805 results about "Spectral response" patented technology

The invention discloses a visual detection system and method for tiny flaws of industrial products, and belongs to the technical field of product detection, multi-source image data of a target industrial product under multiple detection angles and illumination conditions are acquired, and an image information matrix is established; performing region segmentation and texture enhancement on the image, and extracting local texture direction inconsistency parameters; carrying out normalization analysis on the pixel ratio under different spectrum channels, and calculating a multispectral reflectance ratio abnormal index; constructing a deep convolution recognition model; reasoning the image by using the model, and outputting a defect judgment result and a confidence score; judging whether the area is a flaw area based on a dynamic threshold mechanism, and outputting a detection report containing flaw position information and a visual heat map; according to the method, multi-dimensional fusion identification of texture structure disturbance and spectral response abnormity is realized, the micro defect identification precision is effectively improved, and the method has high robustness, automation and engineering practicability and is suitable for high-precision quality control requirements of various industrial scenes.

The invention relates to an optical film detection method, device and equipment based on image processing. The method comprises the following steps: collecting multiple frames of images of a multilayer optical film under different illumination conditions, and carrying out preprocessing and characteristic value calculation on the multiple frames of images to obtain a characteristic value response matrix; calculating an optimal weight coefficient of each frame of image according to the feature value response matrix, and performing multi-frame image feature fusion to obtain integrated feature representation; performing multi-scale defect feature extraction on the integrated feature representation to obtain a defect candidate region; spectral response characteristics are extracted based on the defect candidate area, matching degree calculation is carried out on the spectral response characteristics and a preset wavelength-film thickness mapping relation matrix, and a multilayer film defect distribution diagram is obtained; and performing autoregression prediction and processing control parameter optimization on the multilayer film defect distribution diagram to obtain a closed-loop control scheme. According to the invention, accurate identification and classification of different film layer defects are realized, and closed-loop control of defect detection results and manufacturing parameter optimization is further realized.

The invention belongs to the technical field of intelligent lighting, and discloses an intelligent adjustment method and system for the spectrum of a quantum dot light-emitting lamp. The objective of the invention is to solve the problem that an existing lighting system cannot meet personalized healthy lighting requirements. The method comprises the following steps: firstly, acquiring user biological rhythm, environment spectrum, use scene, user preference and physiological health data through multi-dimensional data acquisition, and constructing a feature data set; then human factor optical feature extraction and cross-situation demand analysis are carried out, and a spectral response model is established; carrying out quantum dot material photoelectric characteristic mapping and spectrum synthesis modeling based on the model, and determining a luminescence parameter space; constructing a spectrum optimization model, performing multi-objective optimization by comprehensively considering visual comfort, energy efficiency and health influence, and generating a dynamic spectrum regulation and control strategy; closed-loop verification and adaptive optimization are carried out based on real-time physiological feedback, and an intelligent spectrum adjustment scheme is formed. According to the invention, the advantage of spectrum adjustability of the quantum dot material is fully exerted, and real personalized intelligent illumination is realized.

A method for quality inspection of an etching paste material based on a spectral response difference, including: identifying a position of density mutation boundary through spectral collection and density gradient analysis. Applying a specific frequency beam to obtain the resonance response parameter, generating stress field reconstruction data. Performing a reverse optical tracking to obtain a defect formation path, generating degradation prediction data. Establishing a self-organizing optical monitoring grid, to form a hierarchical spectral fingerprint library. Constructing a multi-point linked defect blocking network, to form an interconnected optical energy field. Monitoring a cooperative response to obtain network stability data, Identifying abnormal position coordinates based on a material quality grade and the network stability data, obtaining the abnormal position coordinates. Performing a phase adjustment to obtain a phase difference spectral set, conducting a phase comparison marking on the abnormal position coordinates, completing the quality inspection of the etching paste material.

The invention relates to an intelligent dimming method and device for a multispectral light source and a storage medium, and the method comprises the steps: obtaining the spectral parameters and environment illumination data of the multispectral light source, carrying out the analysis processing of the spectral parameters based on the environment illumination data, and obtaining the corresponding target spectral information; acquiring real-time output data of the multispectral light source, and performing association processing on the real-time output data and the target spectral information to obtain a corresponding real-time spectral group; acquiring illumination feedback data of the multispectral light source, and performing spectral prediction on the target spectral information to obtain corresponding spectral adjustment information; performing dimming planning analysis on the real-time spectrum group and the spectrum adjustment information to obtain a corresponding initial light source control scheme; performing spectrum identification on the illumination feedback data to obtain corresponding characteristic spectrum information; and performing dimming optimization on the initial light source control scheme according to the characteristic spectral response parameters to obtain a corresponding global dimming strategy. According to the invention, global optimization of the system can be realized through optimization and adjustment of the characteristic spectral response parameters.

The invention relates to the technical field of remote sensing surveying and mapping, in particular to a terrain recognition and three-dimensional reconstruction method based on a remote sensing surveying and mapping image, which comprises the following steps of: recognizing and selecting a key spectral band based on a remote sensing image, adjusting the configuration of a spectral filter, extracting key terrain data according to configuration data, and analyzing terrain change by utilizing terrain feature data. And recording related wave bands and positions, forming a comparison table, and combining natural colors and surface texture analysis to generate a three-dimensional model of the terrain. According to the method, the key spectrum sections are screened by adopting the preferable waveband index, the specificity and efficiency of data acquisition are improved, the spectral response section is accurately adjusted, it is ensured that a spectral region with remarkable earth surface reflection characteristics is focused on, and the practical value of spectral data is improved; the spectral configuration data optimizes the response performance of the sensor so that the data collected from the terrain is more sensitive and accurate.

The invention belongs to the technical field of all-dielectric metamaterial optical devices and machine learning, and discloses an all-dielectric metasurface target spectral response reverse design method based on deep learning. And realizing efficient prediction of the transmission spectrum by using a convolutional neural network-recurrent neural network-residual network architecture. A fitness function is designed, and a machinable structure is generated by aiming at single-peak and multi-peak target wavelength optimization and combining a linear and shape optimization strategy. The method breaks through the limitation of spectrum dependence and fixed structure type of the traditional reverse design, realizes on-demand design, and remarkably improves the design efficiency and processing compatibility of the integrated photonic device.

The invention relates to the technical field of spectral analysis, and discloses a method and a system for detecting the concentration of trace metal ions. The method comprises the following steps: acquiring original spectral response data of an electronic smoke sample; carrying out signal separation by utilizing a frequency domain feature extraction technology to obtain an initial spectrum data set; performing background noise filtering and baseline drift correction on the initial data to obtain a refined spectrum data set; constructing a concentration-wavelength mapping relation through absorption peak positioning and characteristic wave band screening on the basis of the refined spectrum data set; carrying out continuous time sequence sampling on the samples based on the mapping relation to generate a concentration dynamic change data set; analyzing a concentration fluctuation rule and an abnormal point in the dynamic data, and generating concentration risk assessment data; and finally outputting a time sequence detection file. According to the method, high-precision dynamic monitoring and intelligent risk assessment of trace metal ion concentration are realized, interference is effectively inhibited, and sensitivity and early warning capability are improved.

The invention discloses a liquid medicine foreign matter detection method and system based on machine vision, and the method comprises the steps: obtaining multiband spectral data of a liquid medicine sample, and carrying out the normalization processing to generate a liquid medicine background standard spectral feature template; comparing the refractive index spectral characteristics of the template and the foreign matter-containing liquid medicine, and recording the surface roughness scattering mode and polarized light reflection angle change data of a foreign matter area; calculating a spectrum peak displacement quantized value according to the polarized light data, and extracting foreign matter edge spectrum gradient information in combination with a threshold value; calculating a transparency spectral attenuation coefficient based on the edge gradient information, and obtaining spectral contrast enhancement factors of different foreign matters in combination with the spectral response characteristic data; and if the enhancement factor does not reach the standard, adjusting the spectrum correction parameter and recalculating, fusing the scattering mode and the multi-angle incident spectrum response result to carry out consistency verification, and obtaining a final identification result containing the foreign matter material type and the danger level. The method can improve the drug detection accuracy and guarantee the drug quality safety.

The invention belongs to the technical field of image recognition, and discloses a multi-modal road change detection method based on reinforcement learning optimization, and the method specifically comprises the steps: S1, designing normative natural language Prompt input and semantic analysis; s2, carrying out text semantic vectorization; s3, inputting and preprocessing road scene multi-modal data; s4, road image feature embedding and multi-modal association are carried out; s5, performing multi-modal feature alignment and dynamic fusion; s6, carrying out parameter optimization and online simulation verification on the detection model; and S7, performing multi-target reinforcement learning optimization and scene verification. According to the method, three-dimensional space structure characteristics, spectral response characteristics and long-time-sequence observation data can be cooperatively processed, adaptive optimization of detection model parameters can be achieved through reinforcement learning, the problems that a traditional method is poor in characteristic coupling and poor in dynamic adaptive capacity in a complex scene are effectively solved, and the method is suitable for large-scale popularization and application. And a novel road change detection normal form with innovativeness and practical application value is provided for the fields of urban governance and intelligent transportation.

The invention provides a molten pool temperature field in-situ monitoring method and system based on multi-view light field imaging, and the method employs a light field camera multi-view system, obtains molten pool images of R, G and B channels through building a light field sub-aperture Bayer model, and calibrates the relative spectral responsivity of a light field camera and the proportion of dual-wavelength intensity under a coaxial temperature measurement system. Molten pool images of two channels are selected from the molten pool images of the R channel, the G channel and the B channel, calibration parameters are combined, and a molten pool temperature field is derived through a dual-wavelength temperature measurement method. A blackbody furnace is adopted to calibrate a multi-view light field temperature measurement system, and the error of a monitored temperature field is kept below 3%. The method simplifies the monitoring process, improves the temperature measurement precision, has a wide temperature range and low complexity, can perform in-situ monitoring on the high-temperature metal molten pool, and has a wide application prospect in the field of additive manufacturing.

The invention relates to the technical field of image recognition, and discloses a surface dirty image recognition method applied to a window-cleaning robot and a related device, and the method comprises the steps: carrying out the preprocessing of a multispectral image collected by the window-cleaning robot, and obtaining a preprocessed image, meanwhile, integrating a side wheel collision signal and a falling detection signal of the window cleaning robot to obtain a window boundary safety map; performing dynamic weighted mixed attention processing and convolution multi-scale stripe pooling processing under edge constraint to obtain an enhanced feature map; edge security perception smudginess segmentation is carried out on the enhanced feature map to obtain a smudginess segmentation result and an edge security region identifier, and a cleaning strategy mapping table for smudginess at different positions is established; according to the method, a dirt density thermodynamic diagram is generated, a path planning algorithm is executed, and a safe cleaning track is generated, so that stable spectral response can be obtained under various illumination conditions, and the stability and reliability of dirt recognition in different environments are ensured.

The invention relates to the technical field of photovoltaic power generation, in particular to a photovoltaic effective solar irradiance measurement method, which comprises the following steps of: converting optical power into irradiance and tracing the irradiance to an SI unit system by taking trap detection transmitted by a low-temperature radiation meter as an optical power standard device and combining a precise diaphragm; respectively collecting the output voltage of the total radiometer, the output voltage of the monitoring radiometer, the zenith angle of the total radiometer in the non-shielding state and the solar irradiance output by the absolute radiometer when the total radiometer is in the shielding state and the non-shielding state, and calibrating the total radiometer; angle response, temperature response, sensitivity linear response and spectral response data of the total radiometer and the photovoltaic module under different influence parameters are obtained, a correction coefficient set is obtained through fitting and used for conducting temperature, angle, irradiance linearity and spectral mismatch correction on the irradiance measured by the total radiometer, photovoltaic effective solar irradiance data are obtained, and the photovoltaic effective solar irradiance data are obtained. Accurate measurement of the solar irradiance for photovoltaic power generation is realized.

The invention discloses an automatic pixel calibration method for a Micro LED display screen, and the method comprises the steps: carrying out the multi-dimensional detection of the real-time brightness, color and temperature of each pixel through a high-precision multispectral sensor, obtaining the actual optical characteristics of each pixel, including but not limited to the parameters of brightness, color temperature, color difference, spectral response and the like, and carrying out the detection of the pixels; and deviation analysis: analyzing the detection data of each pixel through a deep learning algorithm, identifying brightness, color and current deviation, determining the correction demand of each pixel, and performing quantitative analysis on the deviation of each pixel. A high-precision multispectral sensor and a deep learning algorithm are introduced, so that the detection and calibration process of each pixel is more accurate. By dynamically adjusting the current output, the problems of pixel aging, uneven brightness, chromatic aberration and the like can be solved, so that the stability and consistency of the display effect are remarkably improved, and the service life of the Micro LED display screen is prolonged.

The invention discloses a non-ideal path radiation infrared hyperspectral remote sensing instrument non-linear correction method, aiming at the situation that partial radiation of a stationary orbit GIIRS enters a detector in a non-ideal path in a complex thermal environment, and initial correction is carried out on an original spectrum of a detection target based on a responsivity non-linear correction algorithm during radiometric calibration; during in-orbit operation, a linear calibration model is constructed through a two-point calibration algorithm, and the spectral response rate of the detector and the theoretical radiation spectrum of an observation target are obtained; based on a nonlinear correction spectral response rate and a theoretical radiation spectrum of an observation target, in combination with non-ideal radiation superposed by an original spectrum of the detection target and a fixed error which cannot be corrected by two-point calibration, a function relationship between radiation abutting against a detector in a non-ideal way and the original spectrum of the detection target is constructed; the non-ideal path radiation correction coefficient is obtained, non-linear correction is further carried out, non-ideal radiation errors which cannot be corrected by response rate non-linear correction are eliminated, and the radiation calibration precision of the target black body is improved.

The invention discloses a hyper-spectral imaging chip, device and system based on an adjustable and reconfigurable metasurface, the chip comprises a metasurface unit array, a metasurface reconstruction module, a metasurface adjustment module, a CMOS image sensor and a spectrum reconstruction and identification module, the metasurface unit array comprises a plurality of metasurface units arranged on a silicon layer; the metasurface reconstruction module is used for adjusting the number of metasurface units included in the reconfigurable metasurface unit array; the metasurface adjusting module is used for being connected with the silicon layer of the metasurface unit array through a wire and changing the spectral response of the metasurface unit by adjusting the voltage of the wire; the CMOS image sensor is used for detecting optical signals modulated by the reconfigurable metasurface unit array; and the spectrum reconstruction and identification module is used for performing hyper-spectrum reconstruction and imaging according to the optical signal detected by the CMOS image sensor. The system is adjustable in spectral response, and has ultrahigh spectral resolution, real-time dynamic monitoring capability and adaptive imaging capability.

The invention belongs to the field of astronomical telescopes, and particularly relates to a large-aperture spliced telescope adjusting device and method, and the method comprises the steps: starting a light source module, providing a far-field illumination light beam for a spliced primary mirror, and carrying out the confocal adjustment of each sub-mirror through an adjusting mechanism according to the far-field illumination light beam; the light source switching module is used for providing a near-field illumination light beam for the spliced primary mirror, and the near-field illumination light beam is split into two separated sub light beams by the pyramid mirror after penetrating through a splicing seam of the spliced primary mirror; performing dispersion on all the sub-beams through a dispersion prism, and converging the dispersed sub-beams through an achromatic lens to form dispersion stripes; the phase difference of the dispersion fringes is extracted through the camera, and co-phase adjustment is carried out on the sub-mirrors through the adjusting mechanism according to the phase difference of the dispersion fringes. According to the invention, high-precision and high-flux spectral response calibration and co-phase detection of the large-aperture spliced telescope can be realized, so that reliable technical support is provided for construction and operation of a next-generation giant astronomical telescope.

The invention relates to the technical field of optical detection, and provides a relative spectral responsivity adjustable optical detector and a use method thereof, the detector comprises an acquisition module, a dispersion module, an adjustment module, a collection module and a detection module which are sequentially arranged along an optical path; the acquisition module is used for acquiring incident light and converting the incident light into divergent, converged or parallel light beams; the dispersion module is used for carrying out dispersion on the light beams output by the acquisition module and carrying out spatial separation on the multi-color light beams according to wavelengths to form dispersion light bands; the adjusting module can dynamically adjust the reflectivity or transmittance of the region corresponding to each wavelength; the collection module is used for converging the adjusted dispersion light band again and transmitting the dispersion light band to the detection module; the detection module is used for receiving the converged light beams and converting the light beams into electric signals. According to the optical detector with the adjustable relative spectral responsivity, by introducing the dispersion module and the adjusting module, light intensity distribution modulation of a dispersion light band is achieved, and the relative spectral responsivity of the detector can be adjusted according to needs.

The invention discloses a visible light communication data transmission method based on dynamic modulation, and particularly relates to the field of visible light technology communication. The method comprises the following steps: performing nonlinear dynamic feature extraction on an actual light intensity signal emitted by a light emitting diode to generate a spectral response feature set; performing segmented analysis on the frequency domain distortion evolution trend based on the frequency spectrum response feature set to obtain a plurality of frequency spectrum distortion subintervals; performing local modulation parameter optimization on each spectrum distortion subinterval to obtain a dynamic local modulation parameter set; mapping the dynamic local modulation parameter set into a modulation driving strategy sequence, and generating a dynamic modulation waveform signal sequence; performing detection and time-frequency feature extraction on the dynamic modulation waveform signal sequence to obtain a target signal sequence after noise suppression; and the target signal sequence is demodulated, complete data is recovered, visible light communication data transmission is completed, and the optical communication signal quality and the data recovery capability in a complex modulation environment are effectively improved.

The invention discloses an ultrafast motion sensing floating gate transistor based on Van der Waals heterojunction and application thereof. The floating gate transistor comprises a back gate substrate, a Van der Waals heterojunction channel layer, a source electrode and a drain electrode, the source electrode and the drain electrode are arranged on the two sides of the channel layer, the back gate substrate is heavily doped silicon, the surface of the heavily doped silicon is covered with hafnium oxide / aluminum oxide / hafnium oxide (HfO2 / Al2O3 / HfO2) used for nonvolatile light storage, and the Van der Waals heterojunction channel layer is composed of bismuth oxygen selenium-palladium selenide nanosheets used for sensing. The floating gate transistor disclosed by the invention has the capability of quickly responding to an ultraviolet-near infrared wide spectrum and non-volatile storage of light at the same time, and the sensitive spectral response range and responsivity of the photoelectric detector can be effectively improved, so that the integration of dynamic target optical signals in devices in a space domain and a time domain is realized.

The invention provides a food pollution detection method based on multi-wavelength spectrophotometry, and the method comprises the steps: transmitting light in a series of wavelength ranges to a food sample through a tunable multi-wavelength light source system, generating spectral response, collecting the spectral response through a high-resolution spectrometer, and forming a multi-dimensional spectral image, a deep learning algorithm is used for analyzing, identifying and distinguishing subtle spectral differences between natural components and potential pollutants in a food sample, a preliminary identification result is obtained, a self-adaptive wavelength selection mechanism is implemented, wavelength output of a light source is dynamically adjusted, spectral response data is obtained, and the spectral response data is compared with a preset food safety standard database. According to the technical scheme provided by the invention, natural components and potential pollutants in a food sample are efficiently and accurately recognized, and the sensitivity, specificity and accuracy of pollutant detection are remarkably improved.

The invention provides a consistency correction method and device based on a multi-source satellite inversion water color index, and the method comprises the steps: converting the surface reflectance of a multi-source satellite sensor of a target water area into remote sensing reflectance, and carrying out the water body range extraction of the multi-source satellite sensor, so as to determine the water body range, carrying out multi-class interference pixel removal on the image of the surface reflectance in the water body range to obtain effective remote sensing reflectance; calculating a chromaticity angle inverted by the multi-source satellite sensor based on the effective remote sensing reflectivity and a CIE chromaticity system; performing spectral response correction on the chromaticity angle inverted by the multi-source satellite sensor based on a polynomial spectral correction model constructed by the water optical simulation data set; performing system deviation correction on the chromaticity angle of the multi-source satellite sensor after spectral response correction by a cross calibration correction model established based on the synchronous observation data of the multi-source satellite sensor; and determining the water color index of the target water area based on the chromaticity angle after system deviation correction.

The invention provides a photovoltaic module damage intelligent detection method and system based on an unmanned aerial vehicle image, and relates to the technical field of unmanned aerial vehicle image.An unmanned aerial vehicle collects a multi-angle high-altitude image of a photovoltaic module array according to a predetermined path and records geographic position information; image splicing and overlap region correction are carried out by using the information to form a high-resolution panoramic image; in combination with a pre-constructed three-dimensional topological structure model, identifying and marking photovoltaic modules in the panorama, and generating a module distribution diagram; by analyzing the actual spectral response characteristics of each component, comparing standard data in a material science database, and screening suspected damage areas; applying an adaptive threshold algorithm and morphological operation to the areas to generate a feature map; and integrating real-time environmental factors and historical performance changes, extracting target features influencing the performance reduction of the photovoltaic module, predicting a damage state, and finally generating a detection report. According to the invention, the detection efficiency of the photovoltaic module is improved.

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 discloses a multi-spectral imaging system and method in a single-pixel type ultraviolet-visible-infrared wide spectral range. The system comprises a light source module, a modulation device, a lens group, a multi-spectral detection module, a multi-channel data acquisition module and a data processing module, according to the invention, a plurality of narrow-band detectors with different spectral responses are introduced into the multispectral detection module, so that additional light splitting devices and light filtering devices are avoided, parameters such as view fields, view angles and pixel numbers of images obtained by using different narrow-band detectors are completely the same, the problem of image registration does not exist, and data analysis and image fusion are facilitated; in addition, the size of the narrow-band detector is basically not limited and can reach the centimeter magnitude, and the imaging capability is improved under the condition of weak light. The multispectral imaging system provided by the invention has the characteristics of single-pixel imaging, large number of spectrums, wide spectral range, high imaging speed, good temporal-spatial resolution and small size.

The invention discloses a liquid crystal display brightness adjusting system and method based on ambient light perception, and the system comprises a high-precision ambient light sensor which obtains the ambient light illuminance and color temperature data in real time; the analog-to-digital converter is used for converting the analog optical signal into a digital signal; an embedded microcontroller; the temperature sensor is tightly attached to the liquid crystal panel backlight unit; and the control input end of the liquid crystal driving chip is connected with the driving signal output end of the embedded microcontroller through a serial peripheral interface bus. The technical normal form of a liquid crystal display dimming system is fundamentally reconstructed: in a physical layer, photoelectric signals and human eye spectral response offset are corrected through a spectral separation mechanism, a carrier recombination effect is inhibited based on a thermodynamic equation, and the physical authenticity of brightness output is ensured; in a control layer, a motion state compensation model and a spatial topology perception algorithm are constructed, and brightness space-time consistency control in a dynamic scene is realized.

The invention provides a super-lens reverse design method based on a selective dual-channel perception fusion network, and the method comprises the steps: obtaining a picture-phase spectrum data set through obtaining K pairs of original images and corresponding original phase spectrums; inputting the data to an adaptive difference frequency feature extraction network ADFFNet; inputting a selective non-common feature interaction network SFIFNet to respectively obtain image frequency features and spectral frequency features; the fusion reconstruction features of the image and the fusion reconstruction features of the spectrum are obtained; obtaining a picture generation result and a spectrum generation result; according to the method, the non-common frequency characteristics between the image and the corresponding spectrum can be deeply mined and deeply fused, the mapping accuracy between the image and the corresponding spectrum response can be improved, and the generation accuracy and efficiency of the image and the spectrum can be improved.

The invention relates to the technical field of image recognition, in particular to an unmanned aerial vehicle tracking system and method based on image recognition, and the system comprises a spectrum optimization module, a trajectory analysis module, a form adjustment module, a flight anomaly detection module and a tracking optimization module. According to the method, the brightness information of the ambient light and the reflected light of the unmanned aerial vehicle is finely analyzed and the spectral response of the image is adjusted, so that the image definition is greatly improved, the unmanned aerial vehicle can be accurately identified under various illumination conditions, and the flight path of the unmanned aerial vehicle is calculated in real time by accurately analyzing the image bounding box and timestamp information of the unmanned aerial vehicle. According to the method and the system, the tracking process is ensured to be continuous and accurate, any form change is effectively captured by continuously monitoring the form of the unmanned aerial vehicle in continuous image frames, the behavior mode change of the unmanned aerial vehicle is responded in time, and in the aspect of flight abnormity monitoring, behaviors inconsistent with a conventional flight mode can be accurately analyzed, and potential security threats can be identified in time.

The invention discloses a depth and color fused true color three-dimensional point cloud acquisition method and system, and the method comprises the steps: setting a plurality of lasers to emit specific spectrum laser, enabling the specific spectrum laser to be reflected by the surface of an object, and filtering the specific spectrum laser through a narrow-band optical filter of a corresponding wave band, thereby enabling a corresponding sensor to only receive a single-spectrum laser line emitted by a corresponding laser emitter. A laser center point position and an intensity response value are extracted through a sub-pixel-level laser line refinement technology; calibrating the unified measurement coordinate system through sensor pose calibration; according to the light transmittance of an optical filter, spectral response characteristics of an image sensor and the like, correcting and compensating the intensity response value, calculating a compensation factor to obtain a color value of a measurement point, fusing a three-dimensional coordinate with corrected color information, outputting true color point cloud data, and presenting depth and color information of an object at the same time. The three-dimensional information and the color information of the object are synchronously obtained, so that the measurement data contain rich spectral characteristics.

The invention relates to the technical field of photoelectric detectors, and discloses an infrared photoelectric detector which comprises a bottom layer, a heterojunction and a top layer which are sequentially stacked from bottom to top, the bottom layer is used for being electrically connected with a first electrode, the top layer is used for being electrically connected with a second electrode, the heterojunction at least partially covers the bottom layer, and the top layer is used for being electrically connected with a second electrode. The top layer at least partially covers the heterojunction, the top layer at least partially has light transmittance, and the heterojunction comprises a narrow band gap material layer. By means of the mode, the infrared photoelectric detector can achieve infrared detection which does not need complex refrigeration equipment and is high in response speed, wide in polarization response and spectral response range and high in stability.