452 results about "Image calibration" patented technology

The invention provides an interaction method and system applied to painting and calligraphy exhibition, and relates to the technical field of data interaction, and the method comprises the steps: building a user exhibition watching behavior data set through real-time collection based on an exhibit region; traversing the exhibit area to carry out multi-dimensional image calibration, and establishing a coordinate-label mapping network; traversing the coordinate-label mapping network set according to the user exhibition viewing behavior data set to activate an exhibit identification module, identifying a target exhibit number to perform linkage display of painting and calligraphy on a target user, generating display information, starting an exhibit interaction module to perform deep interaction on the target user in combination with the display information, and generating a personalized painting and calligraphy display guide path. The technical problem that in the prior art, due to the lack of real-time perception and accurate recognition of exhibition watching behaviors of users, personalized exhibit linkage and dynamic guide cannot be achieved is solved, and the technical effect that the personalized guide path is generated based on the interests of the users, so that the exhibition watching immersion and interactive experience are improved is achieved.

An image calibration method and a device are provided. The method includes: obtaining a pupil position offset of a user and a visual acuity of the user, where the pupil position offset of the user is an offset of a pupil of the user relative to an optical axis; and adjusting a to-be-displayed image based on the pupil position offset of the user and the visual acuity of the user. In this way, when the user wears a head-mounted display device improperly, a point seen by the user when the user looks straight ahead is a center point of an image displayed on a display.

An electronic device for processing a blood vessel image according to an embodiment may include: an arc-shaped C-arm open toward the isocenter; a radiation source connected to the C-arm and emitting radiation to a target blood vessel located on a table; and a processor for computing a target distance from the radiation source to the target blood vessel, on the basis of a first vertical distance from the isocenter to the table and a second vertical distance from the target blood vessel to the table, and computing a physical distance of the target blood vessel by using the computed target distance, from a blood vessel image obtained using radiation.

The invention relates to the technical field of image calibration, and discloses an ink-jet printer real-time image calibration system and method based on edge calculation, and the method comprises the steps: constructing a composite parameter matrix, completing the no-load error analysis, and generating a compensation matrix and a dynamic weight distribution function; constructing a multi-scale gradient feature pyramid according to the composite parameter matrix, fusing the features of the pyramid to generate a feature correlation thermodynamic diagram, and establishing a model to predict an ink diffusion trajectory after correction; and finally generating a control signal by combining the compensation matrix and the prediction result, and controlling the motion pose of the nozzle. According to the method, the code spraying process is accurately controlled by integrating multiple factors, the precision and quality of code spraying patterns are remarkably improved, the rejection rate is effectively reduced, and the production efficiency is improved.

The invention discloses a key point detection-based fish size estimation system and method in a complex underwater environment. An image acquisition module acquires a calibration plate image and left and right images of a fish; the calibration parameter acquisition module acquires calibration parameters; the distortion correction module performs distortion correction on the left and right images; a depth information calculation module calculates depth information corresponding to the pixel points of the left image; the data set construction module is used for marking a fish body and constructing a fish key point detection data set; the image enhancement module performs image enhancement on the left image; the key point detection model construction module constructs a key point detection model, the model training module trains the key point detection model and identifies a fish target and key points in an image, the key point moving module moves the key points, and the fish size calculation module obtains depth information of the moved key points. And converting the pixel coordinates into world coordinates, and calculating the distance between the key points to obtain the fish size. According to the invention, accurate estimation of the fish size is realized.

The invention belongs to the technical field of space remote sensing surveying and mapping, and particularly relates to a monitoring system and method for a front and rear view visual axis included angle and absolute direction of a surveying and mapping camera. The method comprises the following steps: S1, through side sway of a satellite platform, taking a time for sky imaging calibration as a reference time; s2, calculating a rotation matrix from a front and rear view ground camera measurement coordinate system to a star camera coordinate system at a reference moment; s3, calculating respective thermal deformation matrixes of the star camera coordinate system, the front-view camera measurement coordinate system and the rear-view camera measurement coordinate system; s4, obtaining a real-time rotation matrix from the measurement coordinate system of the front-view camera to the coordinate system of the star camera and a real-time rotation matrix from the measurement coordinate system of the rear-view camera to the coordinate system of the star camera at the measurement moment; and S5, carrying out arc cosine calculation on the two absolute pointing vectors to obtain a visual axis included angle between the front-view camera and the rear-view camera at the measurement moment. According to the invention, while the geometric accuracy of the surveying and mapping camera is ensured, the real-time performance of measurement and the comprehensiveness of subsystem monitoring are realized at the same time.

The invention relates to the field of microscopic imaging, and discloses a miniature microscopic system optical precision improvement and image calibration error optimization method, which comprises the following steps: establishing an optical distortion model and a mechanical disturbance model, and respectively describing a static error and a dynamic error; constructing a joint dynamic error model, and uniformly expressing a coupling relationship between optical distortion and mechanical disturbance; decoupling and separating the joint error through a space-time separation method to obtain a static error component and a dynamic error component; performing iterative optimization on the optical distortion parameter and the mechanical disturbance parameter based on an optimization algorithm to minimize a system calibration error; a real-time sensor is utilized to obtain dynamic disturbance data, and real-time dynamic compensation is performed on an image calibration error in combination with an optimization result, so that a high-precision calibration result is obtained. The method can effectively improve the calibration precision of the microscopic system in a dynamic environment, remarkably improves the imaging quality of the system, and has a wide application prospect.

The invention discloses an image feature calibration method based on motion offset, and relates to the field of track detection image processing. The method comprises the steps of motion image acquisition, initial image calibration, fuzzy feature calibration and calibration image output. Acquiring real-time acceleration data through a train acceleration sensor, and converting the real-time acceleration data into pixel displacement deviation to realize preliminary calibration so as to obtain a reference processing image; based on historical database target features, separating a target body from an environment area, generating an environment point processing curve in combination with motion parameters, and screening a to-be-calibrated pixel set through feature fitting; a fuzzy feature calibration strategy is adopted to calibrate pixels and then fuse the calibrated pixels with a reference image, and the calibration precision is dynamically optimized through curve calibration and effect verification steps. Layered calibration is realized, the detail reduction degree of the moving image is improved, the environmental adaptability is enhanced, the target feature integrity is guaranteed, and the method is suitable for a rail transit image monitoring scene.

The invention discloses a self-adaptive system for industrial line-scan digital camera imaging, and relates to the technical field of imaging calibration, and the system comprises a machine vision collection module which is used for obtaining an image obtained by collecting a detected object through an industrial line-scan digital camera in a continuous steel belt production detection process; the control algorithm module is used for analyzing the image to obtain an analysis result; the communication control module is used for generating a target instruction for controlling the three-dimensional electric adjusting structure to move according to the analysis result; and the electrical structure adjusting module is used for adjusting the moving state of the three-dimensional electric adjusting structure according to the target instruction, so that the industrial line-scan digital camera acquires the image of the measured object at the target position. According to the invention, the control algorithm module performs optimization in real time according to the adjusted state while automatic correction is performed, the quality of the output image is ensured, and when the quality of the output image meets the design requirement, self-adaption is stopped.

The invention relates to the technical field of AR, and discloses an AR glasses image calibration method, device and system and AR glasses, and the system comprises a camera, an optical waveguide sheet, a glasses support and a controller. The camera is arranged on the glasses bracket, is connected with the controller and is used for collecting images displayed on the optical waveguide sheet; the controller is used for acquiring standard images and controlling the left optical waveguide sheet and the right optical waveguide sheet of the AR glasses to display the standard images respectively; controlling a camera to respectively collect standard images displayed by left and right optical waveguide sheets of the AR glasses to obtain left and right collected images; respectively judging whether the two acquired images are consistent with a standard image or not; if at least one acquired image is inconsistent with the standard image, calculating the offset between the acquired image and the standard image; and adjusting the display content of the optical waveguide sheet corresponding to the acquired image by using the offset. According to the method and the device, the effects of timely finding out the display inconsistency of the binocular images of the AR glasses and timely adjusting the inconsistent display content are achieved.

The invention provides an attitude measurement camera coordinate system calibration method, apparatus and device, and a storage medium, which can be applied to the technical field of measurement calibration. The method comprises the steps that a calibration plate is constructed, a conversion target seat and at least one reflective mark point are arranged on the calibration plate, the conversion target seat is used for placing a cube-corner prism target ball and a photogrammetry target ball, the cube-corner prism target ball and the photogrammetry target ball are the same in diameter, and the calibration plate is placed at different positions in a view field of an attitude measurement camera; the method comprises the following steps: acquiring three-dimensional coordinates of a cube-corner prism target ball by using a laser tracker, replacing a photogrammetric target ball, shooting an image of a calibration plate by using an attitude measurement camera to obtain the three-dimensional coordinates and a plurality of images of the cube-corner prism target ball in a laser tracker coordinate system, and calculating the three-dimensional coordinates of the cube-corner prism target ball according to the three-dimensional coordinates and the plurality of images of the cube-corner prism target ball in the laser tracker coordinate system. And calibrating a coordinate system of the attitude measurement camera. The extraction precision of the two-dimensional image coordinates of the target spot can be improved, and then the calibration precision of the coordinate system is improved.

The invention is suitable for the technical field of welding defect detection, and provides a welding defect detection method and system, and the method comprises the steps: constructing a region-of-interest extraction model, a permeability meter line model and a welding defect model based on a target detection algorithm; inputting a to-be-detected welding image into the region-of-interest extraction model to obtain a penetration meter region, a welding bead region and a positioning mark region; inputting the permeameter area into the permeameter line model to obtain a visible line detection result, and obtaining image calibration information based on the visible line detection result; the welding bead area is input into the welding defect model, and a defect detection result is obtained; based on the image calibration information and the positioning mark area, the defect detection result is mapped to the physical welding area, welding defects are positioned, automatic detection of welding production is achieved, and then the production quality of welding workpieces is improved.

The invention discloses a satellite-borne inverse synthetic aperture radar motion compensation imaging calibration integration method, equipment and a medium, and relates to the technical field of radar signal processing and radar imaging. The objective of the invention is to solve the problems of inaccurate motion compensation and difficult large-rotation-angle imaging in ISAR imaging. According to the method, a particle swarm optimization algorithm is adopted to optimize motion parameters, optimal motion parameters are obtained, and the motion parameters comprise relative translation motion parameters and relative rotation motion parameters of a target and a radar; and obtaining focusing and calibration imaging results based on the optimal motion parameters and echo data reflected by the target. The influence of the translation compensation effect on rotation parameter estimation is reduced, more accurate parameter estimation and better imaging focusing performance are realized, and the ISAR imaging problem under the condition of violent relative movement in the rendezvous scene is solved.

The invention provides a polyvinyl chloride sheet defect detection method and system based on image recognition, and relates to the technical field of quality detection.The method comprises the steps that a plurality of detection area coordinates are preset in an image acquisition system, and through position mapping and real-time image calibration of the plurality of detection area coordinates, the detection area coordinates are obtained; and aligning the actually shot image with the detection areas of the polyvinyl chloride sheet, and generating a final defect result according to a detection result obtained by identifying each detection area. According to the method and the device, the technical problem that the reliability of an overall quality evaluation result is affected due to the fact that the traditional image detection method is limited in sheet feature extraction capability, the defect recognition accuracy is not high and local anomaly is difficult to position is solved, and the reliability of the overall quality evaluation result is improved by constructing a multi-detection-area mapping mechanism based on a standard geometric template. And in combination with image registration, feature recognition and defect judgment algorithms, the detection precision of sheet defects is improved, so that the recognition accuracy of the quality state of the polyvinyl chloride sheet and the efficiency of the detection process are improved.

The invention discloses an oral cavity three-dimensional scanning system and a control method thereof, electronic equipment and a storage medium, and relates to the technical field of oral cavity three-dimensional scanning. The method comprises the following steps: controlling a projection module to alternately project white light and projection fringes generated based on Debrueine coding on a preset chessboard graph in different time periods towards a target; controlling the target to move, and controlling the imaging module to shoot a plurality of target images towards the target; the target image comprises a coding stripe image collected at the same position and a checkerboard image collected under white light; the multiple checkerboard images are calibrated to obtain imaging calibration parameters of the imaging module, meanwhile, after the multiple coded stripe images are calibrated to obtain projection calibration parameters of the projection module, a system calibration result is determined, and calibration is completed; and performing three-dimensional reconstruction processing based on the system calibration result on the to-be-reconstructed object to obtain a three-dimensional reconstruction result. The calibration efficiency and the calibration accuracy when the oral cavity three-dimensional scanning system is calibrated can be improved.

A camera system contains 3 or more identical cameras fixedly attached to a common platform and positioned in a manner with images of a pair of 2 cameras having overlap and defining an area of an image sensor that generates no overlap image data, called an active image sensor area. Image data generated by active image sensor areas being combined to an extended image space. Displaying a real-time panoramic video image based on the extended image space. Image data of a camera is undistorted by image calibration with a trained neural network. Determining active areas of image sensors with a convolutional neural network and reinforcement learning. Deriving an image window in the extended image space as an e-gimbal. Incorporating the cameras system in a portable and mobile housing.

The invention relates to the technical field of tunnel crack detection, and discloses a tunnel crack image identification method and a tunnel wall uniform image detection system. The method comprises the steps that tunnel images are collected, images belonging to cracks are calibrated to form an image set, and a crack target sample library is constructed; performing target detection identification on the collected tunnel image set, optimizing a target identification method according to an identification result, and outputting multiple tunnel crack disease detection images; extracting crack features from the collected tunnel image set; and based on the multiple tunnel crack disease detection images, performing pixel-level segmentation on the tunnel crack disease to complete tunnel crack identification. According to the invention, the traditional layout is broken, the requirements of closer shooting object distance and depth of field are met, and the detection requirement of smaller width of the welding seam is met; according to the algorithm level, a front image preprocessing part of deep learning training is optimized, especially contrast enhancement, multi-level fusion and the like are added, and the recognition accuracy of a tiny target can be further improved.

The invention discloses an unmanned aerial vehicle image calibration method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the image data of an unmanned aerial vehicle image, and carrying out the analysis of the image data, and obtaining the parameter information of the unmanned aerial vehicle image and the flight attitude information of an unmanned aerial vehicle; wherein the flight attitude information comprises a pitching angle, a rolling angle and a flight height; calculating the initial resolution of the image center point of the unmanned aerial vehicle image according to the parameter information and the flight height, and calculating the initial resolution of the image center point of the unmanned aerial vehicle image according to the initial resolution, the pitching angle, the rolling angle and the offset distance of each pixel point in the unmanned aerial vehicle image relative to the image center point. Calculating the actual resolution of each pixel point in the unmanned aerial vehicle image; and according to the actual resolution, calibrating the resolution of each pixel point in the unmanned aerial vehicle image to obtain a calibrated unmanned aerial vehicle image. According to the invention, the calibration precision of the unmanned aerial vehicle image can be improved.

The invention discloses an unmanned aerial vehicle inspection system and method for an intelligent street lamp based on multi-source video fusion, and relates to the technical field of unmanned aerial vehicle inspection, and the system comprises an inspection data collection module, an inspection image analysis module, an inspection mode switching module and an inspection task dynamic evaluation module. The inspection data acquisition module, the inspection image analysis module, the inspection mode switching module and the inspection task dynamic evaluation module are in communication connection with one another; wherein the inspection data acquisition module is used for performing flight inspection on street lamps in a target inspection area one by one through an unmanned aerial vehicle with a visible light camera, and setting image calibration array points to match the accuracy of inspection image acquisition; the inspection image analysis module is used for processing and analyzing the acquired image data; according to the invention, the problem that the inspection time consumption and the data processing burden are greatly increased in the existing multi-source image fusion processing mode is solved.

The invention discloses a car door collision reminding system and method based on fisheye camera image distortion correction, and relates to the technical field of car safety reminding. According to the system, scene images on the two sides of a car in the parking state are collected in real time through a fisheye camera, image calibration and distortion correction are carried out through an improved Harris corner detection algorithm, and the car door collision reminding system is obtained. In combination with a multi-task learning model of a convolutional neural network, the potential collision risk in the vehicle door opening process is analyzed in real time, the distance and height between an obstacle and a vehicle door are calculated through a signal processing module, a reminding module generates reminding signals of different grades, and the reminding signals are fed back to a driver in time through a vehicle display screen and a sound system. And the image display module marks the dangerous area and the dangerous level on the display equipment in real time. The system has wider visual angle coverage, higher detection precision and stronger environmental adaptability, effectively avoids the occurrence of vehicle door collision accidents, and is particularly suitable for narrow parking spaces, complex urban environments and high-density people flow areas.

The invention relates to the field of track detection, in particular to a vision-based rapid identification method for a target object in a track area, which comprises a target object image sampling step, a fuzzy database construction step, a sampled image calibration step and a target object rapid identification step. The problems of image blurring, multi-source errors and real-time performance under high-speed movement are systematically solved; the beneficial effects of efficiently coping with image blurring and dynamic interference, improving system robustness and detection coverage rate through a multi-camera cooperative calibration mechanism, adapting to a complex operation environment through a dynamic error elimination strategy, and improving detection reliability and safety are achieved.

The invention discloses an unmanned aerial vehicle surveying and mapping method and system based on three-dimensional point cloud data analysis, and relates to the technical field of unmanned aerial vehicle surveying and mapping. Determining the altitude of a key position node, and constructing an initial three-dimensional model; analyzing the laser data, generating a ground point cloud model, and screening an adjustment strategy with a high initial matching degree through proportional adjustment, rotation and translation optimization; and comparing the ground image with the surveying and mapping block features, determining a secondary matching degree, selecting an optimal point cloud model, and outputting data in combination with surveying and mapping marks. According to the method, GIS positioning, node modeling, point cloud optimization and image calibration are creatively fused, the complex terrain surveying and mapping precision is improved, and the method is suitable for the fields of engineering planning and the like.

This application provides a method for determining a wireless signal strength in an area, a computer-readable storage medium, and an electronic device. The method includes: obtaining building diagram information, wherein the building diagram information comprises a position of a target signal source, a target area, size information of one or more obstacles in the target area, type information of the one or more obstacles, and image calibration information; converting the building diagram information into a polar coordinate system; determining an attenuation amount of a target pixel based on the size information, the type information, the image calibration information, and a propagation path in the polar coordinate system, wherein the propagation path penetrates at least part of the one or more obstacles; and determining a signal strength of the target pixel based on a signal strength of the target signal source and the attenuation amount of the target pixel.

The embodiment of the invention is suitable for the technical field of medical imaging and image calibration, and provides an ultrasonic probe calibration method and system and electronic equipment, and the method comprises the steps: receiving an ultrasonic probe pose sequence and a calibration model pose sequence; receiving an ultrasonic image sequence; performing mark point identification and straight line identification on the ultrasonic image sequence to determine a first noise image and a second noise image in the ultrasonic image sequence; after the second noise image is deleted from the ultrasonic image sequence, time calibration is carried out on the ultrasonic probe, and a rate difference value between an ultrasonic probe displacement signal and an ultrasonic image displacement signal is obtained; and after deleting the first noise image from the ultrasonic image sequence, performing spatial pose calibration on the ultrasonic probe based on the rate difference value to obtain a spatial pose calibration matrix of the ultrasonic probe. By adopting the method, the calibration precision of the ultrasonic probe and the stability of the calibration result can be improved.

The invention discloses a micro-scale mixing effect induced carbonate precipitation rate coefficient calculation method, which comprises the following steps: S1, carrying out a micro-scale mixing effect induced carbonate precipitation visualization experiment to obtain a carbonate precipitation image data set; s2, establishing a carbonate precipitation identification model, wherein the carbonate precipitation identification model sequentially comprises three steps of image calibration, gray scale iteration adjustment and precipitation identification; s3, establishing a carbonate precipitation rate calculation model, wherein the carbonate precipitation rate calculation model sequentially comprises three steps of pixel point statistics, precipitation amount calculation and precipitation rate calculation; and S4, establishing a carbonate precipitation rate coefficient calculation model, wherein the model comprises precipitation rate analysis and precipitation rate coefficient calculation. The calculation of the rate coefficient of the carbonate precipitation induced by the mixing effect under the microscale is realized, and support is provided for understanding the carbonate precipitation mechanism in the karst area and improving the geological storage efficiency of carbon dioxide and the efficiency of calcium carbonate precipitation induced by microorganisms.

The invention discloses a diamond microstructure precision grinding system and method with visual positioning, and the method comprises the following steps: collecting a microscopic visual image, calibrating a visual coordinate system and a machine tool coordinate system, and building a unified positioning coordinate system; extracting composite visual features, constructing an energy field, performing adaptive partitioning, and generating risk partitioning codes; the risk partition codes are input into a double-flow network, grinding signals are input into grinding branches, and parameter tracks are generated; precisely grinding according to a segmented parameter track, reducing the cutting depth and the speed in a high potential energy area, and increasing the speed in a low potential energy area; after grinding, obtaining a three-dimensional shape, performing error analysis and energy spectrum generation, and mapping to risk partition coding; and according to the error energy and the energy field, the grinding priority is judged, and high-priority partitions are selectively ground and remeasured. According to the method, the visual potential energy field is constructed and the improved double-flow neural network is fused, so that accurate positioning, self-adaptive grinding control and high-precision micro-area grinding of the diamond microstructure are realized.

The invention discloses a structured light camera exposure duration prediction method based on RGB information. The method is divided into a camera calibration stage and a camera working stage. In a camera calibration stage, firstly, a two-dimensional color image calibration plate is shot with different exposure durations to obtain a corresponding two-dimensional color image sequence and a three-dimensional point cloud image sequence, and the two-dimensional color image sequence and the three-dimensional point cloud image sequence are used to calibrate a camera response function of RGB three channels of a camera and cut-off exposure of the RGB three-color channels corresponding to complete point cloud information. In the working stage of the camera, a two-dimensional color image sequence of a working scene is firstly shot, and the optimal exposure duration of the three-dimensional point cloud image of the structured light camera is calculated by using the camera data obtained in the calibration stage. The method provided by the invention has good adaptability to complex ambient light, and compared with manual adjustment of exposure duration, the three-dimensional point cloud imaging speed of the structured light camera adopting the method provided by the invention is greatly increased, and the imaging quality is obviously improved.

The invention provides a line-scan digital camera image-based high-precision calibration method, a measurement method and a system, and relates to the field of automatic optical measurement of plates, and the calibration method comprises the following steps: constructing a hardware mechanism for line-scan digital camera image calibration; acquiring a linear array camera image based on a hardware mechanism; performing distortion calibration on each line-scan digital camera based on the line-scan digital camera images so as to obtain reference point X coordinates, X-axis average precision, distortion correction coefficient arrays, working distances, grid numbers, Y longitudinal view offset pixels and Y longitudinal average precision corresponding to different intervals, wherein the reference point X coordinates, the X-axis average precision, the distortion correction coefficient arrays, the working distances, the grid numbers, the Y longitudinal view offset pixels and the Y longitudinal average precision correspond to different intervals; and performing multi-machine joint calibration on the plurality of line-scan digital cameras based on the line-scan digital camera images so as to obtain the proportion of the blind area width corresponding to different intervals to the height difference of the calibration plane. Calibration data are obtained on the basis of high-precision calibration, automatic optical detection is carried out on the thickness of the plate in combination with the calibration data, and the problems that existing plate size measurement is low in efficiency, poor in precision and poor in repeatability are solved.

The invention provides an intelligent image calibration system based on a vehicle-mounted AI, and the system comprises a vehicle-mounted image collection device, and also comprises an image marking subsystem and an image calibration subsystem. The image marking subsystem comprises an image screening module, an image processing module, a feature marking module and a feature construction module; the image calibration subsystem comprises a feature index module, an extraction marking module, a feature comparison module and a parameter correction module; element features are determined from environment image information of a scene point through an image marking subsystem, an element feature model is configured in advance, when a vehicle passes through a scenic spot again, an image calibration subsystem compares reference shooting features with actual shooting features to generate comparison difference information, then image parameters and position parameters at each moment are calibrated, and the scene point is obtained. And the image acquisition unit is configured in an optimal acquisition state, so that the reliability of vehicle image acquisition is improved, and support is provided for functions of intelligent driving, obstacle avoidance and the like.

The invention discloses a camera module image calibration method, relates to the technical field of electronic data processing, and aims to solve the problems that the calibration of a camera module cannot adapt to a changeable illumination environment and the consistency of the camera module is difficult to guarantee, and the method comprises the following steps: S1, obtaining a color temperature graph from the first color temperature to the Nth color temperature of a current module, each color temperature image is divided into a * b areas in a gridding mode; s2, calculating an R / G mean value and a B / G mean value of each region according to the image data of each region of each color temperature image of the current module; s3, screening out bad modules according to R / G and B / G ratios of the current module and the corresponding area of the typical module; s4, calculating AWB data and LSC data of the camera module from the first color temperature to the Nth color temperature according to the image data of the N color temperature graphs, and storing the AWB data and the LSC data in a memory; and S5, according to the actual environment illumination condition, automatically calling the AWB data and the LSC data, calculating a correction coefficient, and using the correction coefficient to calibrate the image, the camera module image calibration method not only can calibrate the color balance under different color temperatures, but also can significantly improve the consistency between modules, especially in large-scale production, the production efficiency is greatly improved, and the production cost is reduced. And the method is particularly effective for controlling bad modules.