1063 results about "Surface reflection" patented technology

The invention provides an aluminum alloy surface oxidation spot defect identification method and device based on machine vision, and relates to the field of intelligent manufacturing and industrial automation, and the method comprises the steps: obtaining an aluminum alloy surface color image, and carrying out the preprocessing of the image, so as to extract a brightness component image; self-adaptive threshold segmentation of local contrast enhancement is carried out on the brightness component image, a defect area binary mask is generated, morphological connected domains are extracted according to the mask, and three basic feature indexes of the area pixel value, the contour Fourier descriptor complexity and the area gray scale standard deviation contrast of each connected domain are calculated; and extracting and marking a connected domain boundary, verifying a boundary closed topological structure, and dynamically generating a curvature-driven self-adaptive sampling point through multi-scale B-spline curvature extreme value detection. Through optical-algorithm-process three-level collaborative innovation, the curved surface reflection false alarm rate is reduced, the pinhole detection rate is increased, and the boundary precision is + / -0.2 pixel.

The invention discloses an egg surface microcrack detection system and method based on image analysis, and relates to the field of surface defect nondestructive detection.The method comprises the steps that a process identification interface module obtains a processing process identifier of an egg in real time; the multi-angle annular light source module is provided with a multi-band annular light source array comprising visible light and near-infrared LED lamp beads which are independently controlled, a polaroid group and a beam splitter prism are integrated, and visible light polarization images and near-infrared polarization images on the surfaces of the eggs are synchronously collected; the thermal excitation enhancement unit obtains a thermal infrared image; the process filtering module extracts the axial elongation of the mechanical stress microcrack after graded transportation, and calculates the mesh fractal dimension of the thermal stress microcrack after UV disinfection; the multi-modal feature fusion module generates a dual-channel crack probability graph; and the dynamic feedback control module outputs a micro-crack risk grade and adjusts the rotating speed of the objective table and the light source intensity. The method has the advantages that accurate judgment of mechanical and thermal stress cracks is realized, and curved surface reflection interference is broken through.

The invention provides an aluminum film sealing defect real-time detection method and system based on multi-algorithm fusion, and relates to the technical field of intelligent manufacturing, and the method comprises the steps: triggering an industrial camera at a detection station to collect an original image of a pesticide aluminum film sealing on a conveyor belt; performing adaptive equalization operation on the original image through pixel brightness distribution data, eliminating light fluctuation and surface reflection interference, and outputting a standardized image; three types of defect detection are synchronously executed based on the standardized image, a dynamic threshold segmentation algorithm is combined with local area brightness analysis to detect edge damage, a contour extraction algorithm is adopted to calculate bottleneck center offset to recognize seal offset, wrinkle defects are recognized based on a surface texture feature analysis algorithm, and a primary detection result is output. The aluminum film sealing defect detection method is based on multi-algorithm fusion, has strong anti-interference capability, real-time detection performance and data traceability, and provides an efficient and reliable automatic solution for aluminum film sealing quality management and control.

The invention discloses a chip surface defect visual detection method and system, and the method comprises the steps: carrying out the high-sensitivity imaging through the dynamic adaptation of a quantum imaging enhancement module to the surface reflectivity, and achieving the sparse efficient processing of a defect signal through the combination of event-driven vision and a pulse neural network; based on a risk thermodynamic diagram generated in real time, intelligently scheduling detection precision and speed resources, and utilizing multi-modal feature decoupling and a federal knowledge graph to accurately associate defects and process roots; the digital twinning module synchronously predicts a defect evolution path and drives online adjustment and optimization of process parameters, and meanwhile the dynamic compensation module corrects optical defocus in real time. According to the invention, full-detection coverage of nanoscale defects is realized, a defect transfer chain is actively blocked while the detection efficiency is improved, and the chip manufacturing yield and reliability are remarkably improved.

The invention discloses a machine vision-based intelligent detection method for steel galvanized surface defects, which comprises the following steps: S1, acquiring and preprocessing a steel galvanized surface image to obtain a standardized image; s2, constructing a specular reflection probability graph according to the brightness distribution and the gradient magnitude, and calculating a reflection intensity value; s3, calculating a structure tensor matrix, determining a main direction angle and an anisotropic consistency coefficient, and generating a direction feature matrix; s4, establishing a multi-scale direction adaptive phase kernel function, and performing phase modulation in a frequency domain by adopting an improved phase stretching transformation algorithm; s5, inverse Fourier transform is executed, and a phase response matrix is extracted; s6, performing weighted fusion to obtain a comprehensive phase response diagram; and S7, setting a threshold value according to the noise variance and the statistical characteristics, executing binarization and morphological processing, and outputting a defect region and boundary coordinates. According to the invention, high-precision identification and boundary positioning of steel galvanized surface defects are realized.

A visual defect detection method, device, medium and product relate to the field of visual detection, and the method comprises the following steps: firstly, recording brightness changes of pixel points in different illumination directions by constructing an illumination response matrix, and establishing a complete mapping of surface reflection characteristics; secondly, performing joint calculation by using the light source direction matrix and the illumination response matrix to obtain normal vector data and reflectivity data, and representing spatial geometric features and material optical features of the surface respectively; thirdly, calculating a gradient feature map, a curvature feature map and a deformation feature map based on the normal vector data, generating a reflectivity map by using the reflectivity data, and forming a multi-dimensional feature representation system; and finally, in a defect detection stage, a strategy of combining gradient feature pre-screening with multi-feature verification is adopted, and final judgment is carried out by calculating a comprehensive defect feature value, so that the technical problem of insufficient micro defect detection precision of a visual detection method in the prior art is solved.

The invention relates to the technical field of image compensation, in particular to a reflection compensation method based on image processing, and provides the following scheme: acquiring an environment panoramic image by using a panoramic camera to establish a scene global coordinate system, and acquiring a multi-view original image in combination with a camera array arranged in the circumferential direction of an object; determining a rotation symmetry axis according to the multi-view contour features, reconstructing a three-dimensional geometric body, and calculating normal distribution and curvature change; generating a prediction image based on diffuse reflection and specular reflection hypothesis in the surface expansion domain through virtual visual angle disturbance, identifying a reflection region according to color and gradient consistency, and generating a reflection mask; and performing texture reconstruction on the reflective area by using geometric registration and multi-view compensation, and finally performing splicing and fusion to obtain a non-reflective high-fidelity panoramic image. The method does not need to change the field illumination condition, and can achieve the precise recognition and compensation of the complex curved surface reflection in the cultural relic in-situ collection environment.

A system for three-dimensional spatial perception underwater that includes a primary submersible vehicle. Frontward facing projectors are used to scan beams of light across a selected field of underwater view. Further, event cameras with pixels triggered by events are used to detect corresponding spots of the scanned beams that are reflected from underwater objects or surfaces. Circuitry is configured to determine positions of the objects based on the pixels that are triggered. Additionally, pilot submersible vehicles the projectors and event cameras are tethered to the primary submersible vehicle to provide extend detection of spots corresponding to reflections from underwater objects or surfaces.

The invention provides a digital twin model correction method and system based on machine vision. The method comprises the steps that a comprehensive data set is constructed by collecting sounding data, tidal flow velocity data and unmanned aerial vehicle images, wave disturbance deviation and water surface reflection distortion are eliminated based on geometric feature matching, and a dynamic compensation coefficient is generated in combination with tidal parameters; after time deviation of sounding data is corrected, a dynamic incidence relation between terrain elevation and sediment migration rate is calculated, a digital twinborn model fusing sedimentary layer thickness distribution and tidal flow velocity driven erosion boundary prediction is established, and a visual terrain curved surface is generated; through reverse verification of real-time sediment accumulation characteristics and terrain curved surfaces, migration rate weight parameters are adjusted in a self-adaptive mode, and dynamic optimization of the model is achieved. High-precision dynamic coupling simulation of sea area terrain evolution and sediment migration is achieved, the real-time performance and reliability of island surface change prediction are improved, and coastal zone safety and economic collaborative decision making is supported.

The invention relates to the technical field of defect detection, and particularly discloses an electronic component defect detection method, system and device, and the method comprises the steps: collecting a multiband original image set based on multispectral imaging, inhibiting batch material difference and surface reflection through orthogonal complementary space projection, and obtaining a de-noised image set; performing feature extraction on the de-noised image set, and identifying and marking all fragmented defect areas; based on a graph neural network space attention mechanism, establishing an association relationship between fragmented defect areas to form a complete defect feature chain; gray frequency value sequences of the to-be-detected image and the standard sample image are constructed respectively, and a first fitting curve and a second fitting curve are obtained through fitting of a skewed distribution function; and finally, comprehensively judging whether the electronic component has defects or not by combining the defect characteristic chain and the difference characteristics of the two fitting curves. According to the method, interference can be effectively suppressed, fragmented defects can be accurately identified, and the detection accuracy and reliability are remarkably improved through multi-dimensional feature fusion.

The invention discloses a data processing method and system for a dental three-dimensional model, and relates to the technical field of dental three-dimensional modeling, and the method comprises the steps: obtaining initial data of oral cavity scanning, recognizing a tooth type in the initial data, and determining a corresponding tooth surface reflection parameter according to the tooth type; generating scanning parameter combinations for different tooth positions according to the tooth surface reflection parameters and the tooth anatomical structure; tooth point cloud data are collected, and a tooth enamel reflective area and a shadow shielding area are identified; performing light reflection removal processing on the enamel light reflection area, performing data completion on the shadow shielding area, and generating corrected tooth point cloud data; and performing registration fusion on the corrected tooth point cloud data to generate a dental three-dimensional model containing a complete dentition. According to the method, the problem of data missing caused by enamel light reflection and adjacent tooth shielding is solved through a differential scanning strategy and regional data processing aiming at specific optical characteristics of teeth, and automatic construction of a high-quality dental three-dimensional model is realized.

The invention relates to the technical field of display screen defect detection, and discloses a mobile phone display screen defect detection method, device and equipment and a storage medium, and the method comprises the steps: collecting display images of a to-be-detected mobile phone display screen at a plurality of observation angles; the reflection intensity distribution of the display image is analyzed by using polarization optical characteristics, and a de-reflection image is generated after surface reflection components are separated; transforming the pixel brightness of each observation angle in the de-reflection image to a unified reference viewpoint to obtain a unified reference viewpoint image, and extracting a first defect feature vector of each pixel in the unified reference viewpoint image; and fusing the first defect feature vectors extracted from multiple observation angles to obtain a second defect feature vector, comparing the second defect feature vector with a preset threshold, and outputting a defect detection report. According to the application, multi-angle information advantages are utilized, and a defect classification mechanism based on RGB channel response differences is established; and various defect types of bright spots, dark spots, color cast and line defects can be accurately distinguished.

The invention discloses a metal processing detection system and method based on computer vision, and relates to the technical field of defect detection.Rotatable polarization filters are installed in front of a lens of a vision sensor, the polarization filters are arranged at four angles respectively, and four sets of polarization images are collected; calculating the polarization degree of each pixel point on the surface during metal processing by using the gray values of the four groups of polarization images, setting a polarization region interval, and dividing a metal surface reflection region into a specular reflection region and a diffuse reflection region; acquiring images of different wavebands by using a multispectral vision sensor, and constructing a multispectral image set; for the same wave band, the images of different exposure times are synthesized to obtain an HDR high dynamic range image; setting a weight for the HDR image of each wave band, and combining the weighting of the HDR image and the suppression of the polarization degree to carry out multispectral image fusion so as to obtain a final image; and a gray threshold value and an area threshold value are respectively calculated through the average value and the standard deviation, and the metal processing defects are judged by using the two threshold values.

The invention provides a plastic packaging barrel online defect detection method and system based on machine vision and deep learning. According to the method, visible light and thermal image data, aligned in time, of the surface of the plastic packaging barrel are collected, the dynamic range of a thermal image is expanded to enhance the identification degree, then highlight interference is compensated through the mapping relation between a thermal image stable area and a visible light reflection area, and surface reflection suppression is achieved; superposing the processed dual-mode data to generate a multi-mode fusion image, dynamically adjusting the temperature reference value of the fusion image based on the thermal conductivity of the material and the environment temperature of the production line, and positioning an abnormal temperature region; and finally, extracting topological contours and temperature diffusion characteristics of the regions, and inputting a deep learning model to judge material structure attributes and spatial positions of the defects so as to finish online detection. According to the method, thermal and visual data are fused to enhance the perception capability on fine structure defects, and the precision and robustness of online detection of the plastic packaging barrel in a complex illumination environment are remarkably improved.

The invention relates to the technical field of exhibition lamps, in particular to an exhibition lamp and an exhibition method, and the method comprises the following steps: inputting preset exhibit database information, extracting exhibit numbers, material types, dominant tone ranges and size information, carrying out point-by-point scanning on exhibit surfaces, collecting reflection spectrum data, converting the reflection spectrum data into CIELAB values, and integrating the extracted information and the collected data. And establishing an exhibit basic information set. The comprehensive exhibit basic information set is established by combining the preset database information and the real-time scanning and acquisition of the surface reflection spectrum or the CIELAB value of the exhibit, so that the subsequent illumination design can be carried out based on the unique optical characteristics of each exhibit, the accuracy and pertinence of personalized illumination are improved, and the material details and color levels can be deeply revealed. Secondly, processing the optical data of the exhibit by using a preset weight set associated with a specific display target, and generating an ideal display illumination parameter including spectral distribution and a brightness value;

The invention provides an apparent defect detection system and method based on CCD image recognition. A specular reflection interference area meeting a preset difference condition is recognized through a first surface reflection image and a second surface reflection image of a target patch element; extracting corresponding orthographic gray scale data from a third surface orthographic image obtained by adopting coaxial light source irradiation based on the specular reflection interference area; according to the brightness distribution gradient of the specular reflection interference area in the first surface reflection image and the second surface reflection image, constructing a texture restoration guide map, and using the texture restoration guide map to carry out texture restoration on the orthographic gray scale data to generate a texture restoration image of the specular reflection interference area; and generating a defect identification reference image for eliminating specular reflection interference based on the texture repair image, and outputting an appearance defect identification result of the target patch element by the defect identification reference image. According to the technical scheme provided by the invention, the defect detection of the patch element can be realized under the interference of mirror reflection.

The invention relates to the technical field of image processing, in particular to an image data processing method and system for digital management of environmental protection equipment, and the method comprises the steps: collecting a real-time image of an aeration area through a waterproof camera disposed above an aeration tank, detecting the definition of the camera regularly, and carrying out the cleaning when the definition is lower than a preset value; a self-adaptive Retinex algorithm is adopted for the real-time image of the aeration area to eliminate water surface reflection interference, noise caused by water turbidity is reduced through a multi-frame weighted average method, and a processed image is obtained; segmenting a bubble region in the image based on a U-Net network and calculating a bubble distribution parameter; comparing the bubble distribution parameter with a bubble distribution threshold value, and generating an aeration rate optimization instruction according to average dissolved oxygen data obtained by a dissolved oxygen sensor; and controlling the air blower based on the aeration rate optimization instruction. The power of the air blower can be better adjusted according to the bubble condition of the aeration tank, so that more energy is saved.

The invention provides a rapid calibration method and system for angle measurement precision of a laser seeker. The method comprises the following steps: emitting a laser beam to a calibration rod array through a laser seeker, and collecting the displacement of a laser spot reflected by the surface of each calibration rod through a position sensitive device; inputting the laser spot displacement into a spot displacement feature extraction network, and generating an angle and displacement time sequence containing a timestamp; identifying abnormal sampling points in the angle and displacement time sequence; and performing geometric reconstruction on the abnormal sampling points by adopting a space geometric constraint optimization algorithm and combining a fixed space included angle constraint relation to obtain angle measurement error calibration parameters of the laser seeker. According to the technical scheme provided by the invention, the high-precision dynamic calibration of the angle measurement error of the laser seeker is realized through the collaborative analysis of the space coordinates of the calibration rod and the displacement of the laser spot in combination with the neural network and geometric constraint optimization.

The invention discloses a bar count visual identification automatic calculation system and method, the system comprises a stereo visual acquisition unit, a dynamic threshold adjustment unit, a geometric feature analysis unit, a data processing module and a man-machine interaction unit, and the method comprises the following steps: S01, image acquisition and preprocessing; s02, adjusting an environment self-adaptive threshold value; s03, bar geometric feature extraction; s04, the number of bars is calculated; s05, outputting a result, displaying the bar count obtained by calculation on an interface of a man-machine interaction unit, and storing a counting result and related data in a database at the same time; the beneficial effects of the invention are that a conventional visual counting system usually only depends on two-dimensional image information, recognition errors are easy to occur under the conditions of bar adhesion, surface reflection and the like, the scheme constructs a stereoscopic vision system through an industrial camera to obtain three-dimensional point cloud data, image textures are enhanced in combination with coding structured light projected by a structured light emitter, and the recognition accuracy is improved. And the spatial position and surface depth information can be obtained.

The invention relates to the technical field of 3D vision measurement, and discloses a 3D binocular line laser weld contour data acquisition method and system. Two core steps of obtaining surface reflection characteristic information of a to-be-scanned area and adjusting output intensity of laser rays projected by a line laser device at different positions of the to-be-scanned area according to the surface reflection characteristic information are introduced, so that the problem that when a high-reflection welding seam is processed by a traditional method, the laser rays cannot be projected by the line laser device is effectively solved; the problem of image overexposure or underexposure caused by dramatic change of illumination characteristics is solved.

The diffuse reflection uniform light-emitting car lamp optical system comprises a lamp body, a circuit board, a light source and an aluminized reflection bowl, the light source is arranged on the circuit board, the diffuse reflection car lamp optical system further comprises a diffuse reflection reflecting plate, and the aluminized reflection bowl comprises a first diffusion pattern face arranged corresponding to the light source and a second diffusion pattern face arranged corresponding to the diffuse reflection reflecting plate; light emitted by the light source irradiates the aluminized reflection bowl, is reflected and diffused through the first diffusion pattern surface, irradiates the second diffusion pattern surface for reflection and diffusion, and then irradiates the surface of the diffuse reflection reflector to be reflected. The diffuse reflection uniform light-emitting car lamp optical system is reasonable in design, a good lighting effect is achieved through mutual cooperation of the reflection bowl, the fogging inner cover and the diffuse reflection reflector, and the diffuse reflection uniform light-emitting car lamp optical system is novel in light-emitting form, uniform in light-emitting effect and rich in layering sense.

The invention discloses a low-profile dual-circularly polarized wave beam scanning folding reflection array antenna. The low-profile dual-circularly polarized wave beam scanning folding reflective array antenna comprises a lower reflective array antenna and an upper circularly polarized selection metasurface. A circular polarization plane feed source is integrated in the middle of the reflective array antenna, and beam deflection is achieved. The circular polarization selection metasurface introduces opposite phase gradients to a left-hand circular polarization wave beam and a right-hand circular polarization wave beam through spin decoupling, and then introduces opposite wave beam deflection angles. Meanwhile, due to the polarization selection function of the circular polarization selection metasurface, the profile height of the antenna is half of the focal length of a traditional reflective array. By rotating the lower-layer reflective array antenna and the upper-layer circular polarization selection metasurface, the antenna can realize simultaneous + / -42-degree pitch angle scanning and 360-degree azimuth angle scanning of left-hand circular polarization and right-hand circular polarization dual beams, and the aperture efficiency, the axial ratio, the scanning loss and other performances are good. The low-profile dual-circularly-polarized wave beam scanning folding reflection array antenna provided by the invention can realize simultaneous scanning of two circularly-polarized wave beams, and is low in profile, compact in structure, low in cost and novel in function.

The invention relates to the technical field of remote sensing data analysis, in particular to a land resource management data analysis system. According to the method, the spectral reflectivity change under the earth surface multi-direction illumination is obtained and the reflection gradient response information of the spectral reflectivity change is extracted, so that the spatial difference of the earth surface reflection characteristics at different angles can be more comprehensively presented; according to the method, surface land type division is more accurate in gray continuity and spatial structure expression, so that potential fission boundaries are identified and reasonable section classification is carried out through quantitative comparison and spatial aggregation analysis of structure texture differences in boundary identification between different regions, and the identification accuracy of the boundary identification between different regions is improved. The stability and variability of the interior and boundary structures of the land areas are effectively described, and on this basis, the area boundary is reconstructed and combined with texture and reflection clustering grouping, so that the land type state and the distribution boundary of each area can be finely judged.

A surface scanning tool and methods of using a surface scanning tool to determine a surface shape of a tool. In embodiments, the surface scanning tool includes a laser, a detector, and a signal analysis module. The laser sends a beam of light that is reflected off a bottom surface of the tool. The detector receives the reflected beam of light and sends the reflected beam of light signals to a signal analysis module. The signal analysis module determines a surface shape of the bottom surface and triggers mitigation actions. In alternative embodiments, the surface scanning tool includes a camera and a signal analysis module. The camera takes a picture of the bottom surface of the tool and sends the image to the signal analysis module. The signal analysis module determines the surface shape of the bottom surface and triggers mitigation actions.

The technology described herein is directed towards a metasurface (reconfigurable intelligent surface) that can be used to redirect signals to and from non-terrestrial network satellites. The metasurface can be passive, and provide signal array gain with respect to indoor user equipment sending and receiving signals to and from the network satellites. The metasurface can be portable for use in various scenarios. Further, the metasurface can be configured to operate in a transmission mode, in which incoming signal is passed through the metasurface, or can be reconfigured to operate in a reflection mode, in which incoming signal is reflected by the metasurface. Different phase shifts of the metasurface's unit cells result in array gain through constructive interference, by refraction in the transmission mode, or reflection in the reflection mode. The presence or absence of a removable back plane determines the transmission or reflection operating mode of the metasurface.

The invention discloses an automobile hexagonal anti-loosening fastening nut full appearance detection method and system.The method comprises the steps of nut placement and lighting, to-be-detected image collection, detection model construction and nut defect detection, and in the nut placement and lighting step, fine lighting control is achieved through a multi-angle adjustable light source system; the lamp bead combination, brightness and angle are adjusted, and a lighting evaluation result is output; in the to-be-detected image acquisition step, hexahedral images of a nut are acquired through a multi-camera system, and detection blind areas are eliminated; in the detection model construction step, a training data set is constructed based on a non-reflective area image, and a deep learning model is optimized in combination with a lighting evaluation result; in the nut defect detection step, real-time defect identification and standard exceeding judgment are realized through a defect detection model, and a lighting evaluation result is associated to guarantee the detection reliability, so that the problem of metal surface reflection interference is solved, full-dimensional, high-precision and high-stability nut appearance detection is realized, the detection requirements of nuts of multiple specifications are met, and the detection efficiency is improved. The efficient quality inspection requirement of an industrial production line is met.

The invention relates to the technical field of industrial automation, in particular to an industrial robot posture recognition method. Aiming at the problems of weak workpiece texture, strong surface reflection, serious stacking and shielding and the like in an industrial production line, a pixel-level dense feature fusion and self-attention mechanism is introduced, and semantic texture information of a color image and spatial geometric information of a depth image are integrated in a feature extraction stage; the problem that the posture of a rotationally symmetrical workpiece is fuzzy is solved through an asymmetric loss function, meanwhile, a comprehensive grabbing scoring model containing force sealing stability, environment collision risk probability, mechanical arm kinematics reachability and visual uncertainty is further established, and through the mode of combining off-line grabbing candidate construction and on-line real-time evaluation, the grabbing accuracy of the mechanical arm is improved. And the globally optimal grabbing pose is screened out. According to the method, the recognition precision and robustness of the industrial robot in the unstructured environment are remarkably improved, and the success rate and safety of grabbing operation are improved.

The invention discloses a coherent interference-based coaxial transceiving line scanning three-dimensional profile measurement system and method. The system comprises a low-coherence light source; the beam splitter is used for collimating light emitted by the low-coherence light source and then dividing the light into two paths; the measuring light is focused into a linear light beam through the cylindrical lens and is emitted to the surface of the to-be-measured sample, and the measuring light reflected by the surface of the to-be-measured sample returns to the beam splitter along the original path; the reference light is emitted to a reference mirror with a certain inclination angle and is reflected back to the beam splitter through the reference mirror; the measuring light reflected by the surface of the sample to be measured and the reference light reflected by the reference mirror are subjected to beam combination interference through a beam splitter and are imaged to enter a camera for interference pattern acquisition; the signal processing system is used for processing the interference patterns to obtain height distribution of the to-be-measured sample on a line field, and three-dimensional profile measurement of the to-be-measured sample is realized by transversely moving or transversely scanning the to-be-measured sample and overlapping the interference patterns measured at different positions. Therefore, high-efficiency measurement can be realized while the micro-nano precision is kept.

Provided herein are various enhancements for radio frequency antennas and antenna arrangements. In one example, an apparatus comprises a reflector for radio frequency energy having a reflector surface, and a lens element. The lens element is configured to alter a distribution of at least a portion of the radio frequency energy reflected by the reflector surface over a detection area of a feed array positioned a selected distance from the lens element.

The invention discloses a drowning detection method and system combined with polarization multiple modes, belongs to the technical field of drowning detection, and aims to solve the problem of low accuracy caused by the influence of water surface reflection and complex water environment in the existing method. The method comprises the following steps: collecting a polarization degree map and an intensity map of a swimmer; inputting the two images into a pre-trained polarization fusion network, and obtaining a fused image through feature extraction, fusion and reconstruction; training a target detection network combined with polarization fusion features by using a simulated drowning scene video / image shot by a polarization camera; and inputting the fused image into the trained detection network, and judging whether drowning occurs or not. The method eliminates water surface reflection, improves image information integrity and detection accuracy, adapts to multiple scenes, and is suitable for intelligent drowning detection in places such as swimming pools and bathing beaches.