113 results about "Calibration matrix" patented technology

The invention relates to a saline intrusion measurement method, system and equipment based on dynamic ship motion conditions and a medium, and aims to solve the technical problem that the salinity inversion precision is reduced due to spatial-temporal dislocation between particle image velocity measurement flow field data and plane laser-induced fluorescence concentration field data caused by ship six-degree-of-freedom motion. According to the method, future poses are predicted by collecting ship motion parameters and environment disturbance parameters, and space-time compensation parameters are generated in combination with a static calibration matrix; performing three-dimensional coordinate transformation and time synchronization on synchronously acquired original flow field and concentration field data by applying compensation parameters, and eliminating space-time deviation caused by ship movement; a three-dimensional salinity distribution field is calculated based on registration data fusion flow field diffusion characteristics and concentration field distribution; and meanwhile, the pose of the measuring equipment is dynamically adjusted through the closed-loop controller so as to optimize the data acquisition quality. According to the method, ship motion interference is effectively inhibited, and accurate characterization of saline invasion frontal surface spatial characteristics is guaranteed.

The invention discloses a transformer substation intelligent patrol recognition algorithm optimization method based on multi-modal fusion, and belongs to the technical field of transformer substation patrol, and the method comprises the following steps: synchronously obtaining a visible light image, an infrared thermal imaging spectrum, an ultrasonic partial discharge signal and environmental parameters, and building a four-dimensional space-time calibration matrix; a dual-channel attention mechanism is adopted to realize multi-source data fusion, a spatial alignment channel and a feature enhancement channel are included, the spatial alignment channel realizes pixel-level registration of visible light and infrared images through affine transformation, and the feature enhancement channel utilizes a graph neural network to construct topological correlation mapping of acoustic, thermal and optical features; constructing a three-stage training architecture containing noise injection; and adding an adversarial generative network in a preprocessing layer to simulate rain fog and electromagnetic interference environments. According to the method, the identification threshold is updated online by deploying a sliding time window mechanism in an output layer, and the problems of poor feature extraction robustness and high false alarm rate of a traditional algorithm in complex environments such as strong electromagnetic fields and rain and fog are solved.

The invention belongs to the technical field of medical robots, and discloses a surgical robot accurate pose real-time registration method and system based on multi-sensor fusion, and the system comprises a multi-source sensing collection assembly; a time-space calibration mechanism; fusing a resolving platform and an exception elimination platform; a deformation sensing and dynamic compensation device; and a registration result closed-loop feedback unit. According to the invention, a multi-source sensing acquisition assembly and a synchronous control board are integrated on a hardware level, a nanosecond timestamp is generated by using a high-precision clock driven by an onboard crystal oscillator, and a cross-correlation delay calculation chip is combined to execute a cross-correlation function method delay estimation formula, so that microsecond-level accurate correction of delay amount among sensing sources is realized; the coordinate transformation unit automatically selects a matched calibration matrix according to a correction result, multi-source data such as optical positioning, inertial measurement, a torque sensor, ultrasonic or electromagnetic positioning and the like are unified to a global rectangular coordinate system, and the structure can effectively ensure the consistency of time and space references of data output by different sensors.

According to the robot vision calibration device and method, through collaborative design of the industrial personal computer, the vision system, the robot, the calibration jig and the calibration plate, the problems caused by complex structure, low calibration precision and poor adaptability in the prior art are solved. A floating mechanism of the calibration jig is combined with a displacement sensor to realize multi-degree-of-freedom dynamic displacement compensation, so that mechanical positioning errors are remarkably reduced; the conical surface guide structure and the reference hole layout of the calibration plate optimize the stability of the positioning reference, and ensure the accurate embedding of the calibration needle. The flexible installation of the visual system adapts to different scene requirements. According to the calibration method, the generation of a high-precision visual calibration matrix is realized through the processes of multi-reference hole coordinate recording, calibration ring coordinate calculation and visual image acquisition and matching. According to the whole scheme, through a dynamic compensation mechanism and intelligent process design, the calibration precision, efficiency and robustness are improved, meanwhile, the operation complexity is reduced, and reliable technical support is provided for an industrial automation scene.

The invention discloses a three-dimensional calibration automatic system suitable for a six-axis physiotherapy robot, and relates to the technical field of robot vision calibration and automatic control, and the system comprises an equipment communication management module which automatically identifies and distributes connection equipment through an intelligent detection technology, and outputs an equipment control instruction; the data acquisition and processing module is used for identifying 13-point feature pixels through RGB information, performing deep matching, calculating 13-point theoretical feature three-dimensional information and outputting an optimized calibration matrix MB2R in combination with a transformation relation between the camera and the tail end of the mechanical arm and a base coordinate transformation relation; and the result verification and backup uploading module is used for converting the relative position of the three-dimensional feature platform and the robot, acquiring three-dimensional information of an evaluation point, controlling the mechanical arm to move to an optimization point position, and calculating a pixel difference value and a height difference value. The method has the advantages that full-automatic millimeter-level calibration precision is achieved through a collaborative structure of multi-protocol heterogeneous equipment intelligent integration, iterative optimization algorithm fitting and closed-loop double-index verification.

The invention discloses a mechanical arm intelligent grabbing system and method based on three-dimensional vision. The system comprises a three-dimensional vision system, an image preprocessing module, a model matching module, a grabbing point generation module, a grabbing control module and a dynamic environment self-adaption module. The method comprises the steps of multi-modal reference model collection and feature library establishment, precise hand-eye calibration and grabbing strategy self-learning and multi-modal fusion recognition, and dynamic prediction and self-adaptive grabbing. By adopting the three-dimensional visual recognition system and combining algorithms such as point cloud processing, point cloud method phase generation, point cloud downsampling, rough model matching and fine model matching, the limitation that a traditional mechanical arm system depends on two-dimensional image training and position coordinate point matching is overcome; by generating the grabbing points and calculating the pose coordinates of the grabbing points according to the hand-eye calibration matrix, the problem that the estimated pose of the grabbed object under the camera coordinate system is inaccurate in the prior art is solved. The system is easy to implement and has high practicability and popularization value.

The embodiment of the invention provides a robot control method and system based on virtual reality and hand motion capture, and the method comprises the steps: collecting the hand posture data of a user, obtaining the first hand posture data of the user through a virtual reality device, the first hand posture data comprises the hand end posture information, and obtaining the first hand posture data of the user through a virtual reality device; obtaining second hand posture data of the user through wearable hand motion capture equipment, wherein the second hand posture data comprises hand joint fine motion information; standardizing the hand position and posture data, and mapping the hand position and posture data into robot target motion data based on a preset calibration matrix, the robot target motion data including first robot target motion data mapped based on the first hand position and posture data and second robot target motion data mapped based on the second hand position and posture data; robot motion control data is generated based on the robot target motion data, and robot parts are controlled to move. According to the robot control method and system based on virtual reality and hand motion capture, the operation precision of the robot can be greatly improved, the operation real-time performance and smoothness are enhanced, and the motion state of the robot can be monitored in real time.

Techniques are provided for real-time calibration of an eye-tracking system in a wearable display device using user interactions with a graphical user interface. A background calibration process continuously or intermittently updates a calibration matrix based on stable gaze-target pairs inferred from natural user behavior, without requiring explicit calibration routines. The system detects user interactions such as selections of UI elements, and associates them with gaze direction data captured immediately beforehand. Fixation filtering is applied to identify stable gaze intervals based on dispersion thresholds and minimum duration criteria.

The invention belongs to the technical field of intelligent traffic sensor calibration, and particularly relates to an end-to-end thunder all-in-one machine automatic calibration system and method based on deep learning, and the system comprises a data collection module, an image target detection module and a calibration network module. The system collects images and three-dimensional coordinates of a target point through a camera and a radar. Identifying a target in the image by using a deep learning model and acquiring pixel coordinates; and the calibration network learns the mapping relation between the image and the radar point, and directly outputs a high-precision calibration matrix T. According to the method, end-to-end automatic calibration in the whole process is achieved, manual arrangement of calibration plates or selection of corresponding points is not needed, efficiency is remarkably improved, and stable operation can be achieved in complex scenes such as dynamic traffic flow, night and rainy days. Through deep fusion of the high-dimensional features of the Leiyu, error accumulation of step-by-step calibration is effectively avoided, the projection error can be controlled within 5 pixels, and the high-precision sensing requirement of intelligent traffic is met.

An automatic end effector tip position initialization mechanism for a micromanipulation system is provided. The method includes: S1, positioning a macro end effector tip, calculating a camera pose by using ArUco Tag, and realizing a three-dimensional positioning of the end effector tip by using a triangulation method, and moving the end effector to a area near a center of a focal plane based on a visual servo; S2, positioning a micro end effector tip; S3, acquiring calibration data based on a visual servo, calibrating the end effector tip and the petri dish, and obtaining a left calibration matrix and a right calibration matrix reflecting the transformation relationship between left and right micromanipulator coordinates and image coordinates; generating an intuitive human-computer interaction interface based on a mouse and a keyboard according to acquired position information. The method has obvious advantages in terms of operation accuracy, operation efficiency and repeatability.

The invention discloses a dynamic environment multi-line radar calibration method and system, and relates to the technical field of road radars, and the system comprises a dynamic reference field generation unit which is disposed on the ground of a radar coverage area, is composed of a reflection target array with known space coordinates, and is adjustable in target distance, and a multi-line laser radar unit which is provided with a horizontal field angle of not less than 120 degrees, and is provided with a multi-line laser radar unit. The number of lines in the vertical direction is larger than or equal to 128 lines per frame, the radar body is installed on the portal frame and connected with the control device, the environmental parameter sensing unit collects the temperature, three-dimensional acceleration and power supply voltage data of the radar body in real time, and the distortion compensation module constructs a space distortion field model based on real-time point cloud feedback and environmental parameters of a dynamic reference field, outputs a calibration matrix and outputs the calibration matrix. And the multi-radar collaborative calibration module is used for synchronizing space-time reference through a PTP protocol. Through a real-time compensation mechanism driven by environmental parameters, vibration acceleration and temperature change data are converted into space coordinate correction, and high-precision stable measurement in a dynamic environment is achieved.

The embodiment of the invention provides a phase focusing method, electronic equipment, a storage medium and a program product, and is applied to the technical field of electronics. According to the method, under the condition that an optical anti-shake module is started, a first phase image collected by a phase detection pixel and a first coordinate of the position where the optical anti-shake module is located at a target moment are obtained, and a phase gain compensation matrix is determined according to the first coordinate and a plurality of phase gain calibration matrixes; the relative positions of the optical center of the lens and the optical center of the image sensor are different when the plurality of phase gain calibration matrixes are calibrated, the phase gain compensation matrix is adopted to compensate the first phase image, and phase focusing is carried out based on a second phase image obtained after compensation. Therefore, according to the embodiment of the invention, the brightness value of the pixel in the second phase image obtained after compensation can be more uniform, so that the phase difference information determined based on the second phase image is more accurate, and the focusing stability and the focusing accuracy in an optical anti-shake mode are improved.

The invention relates to the technical field of multi-spectral colorimeter inter-table difference reduction, and discloses a method and device for reducing multi-spectral colorimeter inter-table difference, electronic equipment and a medium, and the method comprises the steps: measuring a set number of color cards to obtain measurement matrixes of different colorimeters, and then selecting one colorimeter from the preset colorimeter group as a standard colorimeter, taking the rest colorimeters as to-be-calibrated colorimeters, and establishing a conversion relation between the standard measurement matrix and the to-be-calibrated matrix. The method has the beneficial effects that the consistency between the to-be-calibrated colorimeter and the standard colorimeter is greatly improved, the calibration procedure is simplified, the reliability and consistency of the calibrated colorimeter in practical application are also improved, the applicability of the multispectral sensor in the corresponding color measurement field is enhanced, and the method is suitable for popularization and application. The cost performance and application universality of the multispectral colorimeter are remarkably improved, and a more stable and accurate color measurement solution is provided for various industries.

The invention provides a string tomato picking robot carpopodium instance segmentation method and system. The method comprises the following steps: constructing a string tomato carpopodium data set and performing enhancement preprocessing; establishing a YOLO11-FFTDA instance segmentation model, performing feature extraction by using a feature pyramid comprising a frequency pyramid attention module in a backbone network, and enhancing frequency domain edge details through fast Fourier transform; a C2PSADA mixed attention module is introduced in the neck network fusion stage, and adaptive sampling points are generated by using a deformable attention mechanism so as to fit the geometrical morphology of the carpopodium and suppress background noise; meanwhile, an independent high-resolution branch is led out to capture a tiny target; and outputting the types, bounding boxes and masks of fruit stems through a decoupling segmentation head, extracting a skeleton center based on the masks to calculate an optimal cutting point, and combining with a hand-eye calibration matrix to realize precise positioning and picking of the mechanical arm. According to the invention, closed-loop control from visual perception to physical operation is realized, and the operation success rate and environmental adaptability of the skewered tomato picking robot are remarkably improved.

The embodiment of the invention discloses a camera and radar external parameter optimization method based on a working site moving target, and the method comprises the steps: collecting a continuous frame image and a point cloud, and extracting an image moving target and a point cloud moving target through an optical flow method and a frame difference method; projecting a moving target to an image by using an existing calibration matrix, performing rigid body transformation matching, and storing a matching result into M; image and point cloud edge features are extracted and obtained through matching; and obtaining an external parameter by using a PNP algorithm, calculating an error, outputting the error if the error reaches the standard, otherwise, rejecting the error and repeating feature matching and subsequent steps. According to the method, iterative optimization of the external parameter matrix is carried out by using the point cloud and image features of the moving target, the moving target with a large error is eliminated, camera and laser radar external parameter calibration based on any scene moving target is realized, the problems that calibration depends on a calibration board and external parameter correction cannot be carried out in the field use process are effectively solved, and the calibration accuracy is improved. And the measurement requirements of the transformer substation can be well met.

The invention belongs to the field of geophysical exploration, and particularly relates to a very-low-frequency three-component coil calibration method based on frequency sweep excitation, which comprises the following steps: acquiring an alternating-current excitation current and a time domain signal of a three-component coil, and performing frequency domain transformation on the time domain signal to obtain a plurality of frequency domain response vectors covering a frequency sweep range; constructing a linear equation set for describing a coil system error based on a plurality of frequency domain response vectors measured under each attitude and the calculated excitation magnetic field reference vector, and solving the linear equation set by using a least square method to obtain a calibration matrix for correcting measurement data; and the calibration matrix is adopted to correct the measurement data of the three-component coil in the use state, so that systematic errors of the very-low-frequency three-component coil can be accurately calibrated and calibrated, and the measurement precision and data reliability of a very-low-frequency electromagnetic method are effectively improved.

The invention provides a chromaticity calibration method, device and equipment based on color classification and brightness segmentation. The method comprises the following steps: acquiring a sensor measurement value of a current display picture of a display through a chromaticity sensor; extracting chromaticity features and brightness features of a current display picture according to the sensor measurement value; determining a color category and a brightness category of the current display picture according to a preset category discrimination strategy based on the chromaticity feature and the brightness feature; determining a calibration matrix of the current display picture according to a pre-stored calibration matrix mapping table based on the color category and the brightness category; and performing linear transformation on the sensor measurement value according to the calibration matrix to obtain a corresponding measurement calibration value. Through color and brightness two-dimensional classification and exclusive calibration matrix adaptation, full-color-gamut and full-brightness refined calibration is realized, the color deviation of the full-color gamut is remarkably reduced, and the color rendition precision and the brightness consistency are improved.

The invention discloses an automatic mounting method and system for a cambered surface wood board based on dynamic point cloud analysis, and the method comprises the steps: building a joint coordinate system of a mechanical arm and point cloud collection equipment, and obtaining a calibration matrix through a specific motion track of the mechanical arm; carrying out initial scanning on the cambered surface substrate on which the wood board is not mounted, and carrying out single-side arc fitting by utilizing a single-side point cloud fitting algorithm to obtain an initial circle center coordinate and a radius; entering a dynamic installation cycle, collecting local point cloud data of the current installation area, and executing Z value mutation feature detection to identify the edge position of the installed part; calculating an actual installation deviation based on the edge position, and dynamically compensating a pose parameter of the wood board to be installed according to the deviation; and according to the cambered surface radius updated in real time, the installation number of the remaining wood boards is adjusted in a self-adaptive mode, and control instructions of the to-be-installed wood boards are generated in batches and sent to the mechanical arm to be installed till all laying is completed. According to the invention, the installation precision and the engineering efficiency of cambered surface packaging are obviously improved.

Provided is an apparatus for assisting driving of a vehicle, the apparatus including: a camera mounted on the vehicle and configured to have a front field of view of the vehicle and acquire image data; a lidar mounted on the vehicle and configured to have a front-side field of view of the vehicle and acquire lidar data; and a controller configured to process at least one of the image data or the lidar data, wherein the controller includes a calibration matrix for correcting the image data and the lidar data and is configured to: obtain a feature map of the image data and a feature map of the lidar data using machine learning; correct the calibration matrix based on a difference between the feature map of the image data and the feature map of the lidar data; and correct the image data and the lidar data using the corrected calibration matrix.

The present application relates to the field of intelligent garbage sorting, and discloses a robot hand-eye calibration method for intelligent garbage sorting, comprising the following steps: Step 1, system initialization, configuration of robot, visual sensor and conveyor belt parameters; Step 2, garbage is transported to the sorting area via a conveyor belt, and the location and category of the garbage are identified by machine vision; Step 3, based on the identification result, the robot controls the metal suction cup to grab the garbage and perform the sorting operation; Step 4, during the sorting process, the target point data of the visual coordinate system and the robot coordinate system are obtained, and the hand-eye calibration matrix is ​​optimized by the H∞ robust control theory; Step 5, the Riemann manifold optimization method is used to perform gradient descent iteration in the manifold space of the rigid body transformation matrix, and by adopting a real-time fault detection technical solution based on sensor networks and data analysis, and by real-time monitoring and fault warning of key components, the technical effect of improving the stability of the garbage sorting system is achieved.

Embodiments of the present application provide a motion mechanism control method and device, electronic equipment and storage medium, and relate to the technical field of robots. The specific solutions are as follows: a current image pose of an object to be grabbed by a motion mechanism in an image collected by an image collection device is obtained; a rotation angle difference between the current image pose and a reference image pose of the object is determined; a translation deviation of the motion mechanism from a first physical position of the reference image pose in a physical coordinate system to a second physical position of the current image pose in the physical coordinate system is determined according to the current image pose, the reference image pose, a calibration matrix, a skew matrix and the rotation angle difference, the calibration matrix representing a transformation relationship between a pixel coordinate system and the physical coordinate system, and the skew matrix representing a transformation relationship between the physical coordinate system and an orthogonal coordinate system; and the motion mechanism is controlled to move according to the translation deviation. The application of the solutions provided in the embodiments of the present application can reduce the error when the motion mechanism is controlled to move.

The invention provides a performance optimization method of an electric power 5G-Advanced communication and inductance integrated wireless control system, and belongs to the technical field of electric power 5G-A networks. Comprising the following steps: through orthogonal reference signal switching, respectively carrying out transmitting and receiving channel calibration on a base station and a first straight-through user side, and generating a corresponding calibration matrix; jointly estimating an uplink channel and an interference channel of the cellular user and the second straight-through user by using the orthogonal DMRS; compensating an estimation channel based on the calibration matrix, constructing an interference covariance matrix and generating an MMSE precoding vector; respectively mapping downlink data of a cellular user and straight-through data of a straight-through user to an airspace, and combining the calibration matrix and the precoding vector to carry out airspace filtering processing to generate a synchronous transmission signal; and transmitting the synchronous transmission signal in the same resource block, and performing interference suppression decoding on the basis of the compensated channel by a receiving end. According to the method, the performance of the wireless control system can be optimized by combining subcarrier-level channel compensation with dynamic construction of the spatial filtering matrix.

The invention discloses a color correction method and system, and belongs to the technical field of image processing, and the method comprises the steps: extracting a chromaticity quantization DCT coefficient, an initial chromaticity quantization table and a standard color card calibration matrix of a compressed image; wherein the chroma quantization DCT coefficient comprises a DCT coefficient of a blue chroma component and a DCT coefficient of a red chroma component; generating a chromaticity correction matrix according to the DCT coefficient of the blue chromaticity component of the compressed image, the DCT coefficient of the red chromaticity component of the compressed image and the standard color card calibration matrix; correcting the frequency domain chromaticity of the compressed image according to the chromaticity correction matrix; generating a final chroma quantization DCT coefficient according to the initial chroma quantization table and the chroma correction matrix; outputting a compressed image code stream according to the final chromaticity quantization DCT coefficient and the entropy coding table; according to the method, chromaticity correction is directly carried out in the frequency domain of the compressed image, quantization table optimization and chromaticity statistical feature modeling are combined, the problems of calculation complexity and distortion caused by decompression processing are avoided, and the color fidelity of the compressed image is improved.

The application discloses an endoscope image electronic staining method, device, system and storage medium. The method extends an original wideband RGB image into a P-dimensional wideband image, and for each pixel point of a current frame: based on a current image block, a reference image block set is obtained by searching for reference image blocks in the current frame and K frames before and after the current frame; according to the similarity distance between each reference image block and the current image block, the image attenuation weight of each image block is determined, the image blocks are fused and weighted, and the RGB light reflectivity estimation data of the pixel point is obtained; based on the calibration matrix of the wideband image and the narrowband image, the narrowband light image signal data corresponding to the estimation data is obtained; based on the narrowband light image signal data of each pixel point, a narrowband image of the current frame is generated, and an electronic staining image is synthesized based on the narrowband image. The approximate imaging result of narrowband light illumination can be realized through software, so that better lesion observation effect is obtained at low cost.

The application provides a distributed picture distortion correction method, system, electronic equipment and storage medium, and the method comprises the following steps: obtaining a distortion calibration matrix of a target camera according to a chessboard picture; creating an RDD (Resilient Distributed Datasets) task according to a plurality of pictures to be corrected in an HDFS (Hadoop Distributed File System); correcting each picture to be corrected in the RDD task by using a foreach operator according to the distortion calibration matrix; and uploading the corrected picture to the HDFS until the correction of all the pictures to be corrected is completed. The application corrects each picture to be corrected in the RDD task by using the foreach operator according to the distortion calibration matrix to obtain a corrected picture, thereby combining the distortion calibration matrix with big data picture processing, achieving the purpose of simultaneously correcting a large number of distorted pictures in batches, and greatly improving the picture correction efficiency.

The application discloses a kind of human motion digital twin construction methods based on inertial action capture technology.Firstly, action capture device is worn on human body, and the original sensing data of each joint corresponding sensor is collected, the original sensing data is processed using adaptive extended Kalman filter algorithm, the attitude of each joint corresponding sensor is obtained, and the original sensing data and sensor attitude data are sent to host computer;Host computer constructs human motion digital twin model according to human skeleton;The attitude calibration matrix of each joint is calculated using human posture calibration method, and the real-time sensor attitude data is calibrated to obtain the attitude of each joint of human body, drive human motion digital twin model;While driving the model, the joint parameters calculated are compared with human joint parameter threshold, and the evolution model is dynamically updated.The application can realize that human motion digital twin model is synchronously mapped real human motion, and model is updated in real time dynamically.

The present application relates to meteorological detection technical field, specifically, it relates to a kind of airborne laser wind measurement radar and cloud precipitation detection coordination system. Including: intelligent sensing detection unit;Particle swarm algorithm data processing unit, the particle swarm algorithm data processing unit constructs multi-physical quantity coupling dynamic calibration model;Coordination control regulation unit.The present application is aimed at airborne scene, based on wind field gradient modulation, body vibration optical axis jitter, temperature and pressure wavelength shift three major physical mechanisms, constructs multi-physical quantity coupling dynamic calibration model, quantifies error coefficient and builds high-dimensional calibration matrix;Using the improved particle swarm algorithm of fusion multi-dimension coding, dynamic inertia weight, local optimal escape factor and beibu restraints, according to laser echo signal-to-noise ratio grading frequency band, share calibration parameter completes synchronous solution, realizes multi-error unified modeling and accurate correction, synchronous completion coordination inversion and noise reduction, improves the stability and reliability of detection data solution.

Embodiments of the present application provide a camera calibration method and device, electronic equipment and storage medium, and relate to the technical field of computer images. The method comprises: constructing a translation calibration matrix; controlling the end effector to rotate to a first auxiliary position where the calibration object is located outside the field of view of the camera; controlling the end effector to translate to a second auxiliary position where the calibration object is located within the field of view of the camera, and controlling the camera to take a picture at the second auxiliary position to obtain an auxiliary image; determining virtual coordinates of the end effector at the first auxiliary position and calibration object pixel coordinates by using pixel coordinates in the auxiliary image, first and second auxiliary position physical coordinates, and the translation calibration matrix; fitting a plurality of virtual coordinates and a plurality of first auxiliary position physical coordinates to obtain a mechanism rotation center; and determining a calibration result by using the mechanism rotation center and the translation calibration matrix. The scheme provided by the embodiments of the present application can improve the accuracy of camera calibration in a small field of view environment.

Methods and systems for wavelength standardization. In some implementations, a method for standardizing wavelength measurements taken from a multi-channel detector may comprise obtaining an idealized matrix associated with a detector, such as a blood analyte detector. The idealized matrix may comprise fixed data corresponding to a fictional, ideal version of the detector. A calibration matrix associated with the detector may be obtained from measurement data taken from the detector. A pseudoinverse of the calibration matrix may be taken and the idealized matrix may be multiplied by the pseudoinverse of the calibration matrix to obtain a wavelength standardization matrix. Multi-channel spectral signal data, such as data from a plethysmography signal, may be received from the detector. A vector may be defined using the signal data and the vector may be updated using the wavelength standardization matrix.

This invention discloses a microfluidic chip imaging and positioning device and method, belonging to the field of microfluidic chip positioning technology. The technical solution includes: taking a picture of the microfluidic chip using a macroscopic camera and performing distortion correction; identifying the microfluidic chip's marker points or channels based on a microfluidic chip marker point or channel recognition model; performing coordinate transformation based on a calibration matrix to obtain the set of pixel coordinates in the microscopic camera coordinates, which is the positioning coordinate set of the microfluidic chip; and obtaining the coordinates of any position of the microfluidic chip from the positioning coordinate set, thus completing the imaging and positioning of the microfluidic chip. This invention is applied to microfluidic chip imaging and positioning, solving the drawbacks of existing microfluidic chip fixtures and addressing the technical problems of universality, automation, and high precision in microfluidic chip positioning. It features speed, automation, high precision, and universality.