1512results about "Polarisation-affecting properties" patented technology

The invention discloses a socket surface defect detection method and system based on image processing, particularly relates to the technical field of industrial surface defect detection, and is used for solving the problem of low detection precision caused by specular reflection noise interference and complex curved surface defect feature coupling on the surface of a socket made of a high-reflection material. The incident angle and light intensity adjustment and control parameters are dynamically adjusted through an adjustable polarized light source, the surface geometric contour and defect high-frequency characteristics are separated through frequency domain decomposition processing, specular reflection interference is restrained, and the defect contrast ratio is enhanced; the method comprises the following steps: constructing a two-dimensional characteristic space of radial curvature and light intensity modulation depth based on diffuse scattering light spot morphological analysis in an orthogonal incident light direction, and quantifying defect physical scattering characteristic difference; metal oxidation and mechanical damage defect types are distinguished through adaptive density clustering, and accurate output of defect positions is realized by utilizing affine transformation mapping, so that the detection robustness and accuracy of the tiny defects on the high-reflective surface of the complex curved surface are remarkably improved.

A method and device for inverting ocean-atmosphere optical parameters and storage medium. The method includes: obtaining a vector apparent reflectance ρl, ρQ, ρU of water-leaving radiance at top of atmosphere and observation geometry of a multi-angle polarized satellite, and inputting the vector apparent reflectance ρl, ρQ, ρU and the observation geometry into a trained ocean-atmosphere optical parameter model, to output a group of ocean-atmosphere optical parameters, the output ocean-atmosphere optical parameters comprise: PBOAw, FAOD / CAOD, FRm / CRm, W, CHL and SPM, the ocean-atmosphere optical parameter model is an XGBoost machine training model. In this way, the ocean-atmosphere optical parameters can be quickly and stably inverted.

The invention discloses a quartzite surface defect detection method, system and device, and relates to the technical field of image processing, and the method comprises the following steps: fixing a to-be-detected quartzite on a detection platform, and carrying out preprocessing; constructing a double-path polarization imaging light path; polarization parameter optimization is carried out based on the optical anisotropy characteristic of quartz stone, so that a polarization state difference is generated between a defect area and a normal area; under the condition of polarization parameter optimization, synchronously acquiring a first polarization image and a second polarization image through a double-path polarization imaging light path; performing polarization difference calculation on the first polarization image and the second polarization image to generate a polarization difference image; and carrying out contrast enhancement processing on the polarization difference image, identifying a defect area, carrying out defect classification, and outputting a quartz stone surface defect detection result. By optimizing polarization imaging parameter configuration and combining image processing, high-precision detection and intelligent classification of quartz stone surface defects are achieved, and the automation level and reliability of detection are improved.

The invention discloses an amphibious unmanned aerial vehicle riverway sediment concentration real-time monitoring method based on underwater light field imaging and cross-modal fusion, and relates to the technical field of riverway sediment monitoring. Comprising the following steps: acquiring aerial multispectral data and preprocessing the aerial multispectral data; an integrated polarized light field camera is carried on an amphibious unmanned aerial vehicle to capture underwater light field data, and underwater three-dimensional light field information is reconstructed and sediment scattering characteristics are extracted through an optical model and a lightweight deep learning network; the air multispectral data and sediment scattering characteristics are fused through space-time alignment and an attention mechanism, a sediment concentration prediction model is generated, and then a spatial distribution diagram of the river sediment concentration is output; and carrying out real-time monitoring and early warning on the river sediment concentration according to the spatial distribution diagram of the river sediment concentration through edge calculation and cloud collaboration architecture. The method is combined with an advanced deep learning algorithm, high-resolution silt concentration inversion can be realized, and the method has real-time performance and adapts to a complex water body environment.

The invention provides a multi-layer optical film detection method, device and equipment and a storage medium, and the method comprises the steps: obtaining a polarization phase difference signal of transmission light and reflected light through multi-angle incidence irradiation of a multi-band programmable laser source, and recording the polarization ellipticity parameter change; then combining confocal microscopic interference and polarization analysis to determine a space coordinate and a stress distribution diagram of a stress abnormal region; continuously irradiating in a photo-thermal coupling environment through a broadband light source, and monitoring interference signals, polarization states and temperature changes to obtain dynamic evolution characteristics; and finally, performing a simulation test on the multi-layer optical film in a system environment with preset optical axis arrangement and light beam energy distribution, obtaining an in-situ polarization state and interference pattern data, and evaluating the optical performance of the film layer. According to the invention, potential defects can be positioned under high resolution, and the reliability and imaging quality of the film layer under complex application conditions can be accurately evaluated.

The invention discloses an industrial area atmospheric environment monitoring management system and method, and relates to the technical field of industrial Internet of Things environment monitoring, and the method comprises the steps: triggering polarization imaging to scan a target region based on the time-space information of an abnormal event signal, obtaining the polarization characteristic data of a pollution plume, and generating a spatial distribution characteristic parameter; inputting the sound pressure abnormal indexes and the spatial distribution characteristic parameters into an industrial equipment leakage causal model, calculating a pollution source confidence coefficient, and when the pollution source confidence coefficient reaches a process safety dynamic threshold value, obtaining an industrial equipment traceability result and a leakage level; according to the traceability result of the industrial equipment and the leakage level, a hierarchical control instruction is obtained, meanwhile, the actually measured attenuation rate of the industrial pollutants is calculated, and the dynamic response effect is verified; according to the method, cross-modal fusion modeling is carried out on acoustic abnormal information and pollutant spatial distribution characteristics, so that the technical limitation that pollution source positioning is carried out by depending on a static empirical formula traditionally is broken through.

The present invention relates to the field of defect detection technology, and in particular to an OLED screen defect detection method based on optical-magnetic multimodal fusion, comprising the following steps: S1: synchronous excitation and data acquisition based on pulsed current drive; S2: cross-modal spatial calibration and noise suppression; S3: polarization-magnetic field coupling feature extraction; S4: dynamic correlation decision-making and closed-loop feedback, including realizing defect classification determination through correlation analysis of multimodal data, and verifying the authenticity of defects through current overload testing. This method effectively solves the problems of ambient light interference, missed detection, high cost, low resolution, etc. existing in the prior art, has significant beneficial effects, can improve detection accuracy, efficiency and reliability, meet the needs of large-scale production lines, and can efficiently locate and reduce errors and redundant steps in the detection process.

The invention relates to the technical field of image data processing, and discloses a fine metal powder defect detection method and system based on image recognition, and the method comprises the steps: illuminating a metal powder region through a non-polarized light source, and collecting two images in an orthogonal polarization state through imaging equipment with a linear polarizer, according to the method, the defect morphological fingerprints are constructed through the polarization information entropy, the three-dimensional structure information is converted into light field order degree change for detection, the dimension limitation of traditional two-dimensional imaging is broken through, and the detection accuracy is improved. Hidden defects such as internal pores and aggregates can be accurately identified, and meanwhile, stable detection and material defect cross discrimination under a dynamic working condition are realized in combination with motion compensation and multiband entropy ratio verification.

The invention discloses an optical performance detection system and method for a camouflage material, and relates to the technical field of camouflage material detection, and the system comprises a structure identification and illumination control module which is used for collecting a surface image of a camouflage material sample, identifying the surface structure of the sample, starting a full-spectrum light source, and simulating step-by-step illumination from weak light to strong light; carrying out RGB imaging based on the standard illumination; and the region division module is used for applying a superpixel segmentation algorithm to the image, automatically dividing sub-regions, performing hyperspectral reflectivity scanning on each region, synchronously acquiring a light intensity image in a polarization direction, calculating a Stokes vector and constructing a polarization enhanced image. According to the method, frequency domain quantitative analysis of microcosmic interference fringes and accurate mask extraction of polarization abnormal areas can be realized, optical exposure risks of camouflage materials under complex illumination and visual angle conditions are effectively quantified through multi-angle reflection sampling and scoring function modeling, and the detection precision, the area pertinence and the automation level are remarkably improved.

The invention relates to a rail surface defect detection method and system, and the method comprises the steps: collecting a reflection response sequence of a rail surface under various illumination conditions through the controllable dynamic disturbance of incident angles and illumination intensity of different positions of the rail surface, and representing the microscopic optical response behavior of a rail surface material; for each tiny area on the surface of the rail, dynamic reflection stability is calculated, and areas with abnormal stability are marked as defect candidate areas; analyzing the difference between the defect candidate area and a normal wheel-rail contact trace, identifying whether abnormal residues or abnormal abrasion boundaries generated due to defect evolution exist or not by combining optical heterogeneity boundary characteristics, and verifying the authenticity of the defect; for the judged defect candidate region, judging whether the optical response of the adjacent region has a general change trend or not along the contact track direction and the normal micro-region fluctuation direction of the rail surface, and determining the space connectivity and the diffusion trend of the defect and a growth defect region; the system executes the steps of the method through a processor.

The invention relates to the technical field of optical detection, in particular to a glass bottle surface spraying quality detection method which comprises the following steps: under a specified wavelength, acquiring target incident light by adjusting a polarization angle, irradiating a glass bottle spraying layer, collecting a transmission spectrum signal to calculate parallel and vertical polarization transmissivity and ratio of the spraying layer, and generating polarization transmissivity. According to the method, the light with the polarization angle irradiates the spraying layer, the polarization component of the transmission light is obtained, the thickness uniformity and the internal structure are analyzed, weak areas, particle flaws and excessive spraying of the spraying layer are recognized, the defect detection precision is improved, multi-angle transmissivity data are collected, the change rate is calculated, and color deviation and thickness abnormity are accurately positioned; through cross analysis of multiple optical parameters, evaluation of adhesive force, curing quality and color consistency is more detailed, spraying abnormity is classified, multiple detection means act synergistically, interference such as environment illumination and material reflectivity is reduced, and the detection accuracy of spraying quality is improved.

The invention discloses a metal film measurement method based on a theoretical spectrum and a measurement spectrum, and relates to the technical field of film optical measurement, and the method comprises the steps: carrying out the spectrum scanning of a to-be-measured metal film sample through an ellipsometer in a preset wavelength range, and obtaining the measurement spectrum data; constructing a theoretical spectrum model based on a three-layer film system structure, and setting initial values of structure parameters; substituting the structural parameter initial value into the theoretical spectrum model to generate theoretical spectrum data; performing iterative adjustment on the structure parameters by adopting a multi-strategy parallel global optimization algorithm, terminating an iterative process when a first convergence criterion is met, and outputting an optimal structure parameter; and calculating and outputting the actual film thickness, the refractive index and the extinction coefficient of the metal film based on the optimal structure parameters. According to the method, the theoretical spectrum model combining the Deroude-Lorentz dispersion model, the effective medium approximation theory and the transfer matrix method is constructed, high-precision characterization of the optical parameters of the metal film is achieved, and the measurement precision is effectively improved.

Described herein are methods and systems for measuring polarization states of nonlinearly generated light by a sample illuminated in response to receiving an incident beam having a known polarization state to determine a characteristic of the sample. The system includes an optical ellipsometer configured to be included in-line of a semiconductor fabrication line and generate measured signals proportional to different polarization parameters of second-harmonic light nonlinearly generated light by the sample, allowing determination of a complete polarization state of the second harmonic light using a characteristic of the sample is determined.

To provide an optical measurement device, a data management method for optical measurement devices, and a data management program for optical measurement devices, which can achieve strict traceability required in the pharmaceutical industry.SOLUTION: An optical measurement device, which stores history data combining measurement data of an optical characteristic of a sample measured by measurement means of the optical measurement device with management information on a plurality of management target components detachably mounted on an optical measurement device body, and can trace the history data when used and required, comprises: recording means attached to the management target component for recording the management information on the management target component; reading means for reading the management information recorded by the recording means when the management target component is mounted on the optical measurement device body, or when the management target component is mounted on the optical measurement device body and measured by the measurement means; and storage means for storing the history data combining the read management information with the measurement data measured by the measurement means.SELECTED DRAWING: None

The invention relates to the technical field of flame retardant particle quality monitoring, in particular to a flame retardant particle quality online monitoring and sorting system based on AI visual identification. The system comprises a polarized light field imaging module, a refractive index gradient field construction module, a dynamic sorting decision module and an online self-optimization module. A Stokes parameter image and a multispectral transmittance distribution diagram of the particles are obtained through a polarized light field imaging module; the refractive index gradient field construction module is used for converting optical data into a refractive index gradient field and accurately identifying internal defects; the dynamic sorting decision module generates a sorting instruction according to the defect characteristics; and the online self-optimization module realizes continuous optimization of the system. The method solves the problem that a traditional method is difficult to accurately identify transparent defects, can effectively identify micron-sized pure bubbles and transparent cracks, realizes defect classification and cause analysis, can meet the real-time quality monitoring requirement of a flame retardant production line, and provides an intelligent solution for product quality control.

The invention provides a door and window glass defect feedback control method and device, electronic equipment and a storage medium, and relates to the technical field of door and window glass defect detection. The method comprises the steps of collecting a first image after a polarized light imaging detection device is adjusted to suppress reflected light on the surface of glass and enhance scattered light of bubbles in the glass; after the polarized light imaging detection device is adjusted to enhance reflected light on the glass surface, a second image is collected; calculating an adaptive weight group by analyzing local characteristics of the second image; weighting the first image according to the self-adaptive weight group, and subtracting the weighted first image from the second image to obtain a difference image; and extracting bubble defect information in the glass by analyzing the differential image. According to the method, interference caused by non-uniformity of glass surface reflection is overcome, the adaptability of image differential processing to surface reflection background suppression is improved, and therefore image features of internal bubble defects are extracted more effectively and more accurately.

Provided in the present invention are an imaging device and method for turbid oil abrasive particles based on polarized image enhancement, which belong to the technical field of image processing. The imaging device of the present invention includes a CMOS fixing device, a Stokes polarized CMOS sensor, an optical lens sleeve and an optical magnifying glass, where the Stokes polarized CMOS sensor includes a CMOS sensor and a Stokes analyzer. By using a polarization characteristic difference between scattered light of lubricating oil media and reflected light of abrasive particles, Stokes vector information is measured in real time under turbid lubricating oil scenes, the scattered light of the media is filtered out, image quality of the abrasive particles is improved, coverage duration for monitoring abrasive particle imaging is effectively prolonged.

According to the ellipsometer based on the micro-nano deformable structure provided by the invention, the ellipsometer can be reduced to a sub-pixel level by the metasurface based on the micro-nano deformable structure, and when a large amount of the micro-nano deformable structure is integrated in the space, parameters of a measured surface of a whole measured material can be obtained in an imaging form; the limitation that a traditional ellipsometer can only perform single-point measurement is broken through; namely, two-dimensional measurement can be carried out in an imaging mode, the defect of single-point measurement of a traditional ellipsometer is overcome, the on-chip size of the ellipsometer is greatly reduced, and the size of the ellipsometer is reduced to the single-pixel level; the micro ellipsometer can be combined with different optical lens groups to detect the optical property and uniformity of the whole film in an imaging manner, and the defect of single-point detection of a traditional micro ellipsometer is overcome; according to the total variation-based full Stokes polarization vector reconstruction model, constraint is applied to iteration internal data, so that an operation result is more stable and is easy to converge.

The invention discloses an intelligent water quality monitoring and evaluating system based on image recognition, which relates to the technical field of environment monitoring, and comprises a fusion module for controlling a polarizer array to rotate based on an environment parameter set, capturing water surface optical images in different polarization directions, and performing image reconstruction through a polarization characteristic tensor decomposition method, generating a high-definition water surface image after reflection suppression; the three-dimensional diagram generation module is used for acquiring a morphology stripe image of the water surface through a DLP projection method, and generating a three-dimensional depth diagram in combination with the high-definition water surface image; the pollution identification module is used for correcting the three-dimensional depth map based on the real-time water temperature data, identifying spatial distribution of pollutants through a dynamic structure element opening and closing algorithm and generating a three-dimensional pollution distribution map; according to the method, mirror reflection noise is suppressed through multi-angle polarization image fusion, and the distinguishability of pollutant characteristics is remarkably enhanced while the image resolution is kept.

The invention relates to the technical field of road engineering and artificial intelligence, and discloses a traffic road disease detection system and method based on a cloud edge-end architecture, and the system comprises: 1, a vehicle-mounted multi-mode optical sensing terminal which is used for synchronously collecting pavement images, spectrums and three-dimensional data; the vehicle-mounted edge calculation unit is used for constructing a digital twin baseline of the road surface grid unit and executing unique double-path parallel analysis, on one hand, the health degree attenuation degree of the current state compared with the baseline is quantified, and on the other hand, whether the change is caused by a natural disease or a manual maintenance event is judged through a feature signature recognition engine; and the cloud management platform is used for storing historical health degree data and predicting a future attenuation trend through a time sequence model. According to the method, the problems that early compound diseases are difficult to recognize and the maintenance behavior is easily misreported as the pain point of the diseases in the prior art are solved, the crossing from passive detection to active prediction is realized, and the accuracy of road detection and the scientificity of maintenance decision are remarkably improved.

The invention discloses a lunar resource in-situ exploration-while-drilling device and method. The lunar resource in-situ exploration-while-drilling device is composed of a spiral drilling tool, an illumination light source module, a polarization spectrum detection module and a dual-channel spectrum measurement module. The drilling tool drill rod is of a hollow structure. Light emitted by the illumination light source module is collimated and depolarized to form unpolarized parallel light to irradiate lunar soil on the side wall of the drill hole, and the polarization spectrum measurement probe collects reflected light of the lunar soil; the reflected light is collimated by a front collimator objective of the probe and then sequentially passes through a spectrum modulation unit consisting of an achromatic 1 / 4 wave plate, a multi-stage wave plate, a beam splitter prism and two polaroids of which the light transmission directions are vertical to each other, and two orthogonal light beams are formed, so that polarization information of the reflected light is modulated in a spectrum dimension; demodulating the modulated spectrum to obtain the spectrum and polarization information of the lunar soil reflected light; and the resource distribution and content and the physical characteristics of the original lunar soil are inversed by using the polarization spectrum characteristics of the lunar soil. According to the invention, in-situ exploration of lunar subsurface depth profile mineral resources can be realized.

The invention discloses a rapid polarized light acoustic imaging device which comprises an excitation source, a light beam shaping module, a rapid polarization modulation module, an energy feedback module, a rapid scanning module and an acquisition processing module. And receiving photoacoustic signals corresponding to the exciting light in four different polarization states for calculation, and extracting anisotropy information of the sample. Compared with multiple times of scanning a sample or modulating the polarization state by rotating a half-wave plate, the problems of dislocation of multiple times of polarization acquisition points and false positive calculation are avoided, meanwhile, the time interval generated by continuously modulating the laser pulses is short, and energy fluctuation among the four pulses and errors caused by fluctuation are reduced. According to the invention, the limitation of the precision and speed of polarized light acoustic microscopic imaging is overcome, the microstructure characteristics in the target sample can be rapidly, accurately and highly sensitively detected, and the method has great application prospects in biomedical imaging and high-precision material detection.

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

The invention relates to the technical field of image data processing, and discloses a method for detecting impurities in metal powder based on image recognition, which comprises the following steps of: irradiating the metal powder by using polarized light, synchronously acquiring an orthogonal polarization component image of the reflected light, and realizing impurity detection by calculating a differential image. Qualified powder spontaneously forms a uniform dark field in a differential image by utilizing the essential difference of response of metal powder and impurities to polarized light, and the impurities generate remarkable signals due to optical anisotropy, so that the detection blind area of the traditional method on the microscopic impurities is broken through, the method further performs time sequence analysis by multiplexing total luminous flux data, and the detection accuracy is improved. Synchronous identification of impurity morphological characteristics is realized, component and morphological two-dimensional detection capability is formed, the system realizes adaptive threshold adjustment based on statistical characteristics of differential images, and long-term operation stability is ensured.

The invention relates to the field of optical material defect detection, and discloses a PC lens defect classification and identification method and system, and the method comprises the following steps: asynchronously collecting lens multi-modal data through polarized light imaging, thermal imaging and an acoustic emission sensor, and constructing a five-order asymmetric tensor containing polarization angle, spectrum, time, space and defect features; performing dynamic dimension reduction on the tensor by using an improved Tucker decomposition method, and extracting a core tensor and a factor matrix; establishing a polarization angle-time correlation coding model based on inverse problem solution of a light field state equation, deducing defect distribution characteristics and optimizing a core tensor; mapping the optimized tensor to the QUBO Hamiltonian of a quantum annealing machine, and carrying out optimization solution; and finally, fusing the multi-mode confidence coefficients of polarized light, thermal imaging and acoustic emission signals, generating defect classification labels and inverting geometric and mechanical parameters of the defects. The lens flaw detection efficiency and the classification accuracy are remarkably improved, and the method is suitable for industrial-grade high-precision quality control scenes.

The invention discloses a defect detection system for a metal-composite material mixed structure device. The defect detection system comprises an industrial control computer, a mechanical scanning arm, a polarization detection probe, an ultrasonic detector assembly and a power supply, the invention further provides a defect detection method for the metal-composite material mixed structure device. The defect detection method specifically comprises the following steps: acquiring polarization image information of the metal surface; solving polarization image parameter information; carrying out surface defect detection; metal internal ultrasonic detection information is obtained; performing internal defect detection; and performing multi-mode data fusion detection. According to the invention, two information sources with complementary advantages, namely polarization and ultrasound, are selected as detection information sources of the multi-modal detection method, so that all-directional defect detection and visualization on the surface-interior of the metal-based composite material mixed structure device are effectively realized; and a feasible technical method is provided for engineering application of polarized light / phased array ultrasonic multichannel integrated detection.

The invention belongs to the technical field of light polarization analysis, and discloses a method for determining the sex of an embryo in an egg based on polarization image recognition. Comprising the following steps: acquiring a transmitted spectrum image sequence of a hatching egg to be detected at a plurality of polarization angles, wherein the transmitted spectrum image sequence covers a transmitted spectrum image from visible light to a near-infrared band; extracting a polarization sensitive wave band set of the embryonic tissue according to the polarization state change characteristics of the embryo area in the transmitted spectrum image at different polarization angles; constructing an embryo gender characteristic spectrum based on the polarization degree distribution difference and the spatial texture characteristics of each wave band in the polarization sensitive wave band set; determining an optimal wave band combination for sex determination by analyzing the relevance between a polarization anisotropy index of a specific wave band in the embryo sex characteristic spectrum and an embryo development stage; according to the polarization response mode corresponding to the optimal wave band combination, the sex of the embryo in the egg is judged, and the resource investment and the waiting cost are greatly reduced.

The invention relates to the technical field of leaf nitrogen content estimation, in particular to a method for establishing a grassland plant nitrogen content monitoring model based on a remote sensing technology. The method comprises the following steps: controlling an unmanned aerial vehicle platform carrying a narrowband multispectral camera and a linear polarization camera, and collecting a spectral image sequence and a polarization image group at an observation window with a solar zenith angle of 30-40 degrees; extracting a reflectivity value of each wave band in the spectral image sequence, calculating a reflectivity first-order derivative and determining a red edge position offset; extracting horizontal and vertical polarization components in the polarization image group, calculating a polarization degree and constructing a polarization degree difference index; and identifying the center of the fecal spot by searching a pixel with a local maximum polarization degree difference index and red edge position offset blue shift exceeding a preset threshold value. According to the method, excrement spot recognition and remote sensing description of the nitrogen influence range thereof are achieved through double-index complementation of the red edge position offset and the polarization degree difference index.

The invention discloses a transient absorption spectrum measurement system, method and device for polarized light, and relates to the technical field of ultrafast spectrum measurement. In the system, a laser generation device generates first laser and second laser, and the first laser is converted into left-handed circularly polarized light or right-handed circularly polarized light through a pump light polarization device to serve as pump light for exciting a sample to be detected; the first Glan prism converts the second laser into detection light which is linearly polarized in a specified direction so as to detect the sample to be detected; the first lambda / 4 wave plate is used for converting the detection light after detecting the to-be-detected sample into linearly polarized light with mutually vertical polarization; the Wollaston prism enables the linearly polarized light with mutually vertical polarization to be respectively transmitted to the measuring device along different directions; the measuring device calculates the transient absorption spectrum of the left-hand circularly polarized probe light and the transient absorption spectrum of the right-hand circularly polarized probe light. The system can simultaneously measure the transient absorption spectrums of the left-hand circularly polarized light and the right-hand circularly polarized light, so that the measurement error is reduced.

The invention relates to the technical field of machine vision and optical detection, in particular to a tea color automatic evaluation method and system based on machine vision. The method comprises the following steps: constructing a stable and repeatable optical measurement environment and calculating radiation baseline parameters; performing multi-band polarization sequence imaging on the tea sample to obtain original data with spectrum and structural characteristics; separating mirror surface and diffuse reflection components on the surfaces of the tea leaves, and performing spectrum consistency correction by combining a radiation baseline; performing multiband spectrum reconstruction and normalization processing on the basis of the corrected diffuse reflection image, mapping to a CIE Lab color space, extracting pixel-level brightness, chromaticity and color distribution statistical indexes, and generating a color feature vector in combination with spatial weighting matrix optimization; a final score is calculated by constructing a quantitative evaluation and grade judgment model and integrating perception color separation, drying calibration color separation and a penalty term, and a grade result is output. According to the method, objective, accurate and automatic evaluation of the color of the tea leaves is realized.