wave infrared bands; the imaging module is composed of an optical filter and an imaging camera, and the imaging camera can be a wide spectral response image sensor or can be formed by combining cameras working in different wavebands and is used for converting optical images in different wavebands into image data; and the image processing module is used for registering and fusing image data of different wavebands in real time and displaying the image data.

The invention relates to the field of surgical robots, and particularly discloses an intraoperative risk assessment system for a cataract surgical robot, comprising: a patient biomechanical monitoring unit for collecting a contact force between an instrument and an eye tissue, and calculating an anterior chamber equivalent pressure value according to an axial force component of the contact force and a contact area between the instrument and a cornea; the patient optical imaging monitoring unit is used for collecting microstructure images of the cornea and the lens capsule and quantifying the energy release density of ultrasonic emulsification; the robot motion parameter monitoring unit is used for collecting joint motion resistance, instrument tail end three-dimensional coordinates, motion speed and attitude angle of the robot; the multi-mode joint reasoning unit is used for identifying a high-risk operation state when the contact force is higher than a first preset value and the energy release density is higher than a second preset value; by adopting the technical scheme of the invention, multi-dimensional real-time monitoring can be realized, and a dynamic risk prediction model can be established by fusing heterogeneous data through an intelligent algorithm.

An optical imaging system includes a first lens having a negative refractive power; a second lens having a negative refractive power; a third lens having a positive refractive power; a fourth lens having a negative refractive power; a fifth lens having a positive refractive power; a sixth lens having a positive refractive power; and a seventh lens having a negative refractive power. At least five of the lenses are made of a plastic material.

The invention relates to the technical field of optical imaging, and discloses a periscopic camera module which comprises a base internally provided with an installation cavity, an anti-shake motor installed on the base, a lens installed on the anti-shake motor and facing the installation cavity, an imaging assembly installed on the base and a steering optical element. The base is provided with a movable part capable of moving relative to the lens, the movable part is fixed through a locking part, and the steering optical element is installed on the movable part. According to the steering optical element, the movable part and the locking part are movably arranged on the base, so that the position of the movable part can still be adjusted after the lens, the anti-shake motor and the like are installed, the light reflection effect of the steering optical element can be optimal through adjustment, then the movable part is fixed through the locking part, and sealing in the installation cavity is guaranteed; therefore, the imaging quality is improved and the influence caused by errors is reduced.

The invention belongs to the technical field of optical imaging equipment, and particularly relates to a lens driving device which comprises a base and a motor mechanism, the motor mechanism comprises a frame which is arranged on the base, an AF coil is arranged on the side wall of one side of the frame, and the AF coil and an AF magnet arranged on the side wall of the base are oppositely arranged so that the frame can move in the third direction relative to the base; the OIS coil plate is arranged in the frame, and an OIS coil is arranged in the OIS coil plate; the carrier is arranged in the frame, the OIS coil plate is located between the carrier and the frame, an OIS magnet is arranged at the bottom end of the carrier, and the OIS magnet and the OIS coil are oppositely arranged so that the carrier can move in the first direction and the second direction relative to the frame. Through an innovative position design mode, magnets adopted by AF zoom operation and anti-shake operation are independent and do not interfere with each other, and the stability of automatic focusing and optical anti-shake control is ensured.

The invention relates to the technical field of machine vision detection, particularly discloses a mechanical part surface defect vision detection system, and aims to solve the problems of blind areas, environment light sensitivity, insufficient tiny defect detection capability and the like in the detection of complex curved surface high-reflection parts. Comprising an optical imaging module, a geometrical morphology sensing module, a dynamic polarization regulation and control module, an image fusion and enhancement module and a defect identification and decision module. The three-dimensional morphology of the surface of the part is sensed in real time, the imaging polarization state is dynamically regulated and controlled according to the three-dimensional morphology, multi-frame polarization image fusion and digital diffraction enhancement processing are combined, full-coverage and high-contrast detection of the complex curved surface part is achieved, motion blur is effectively restrained, and the detection capacity of sub-pixel-level tiny defects and the system environment adaptability are improved.