56 results about "Source imaging" patented technology

The invention discloses a brain power supply imaging method and system based on a physical information neural network. The method comprises the following steps: establishing a three-layer boundary element method head model based on a Maxwell equation set under quasi-static approximation and calculating a lead matrix; carrying out filtering, artifact suppression and standardization processing on the multi-channel electroencephalogram signals; inputting the standardized signal into a neural network encoder to extract a time sequence feature tensor, estimating the source current density based on the feature tensor, and performing forward calculation by using the lead matrix to obtain a predicted scalp potential; constructing a mixed loss function consisting of a data fidelity item, a physical consistency item and a physical heuristic regularization item, and performing network training and optimization by taking minimization of the loss function as a target; and when the training meets a convergence condition, outputting a visualization result of the brain endogenous current density spatial distribution. According to the method, electromagnetic physical constraints are introduced, so that the physical consistency, interpretability and stability of electroencephalogram inversion are improved.

The invention discloses a surface defect detection system based on a microcrystalline glass panel finished product, and relates to the technical field of surface defect detection. The defect full-dimensional dynamic state map construction module is used for constructing and updating a defect full-dimensional dynamic state map containing defect three-dimensional coordinate information, multi-modal feature confidence information, virtual-entity parameter deviation information and feature definition-registration precision linkage threshold information in real time; the structured light three-dimensional contour acquisition module is used for acquiring three-dimensional contour data of the surface of the microcrystalline glass panel; the multi-modal feature fusion module is used for collecting two-dimensional image data of multi-light-source imaging and extracting multi-modal feature information; the digital twin virtual debugging module is used for constructing a virtual detection environment based on the defect full-dimension dynamic state graph; the problem of feature confusion caused by light source combinational logic solidification in an existing multi-light-source switching system is effectively solved.

The invention relates to the technical field of computer vision, and discloses a computer vision-assisted dental restoration adaptation system, which comprises an image acquisition module, an image processing module, an adaptation evaluation module, a central control module and a feedback optimization unit, high-resolution image data, including visible light images, three-dimensional scanning data and infrared images, of the interior of the oral cavity and a restoration body are obtained through multi-source imaging equipment of the image acquisition module, the form, texture and temperature distribution characteristics of the oral cavity environment are captured, and the image contrast and the alignment precision are enhanced in combination with the illumination control unit and the positioning calibration unit. Data integrity and detail visibility are ensured, and a reliable basis is provided for subsequent image processing; the image processing module performs preprocessing, feature extraction and segmentation on the acquired image data, so that the accuracy and efficiency of adaptive state analysis are improved.

The invention provides a fundus camera system integrated with adaptive optics and a correction method, and relates to the technical field of ophthalmology imaging. The fundus camera system comprises a beacon light source, an imaging light source and an imaging sensor; the device comprises a wavefront sensor, a wavefront correction device and a control module, and the wavefront correction device comprises a focusing lens group and a deformable reflector; the focusing lens group and the deformable reflector are arranged in the same light path from the beacon light source to human eyes and from the human eyes to the wavefront sensor; moreover, the control module executes a two-step closed-loop control strategy of first focusing and second correction: firstly, based on a first measurement result of the wavefront sensor, the focusing lens group is driven to move so as to compensate low-order aberration; and after the focusing is completed, the deformable reflector is driven to deform based on the subsequent measurement result of the wavefront sensor so as to compensate the high-order aberration in a closed-loop manner. On the basis of inheriting the advantage of rapid focusing in the prior art, the self-adaptive optical technology is further integrated, so that the limitation of high-order aberration on resolution is solved.

The small-size lens defect classification detection system comprises a light source imaging system, a defect simulation data set and a defect detection and identification system, the light source imaging system comprises a first light source located under the lens, a second light source surrounding the horizontal periphery of the lens, a third light source projecting from the side of the lens at a low angle and having an irradiation angle lower than that of the second light source, and an image acquisition device for acquiring front or cylindrical surface images of the lens; generating lens defect images in batches by the defect simulation data set; the defect detection and identification system takes a lens defect image and a real image collected by the light source imaging system as training data, and after model training, defect identification and classification are carried out on the lens image collected by the light source imaging system in real time. The defect imaging contrast ratio is effectively improved through multi-light-source combined illumination, the problem that defect samples are scarce is solved in combination with simulation data, and efficient, accurate and automatic detection of multiple defects of a small-size lens is achieved.

The application discloses a mobile fire detection system and method, and belongs to the technical field of fire detection. The system realizes over-distance accurate positioning and sub-pixel level precision. Through a unique "polynomial fitting + extreme value calculation" algorithm, the system can perform three times curve fitting on the signals of 2-3 detection units covered by the fire source imaging, and can analyze the sub-pixel level center coordinates by derivation. In combination with a preset coordinate mapping table, the fire source positioning precision can be improved to within 0.3 meters at a distance of 150 meters, and the specific tunnel post number and lane position can be accurately output, so that the limitation of the traditional detector that can only give an area alarm is completely changed. In terms of adaptability to complex environments, the application not only solves three major pain points of the traditional flame detector, i.e., positioning loss, weak anti-vibration and high false alarm rate, but also provides a complete set of high-reliability, intelligent and practical fire monitoring and emergency command tools for tunnel safety.

This invention discloses a high-precision density reversal method and system for gravity anomalies based on regular, stable, and high-speed solution. [Solution] Based on the above-mentioned field source regularization solution, we propose using data with false anomalies at the field source imaging depth as boundary value conditions. Again, by solving the upper space of the first class boundary value problem of Laplace's equation, we calculate gravity anomalies on the ground and perform least-squares optimization iterative solution with the actual ground anomalies to obtain high-precision anomaly imaging data at the field source depth that does not contain false anomalies due to the Gibbs effect. This depth is used as the top interface of the field source, and the top interface is divided into grid prisms to construct the field source morphology. Density inversion is performed on each prism top surface in the frequency domain to obtain the density distribution of the field source morphology. Since this algorithm is implemented in the frequency domain and the inversion is performed at a known field source depth, the present invention is a gravity density inversion method with high speed, high precision, and high resolution characteristics, and provides a new concept for realizing the solution of gravity field source density parameters.

The application discloses a real-time visual image matching positioning method for an optical communication module, relates to the field of optical visual positioning, and aims to solve the problem of accurate matching positioning of the module. The application constructs a unified transformation relationship from a multi-source imaging unit image coordinate system to a device mechanical coordinate system, fuses template matching and feature matching technologies, combines a structure model preset area region of interest, and drives adaptive distribution of an imaging mode and collection parameters, performs high-quality feature extraction and redundant supplementary collection based on multi-source images, improves a transparent window in a complex area, introduces a geometric model constraint and a residual error elimination mechanism in a fusion process, realizes high-confidence fusion of features of each area, and finally obtains an overall six-degree-of-freedom attitude through a rigid body registration and pose solving algorithm and outputs key structure coordinates, so that the recognition precision and engineering implementability of the optical communication module in positioning, assembly and detection and other links are improved.

This disclosure pertains to the field of exploration geophysics and presents a method and system for combined active and passive source reverse time migration imaging of metallic minerals. The method includes: performing time difference correction on active and passive source seismic data from the same subsurface structure; performing wavefield separation on the time-aligned active and passive source seismic data to reconstruct the P-wave and S-wave fields of the active source and the passive source; performing active and passive source wavefield extrapolation based on the two-way wave equation; obtaining active and passive source PS-converted wave imaging results using cross-correlation imaging conditions; and performing weighted superposition and fusion to obtain the combined active and passive source imaging results. This disclosure leverages the high resolution advantage of active sources combined with the deep detection capability of passive sources, replacing the limitations of single-source detection and achieving high-precision deep reverse time migration imaging.

The invention relates to the technical field of optical three-dimensional reconstruction, in particular to a three-dimensional fingerprint microstructure reconstruction method and system based on illumination self-calibration and sparse integration, and the method comprises the following steps: constructing a multi-light-source imaging system, and arranging a standard spherical reflector in an imaging field of view to perform illumination direction self-calibration; performing multi-angle illumination acquisition on the surface of the finger to obtain a finger image sequence under multi-frame illumination variation; a reconstruction area of the finger image sequence is limited; carrying out vectorization solution on the pixel brightness change of the reconstruction region under the multi-illumination condition, and obtaining a global continuous normal gradient field based on the surface normal vector and reflectivity of each pixel; the normal gradient field is converted into a depth constraint equation, sparse matrix optimization and least square integral solving are adopted, and global consistent reconstruction of the depth map is achieved. According to the method, high-fidelity three-dimensional reconstruction of the finger surface microstructure is realized through an integrated technical framework of physical calibration, photometric solution and sparse integration.

The invention discloses a sensor array error evaluation method for magnetocardiogram source imaging, which relates to the technical field of biomedical signal analysis, and comprises the following steps: performing tissue segmentation and three-dimensional reconstruction on a CT image to generate a CT model; carrying out registration on the 3D scanning model and the CT model; error types existing in the information of the magnetocardiogram sensor array are set; simulating and generating a magnetocardiogram signal containing error influence; and evaluating the influence of the error on the source imaging performance. The method can systematically and comprehensively quantify the influence of crosstalk, gain error, sensitive axis angle error and position error on the imaging performance of the magnetocardiogram source and three core dimensions of positioning precision to construct a unified multi-dimensional evaluation system, overcomes the defect of lack of comprehensive evaluation standards in the prior art, can also provide priority guidance for error calibration of an MCG system, and improves the accuracy of the MCG system. And the imaging accuracy, the clinical availability and the application value are obviously improved.

The invention relates to the technical field of image processing and multi-source imaging data fusion, in particular to a multi-modal image diffusion fusion method based on imaging physical feature constraint. According to the technical scheme, the method comprises the following steps: acquiring data of a plurality of original images of the same target object in different imaging modes, and preprocessing the data of the plurality of original images to obtain a spatially aligned multi-mode image; according to the method, in the reverse diffusion sampling process of multi-modal image diffusion fusion, pixel-level constraint weights based on imaging physical characteristics are introduced, and spatial self-adaptive fusion updating control is achieved; updating is restrained in a structure boundary area to keep a geometric contour clear and stable; the specific modal response salient region is enhanced and updated to fully integrate detail information, the problem that structural integrity and detail richness are difficult to consider in a data scarce scene in a traditional method is effectively solved on the premise that a diffusion model does not need to be trained again, and the quality of a fused image is remarkably improved.

The invention relates to the technical field of biological magnetic signal detection and imaging, and discloses a thoracic conductor modeling and signal attenuation compensation method and system for magnetocardiogram imaging. The method comprises five steps of multi-modal data synchronous acquisition and registration, personalized thoracic conductor model construction, personalized magnetic field attenuation transfer matrix construction, signal inverse compensation and general high-precision source imaging. According to the method, the high-precision personalized thoracic conductor model is constructed to carry out front-end pre-compensation on the original magnetocardiogram signal, and the quasi ideal signal diagram with corrected individual conduction attenuation is generated, so that any subsequent standard source imaging algorithm works on the basis of fair and real signals, and the precision and consistency of final imaging are improved from a data source.

The invention relates to a high dynamic range sound source imaging method based on a double attention mechanism, and the method comprises the steps: receiving a space sound field signal through a microphone array, and processing the space sound field signal into a frequency domain signal; performing cross-spectrum matrix characteristic filtering processing on the frequency domain signal to obtain a complex frequency domain signal vector; performing adaptive enhancement on a real part and an imaginary part of the complex frequency domain signal vector by using a double attention mechanism; fusing the enhanced real part with the enhanced imaginary part to obtain an enhanced signal vector; and performing beam forming calculation by using the enhanced signal vector to generate an acoustic image. According to the invention, the real part attention module and the imaginary part attention module are introduced in parallel at the front end of beam imaging, and the amplitude and phase characteristics of the acoustic signal are subjected to adaptive weighted enhancement, so that the spatial information in the array signal is fully mined, the dynamic range of acoustic imaging and the robustness in a noise environment are significantly improved, and the method is suitable for wide application. And a better solution is provided for precise fault diagnosis and acoustic monitoring.

The present invention discloses a method and system for high-precision density inversion of gravity anomalies based on regular stable fast solution. [Solution] Based on the above source regularization solution, we propose using data containing spurious anomalies at the source imaging depth as boundary value conditions. Then, through the upper half-space solution of the first-class boundary value problem of Laplace's equation, we calculate the gravity anomaly on the ground, and perform a least-squares optimization iteration with the actual ground anomaly to obtain high-precision anomaly imaging data at the source depth without spurious anomalies caused by the Gibbs effect. This depth is used as the top interface of the source, and the top interface is divided into grid prisms to construct a source configuration. Density inversion is performed on each prism top surface in the frequency domain to obtain the density distribution of the source configuration. Because this algorithm is implemented in the frequency domain and the inversion is performed at a known source depth, the present invention provides a gravity density inversion method with high speed, high precision, and high resolution, and provides a new concept for solving gravity source density parameters.

The invention discloses an automatic multi-modal image registration method and system. The method comprises the following steps: initializing and preprocessing a registration image; extracting feature points of the registered image, and calculating descriptors; matching descriptors of the registered image pairs; calculating an affine matrix; and performing affine matrix processing on the to-be-registered image to obtain a registered image. According to the method, the registration problem of an endogenous imaging technology, a light field imaging technology, a tissue slicing technology and the like which cannot be solved in the prior art can be solved at the same time, fine adjustment is not needed for different modes, zero sample learning can be achieved, and the method can be suitable for imaging conditions of different scales from mesoscopic imaging to microscopic imaging and the like.

A frequency encoded source imaging system includes an EEG or MEG sensor array and a processing system for analyzing the signals from the sensor array in at least two different frequency bands, where the analysis is localized with respect to a three-dimensional grid corresponding to the portion of the human body. Alternately, a frequency encoded source imaging system includes an EEG or MEG sensor array and a processing system for analyzing the signals from the sensor array in a high-definition frequency band comprising frequencies greater than 70 Hz, where the analysis is localized with respect to a three-dimensional grid corresponding to the portion of the human body.

An airborne-particle detector includes a first emitter unit, a second emitter unit, and a photodetector. The first emitter unit includes a first light emitter and a first imaging element, that outputs a first incident beam propagating in a first direction toward a scattering region. The second emitter unit includes a second light emitter and a second imaging element, that outputs a second incident beam propagating toward the scattering region in a second direction substantially antiparallel to the first direction. the first imaging element images the first light emitter to a first image plane. The second imaging element images the second light emitter to a second image plane. The scattering region is between the first image plane and the second image plane. The photodetector detects scattered illumination from the scattering region.

Accurate concentration measurements can be performed even with low-concentration dispersions. [Solution] The dispersion concentration measurement system according to the present invention comprises a container 20 for containing the dispersion, a laser light source 10, an imaging device 30 that captures an image of the region where laser light 11 from the laser light source 10 is incident on the liquid in the container 20 and generates an image, and a processing device 40. The processing device 40 counts the number of bright spots based on a first image obtained by irradiating the container 20 with only the solvent and laser light 11, and counts the number of bright spots based on a second image obtained by irradiating the container 20 with the dispersion and laser light 11. The concentration of the dispersion is determined by subtracting the number of bright spots in the first image from the number of bright spots in the second image and dividing the result by the volume of the dispersion obtained by multiplying the imaging range of the imaging device 30 by the depth of field.

An endoscopic light source-imaging module including a substrate, an image sensor, and a light-emitting element is provided. The top surface of the substrate is provided with a cavity. The cavity has a first surface and a second surface neighboring each other and having a preset height drop therebetween. A first conductive route and a second conductive route of the substrate extend from the top surface penetrating through the substrate to a bottom surface. The image sensor is disposed on the first surface and is electrically connected to the first conductive route. The light-emitting element is disposed on the second surface, neighboring one side of the image sensor and electrically connected to the second conductive route. The present invention improves the image quality of the endoscope, reduces the module size, decreases the fabrication stages, increases the productivity, and lowers the cost.

A method includes segmenting a region of interest in an anatomical region in both a source imaging data and a destination imaging data, wherein different regions of the region of interest are labeled with different segmentation masks. The method includes selecting a region from the different regions from the source imaging data and spatially matching the region to a corresponding region in the destination imaging data. The method includes determining a spatial intersection between the region and the corresponding region. The method includes utilizing an intersection mask to crop a first portion of the region from the source imaging data and utilizing the intersection mask to remove a second portion of the destination imaging data in the corresponding region. The method includes adding the first portion of the region from the source imaging data into the destination imaging data where the second portion was removed.

This invention discloses a method for repairing adhesive coating defects on a mask substrate, belonging to the field of mask substrate adhesive coating repair technology. It aims to solve the problem of poor repair results for defects in the adhesive coating area of ​​a mask substrate. This invention utilizes differential enhancement to strengthen defect contrast. A machine learning model accurately classifies defect types and attributes through geometric, textural, and optical features, significantly improving the comprehensiveness and accuracy of defect identification and providing a reliable basis for repair. It employs multi-band light source imaging and differential enhancement fusion technology, combined with a machine learning classification model, to achieve comprehensive defect identification and accurate classification. A full-process data traceability and visualization storage mechanism is established, integrating original defect data, repair process parameters, and finished product information, standardizing data formats, and presenting them visually.

The invention discloses a near monochromatic light source color-mixed white light achromatic high-quality imaging method, and belongs to the technical field of optical imaging and image processing. Comprising the following steps: S1, configuring a red, green and blue near-monochromatic mixed white light source; s2, collecting standard color card data and white standard area reference data under a xenon lamp and mixed-color white light; s3, correcting color deviation in mixed color white light source imaging based on the color card data and the reference data; s4, by taking the green channel as a reference, adjusting and synchronously correcting the position offset and intensity calibration of the red and blue channels; and S5, based on a Sobel operator, enhancing the image contrast. By adopting the near monochromatic light source mixed color white light achromatic high-quality imaging method, the problems of near monochromatic light imaging chromatic aberration and channel position offset are solved, and achromatic, high-definition and high-color-rendition high-quality imaging is realized.

The invention belongs to the technical field of deep mineral resource development, and provides a roadway front disaster source excavation-following sound wave fine detection method and system, multiple groups of detection data in the excavation process are obtained, and the detection data comprise seismic source vibration data and excavation-following sound wave data; the method comprises the following steps: preprocessing detection data to obtain a single-channel seismic record, carrying out delay calculation and beam forming directional superposition, optimizing a reflection coefficient sequence, and carrying out multiple times of beam forming directional superposition through combination; and establishing a geologic model based on the superposed multi-component wave field data, calculating wave velocity distribution by using a tomography algorithm, and carrying out disaster source imaging by using the calculated wave velocity distribution as an initial model and using a decoupling reverse time migration method. According to the invention, effective suppression of interference signals is realized, and spatial positioning and imaging of disaster sources are realized by using a decoupling elastic reverse time migration imaging method.

The present disclosure provides a coordinate calibration device and method based on a distributed ray source imaging system. The coordinate calibration device comprises a ray source and a detector. The ray source is configured to emit X-rays. The detector comprises a detection part and a marking part. The detection part is configured to be disposed within a target area; the detection part and the ray source are respectively arranged on two sides of an object to be measured; and the detection part is configured to receive the X-rays. The marking part is located between the detection part and the ray source; and the relative position of the marking part and the detection part is fixed, wherein at least two marking points are spaced apart on the marking part, the at least two marking points are configured to perform coordinate calibration on X-ray imaging, and the coordinate calibration and the X-ray imaging are performed using the same data. The known parameters on the marking part are used to correct the relative coordinates between the ray source and the detector, and the calculation of the relative coordinates between the ray source and the detector is assisted by relying on the mechanical positioning of the system, thereby reducing the calculation amount of coordinate estimation, improving the relative position accuracy or realizing real-time position calibration, and avoiding secondary capturing, and thus realizing convenient three-dimensional imaging.

An airborne-particle detector includes a first emitter unit, a second emitter unit, and a photodetector. The first emitter unit includes a first light emitter and a first imaging element, that outputs a first incident beam propagating in a first direction toward a scattering region. The second emitter unit includes a second light emitter and a second imaging element, that outputs a second incident beam propagating toward the scattering region in a second direction substantially antiparallel to the first direction. the first imaging element images the first light emitter to a first image plane. The second imaging element images the second light emitter to a second image plane. The scattering region is between the first image plane and the second image plane. The photodetector detects scattered illumination from the scattering region.

The invention relates to a nuclear pipeline radioactive decontamination system and method. The system comprises a decontamination module, an imaging data acquisition module, an autonomous crawling mechanism and a control module, the decontamination module is used for generating a decontamination field; the imaging data acquisition module is used for acquiring multi-source imaging data; the autonomous crawling mechanism is used for carrying the decontamination module to move on the pipeline; the control module is used for executing the following steps: constructing a pipeline pollutant distribution model according to the multi-source imaging data; pollutant position data and a decontamination path are generated according to the pipeline pollutant distribution model; controlling the autonomous crawling mechanism to carry the decontamination module to reach the hot spot according to the decontamination path; and when the autonomous crawling mechanism arrives at the hot spot every time, the decontamination module is controlled to generate a decontamination field, and the decontamination module is controlled to work in real time according to the latest acquired multi-source imaging data. According to the invention, hot spot pollutants are automatically and intelligently removed, and the decontamination efficiency and thoroughness are improved.

This invention discloses an asynchronous measurement technique for 3D imaging of multi-point, non-planar low-frequency sound sources. It utilizes two 64-channel 3D spherical arrays for asynchronous measurement, proposing a unique dual-cylindrical spiral ascent and rotation movement method to achieve 3D point source imaging within low-frequency sound sources. This method differs from previous directional methods. It employs an asynchronous measurement technique involving the centers of two spherical arrays following a designed dual-cylindrical spiral parallel ascent trajectory and the array's rotation, applied to 3D imaging of multi-point, non-planar low-frequency sound sources. This results in a larger and denser array. To a certain extent, the asynchronous measurement method combining the dual-cylindrical spiral trajectory and rotation further improves the density of synthesized microphones compared to cylindrical trajectory asynchronous measurement methods and spherical array center revolution-rotation asynchronous measurement methods. The method is stable and efficient.