37 results about "Image registration algorithm" patented technology

The invention relates to the technical field of computer vision, and discloses a jade defect intelligent detection method and system based on machine vision and deep learning, and the method comprises the following steps: S1, based on a high-resolution industrial camera and a laser three-dimensional scanner, adopting a multi-mode synchronous collection strategy, and rotating a jade sample through a precise motion control system, a jade surface high-resolution two-dimensional color image and high-precision three-dimensional point cloud data are respectively obtained, and a jade multi-mode original data set is generated. A high-resolution two-dimensional color image and high-precision three-dimensional point cloud data are integrated through a multi-modal synchronous acquisition strategy, and multi-dimensional feature expression under unified coordinates is constructed, so that the limitation of a single data source is effectively overcome; an image registration algorithm and a feature pyramid network are combined with a point cloud network to perform multi-modal feature fusion, complementarity of color texture and geometric morphology information is enhanced, and image quality is optimized based on adaptive histogram equalization and non-local mean filtering.

The invention discloses a power line identification method, device and equipment based on image fusion and a medium, and the method comprises the steps: obtaining an infrared image and a visible light image of a power line of a power distribution network, and carrying out the registration of the infrared image and the visible light image through a preset image registration algorithm, and generating a first image; wherein the infrared image and the visible light image are derived from the same picture; performing feature extraction and feature fusion on the first image and the visible light image through a preset image fusion algorithm to generate a second image; and performing power line identification on the second image through a preset power line identification algorithm. According to the method, the infrared image and the visible light image which are derived from the same power line picture are fused to obtain the fused image which contains more source information and has more obvious power line characteristics, so that power line recognition is performed, the difficulty of power line recognition is greatly reduced, and the accuracy of power line recognition of the power distribution network is further improved.

The application relates to an airplane change detection method based on a deep learning and an image registration algorithm, and the method comprises the following steps: acquiring a first remote sensing image and a second remote sensing image of the same region at different time points; performing airport detection on the first remote sensing image and the second remote sensing image to obtain an image of a first airport region in the first remote sensing image, a first offset of the first airport region, an image of a second airport region in the second remote sensing image and a second offset of the second airport region; performing image registration on the image of the first airport region and the image of the second airport region according to a surf image registration algorithm to obtain a registration image; performing airplane detection on the registration image to obtain an airplane target; performing change detection on the result obtained by the airplane detection; and restoring a target frame corresponding to the airplane target to the first remote sensing image and the second remote sensing image. The application can solve the problems of low detection precision, slow detection process running speed and large hardware resource occupation in the prior art.

The present description relates to an image sequence motion correction method and apparatus based on intensity correction optical flow registration. The method comprises: determining a reference image of each deformed image in a deformed-image sequence, and performing motion correction on the deformed image by means of adjusting the weight of a mechanical regularization term between the reference image and the deformed image, so as to obtain a displacement field of the deformed image relative to the reference image; on the basis of the displacement field and an intensity correction value of a finite element node, performing intensity correction on the reference image; adjusting the weight of the mechanical regularization term, performing motion correction on the deformed image, performing intensity correction on a first corrected reference image on the basis of an optimized displacement field, repeatedly executing the process until an image residual function converges, determining that the deformed image has been corrected, and recording the optimal solution of a weight value of the mechanical regularization term of the deformed image; and on the basis of the optimal solution of the weight value, determining the actual displacement of the deformed image. In the present description, the mechanical model behind physiological motion and an intensity correction technique are integrated into an image registration algorithm to reduce image noise, thereby improving the algorithm accuracy.

The invention relates to the technical field of textile double-sided printing, in particular to a high-permeability and double-sided positioning printing method for all-cotton towel products, which comprises the following steps: pre-treating all-cotton towel gray cloth, including desizing, scouring and bleaching procedures; padding the treated gray cloth in slurry containing urea, sodium bicarbonate, anhydrous sodium sulphate and a penetrant, and then drying and sizing; printing on the front surface of the towel by adopting a digital printing machine, and spraying a penetrating agent with the surface tension of 25-35mN / m to a printing area through an independent jet printing channel, so as to promote the dye to fully permeate to the back surface of the fabric and form a clear pattern outline; according to the invention, an image acquisition system composed of an industrial camera, an annular LED coaxial light source and a polarization filter captures fabric back pattern contour features in real time, and generates a translation, rotation and zooming transformation matrix based on an image registration algorithm; in combination with closed-loop feedback control of the digital printing machine, the positioning precision is improved by more than 75% compared with a traditional method.

The application provides a pinhole image splicing true value acquisition and splicing method based on a heterogeneous camera combination. The acquisition method first symmetrically installs two pinhole cameras on a support, and installs an fisheye camera between the two pinhole cameras. Based on a double spherical camera model, the three cameras are calibrated to obtain the internal parameters and external parameters of the three cameras. The left eye pinhole view, the right eye pinhole view and the middle eye fisheye view of the target scene are simultaneously acquired by using the three cameras. The middle eye fisheye view is subjected to equirectangular projection. According to the internal parameters and external parameters of the three cameras, the left eye pinhole view and the right eye pinhole view are projected to the equirectangular projection view plane respectively, multi-camera coordinate system one is completed, and the splicing true value is obtained. The application has the core advantages of the hardware structure design and the heterogeneous camera image registration algorithm, can stably acquire images without seams and time sequence consistency, and provides strong support for the true value reference of the precision verification and model training of subsequent panoramic video splicing.

Some embodiments of the present disclosure provide a method, device and computer readable medium for identifying an analog instrument, the method comprising: inputting a first instrument panel image to be tested into a first neural network model, and outputting the first instrument panel image; extracting feature points of the first instrument panel image, and performing feature point registration on the first instrument panel and a standard instrument panel based on an image registration algorithm, and outputting a second instrument panel image after registration; inputting the second instrument panel image into a second neural network model, and outputting pointer position information on the second instrument panel image; and calculating a reading of the analog instrument based on the pointer position information. Embodiments of the present disclosure achieve identification and reading of the analog instrument based on an improved neural network model.

This invention discloses a multimodal image real-time registration and fusion system and method for cardiac interventional surgery, comprising: a multimodal image acquisition module, an image data transmission module, an intraoperative twin image registration and analysis platform, an algorithm calculation module, a parameter adjustment module, and an image fusion output module. After acquiring image data, the multimodal image acquisition module sends it to the intraoperative twin image registration and analysis platform via the image data transmission module. The platform incorporates a cardiac deformation adaptive optical flow algorithm, a multi-resolution hierarchical mapping algorithm, and a large-deformation cardiac image registration algorithm. The algorithm calculation module performs registration calculations, and the parameter adjustment module optimizes the fusion parameters based on the calculation results. Finally, the image fusion output module generates and outputs the fused image. This invention achieves real-time and accurate multimodal image registration and fusion, providing reliable image support for cardiac interventional surgery and improving surgical accuracy and safety.

The invention relates to the field of image recognition, in particular to an in-transit transportation abnormity intelligent early warning system for an intelligent supply chain. The visual information acquisition module is used for acquiring land visual representation, vehicle motion time sequence signals, operation flow time sequence and intersection point visual representation; the morphological correlation model construction module is used for outputting seaport scene visual representation through semantic segmentation; outputting a sea-land intersection point form correlation model through an image registration algorithm; the event attribution module is used for adding the vehicle motion time sequence signal and the sea transportation environment data to the sea-land intersection point form correlation model to obtain sea-land visual time sequence representation; performing feature analysis to obtain attribution judgment; generating a transportation event attribution heat map through a feature attribution algorithm; and the risk judgment module is used for generating an early warning signal when the cause is judged to be damage and the visual activation degree is lower than a threshold value. According to the method, end-to-end multi-dimensional coupling from geometric modeling to space-time attribution to risk decision is carried out, so that the logicality and credibility during damage distinguishing are improved.

The invention relates to the technical field of industrial machine vision detection, in particular to an intelligent grading and feedback system based on image recognition. Comprising a multi-modal image acquisition unit used for synchronously acquiring a visible light image, an infrared thermal imaging image and a hyperspectral image of a target object; the dynamic self-adaptive preprocessing unit is in communication connection with the multi-modal image acquisition unit, performs combined preprocessing on the acquired multi-modal image, and comprises a dynamic noise reduction algorithm based on target edge features, a self-adaptive contrast enhancement algorithm and a multi-modal image registration algorithm; and the closed-loop feedback unit is respectively in communication connection with the multi-modal image acquisition unit and the multi-dimensional dynamic threshold grading unit. Through multi-modal image acquisition and attention-multi-scale feature fusion design, the limitation of traditional single-modal detection is effectively broken through, the recognition capability of micro bubbles and hidden cracks of the quartz crucible is remarkably improved, surface stains and internal impurities are accurately distinguished, and the problem of subjective difference of manual visual detection is solved.

The invention relates to the technical field of biological imaging, and discloses a macromolecular morphology restoration method based on microscopic imaging, which can achieve accurate restoration of macromolecular morphology more simply and conveniently. The method comprises the following steps: generating a grey-scale map according to atomic force microscopic imaging data, wherein the grey-scale map comprises a plurality of macromolecules; applying a migration model to the grey-scale map, performing image detection, extracting an image of macromolecular single particles, filtering defective particles, and retaining conventional particles; wherein the migration model is obtained based on a segmentation model by training data sets in different view ranges to perform multiple rounds of learning; and aligning the images of the conventional particles through an image registration algorithm and averaging to obtain a macromolecule morphology restored image.

A mosaic dislocation repair method and device based on a high-precision image registration algorithm and a medium. It belongs to the technical field of satellite remote sensing, and specifically relates to the technical field of image mosaic dislocation repair. The method comprises the following steps: S1, inputting the dislocated area in the mosaic process in the form of vector data, determining the area to be repaired, and obtaining the local area image to be registered; S2, performing feature point matching on the local area image to be registered; S3, adding fixed points to the buffer area outside the area to be repaired; S4, transforming the local area image to be registered through a thin plate spline function to obtain a final registration image; and S5, replacing the final registration image into the original image for re-mosaic. The method is suitable for dislocation repair requirements in different scenes, significantly reduces the manual repair cost while improving the image product quality, and has important practical value.

The invention relates to the field of railway assistance, in particular to a railway line information acquisition device and method based on deep learning, and the device comprises a motion structure which comprises a small rail car which is a core bearing part of the device and is internally integrated with an intelligent acquisition module to realize data acquisition, processing and storage, and an information acquisition component which is used for acquiring information of the small rail car. Data acquired by the information acquisition component are uploaded to the data processing system through an RTSP protocol, real-time video streams of all the cameras are received, timestamp marking is carried out on the acquired data, and time sequence synchronism of data of different visual angles is ensured. And performing preprocessing steps of distortion removal, geometric correction and the like, and performing feature matching and alignment by using an image registration algorithm. A complete track section image is generated based on an image splicing technology, and a trackside three-dimensional reconstruction model is generated in combination with 3D point cloud data.

The present application relates to a medical image-based multi-modal registration method and device, the method comprising: obtaining a brain registration dataset and dividing it into a training set and a test set. A registration network is constructed based on a UNet network structure. An input image is selected and input into a dual architecture. The input image is subjected to one-way registration in both directions to obtain forward and reverse deformation fields and a one-way registration image. The deformation fields of the two dual parties are exchanged and applied to the one-way registration image for secondary registration to obtain a secondary registration image. A Laplace operator is called to extract structural features from the input image, the one-way registration image and the secondary registration image, respectively, and the registration network is constrained by structural similarity measurement. An end-to-end unsupervised image registration algorithm is trained by the training set and the test set, and is optimized according to the loss constraint. The registration image to be detected is input into the registration network, the optimal model weight is applied, and the registration result is output to ensure the uniformity and accuracy of the result.

The application provides a kind of measurement method, device and system, the method includes: the initial function of the outgoing wave of the first part and the second part of the object to be measured is obtained respectively, at least once the i iteration is executed respectively, in each iteration: by reciprocating propagation between object plane, modulator plane and detector plane to the outgoing wave of the i part, and the amplitude of the outgoing wave of the i part is constrained according to the actual diffraction intensity of the outgoing wave of the i part in the detector plane;Obtain the reconstruction function of the outgoing wave of the i part on the object plane;According to the reconstruction function of the outgoing wave of the first part and the second part, the displacement vector between the first part and the second part is calculated using image registration algorithm.The application can obtain the relative displacement of scanning position without positioning system, further, the relative displacement can also be used to complete diffraction imaging.

The present invention discloses a cutting path planning method and system for an ultrasonic scalpel device, and relates to the field of medical technology. A cutting path planning system for an ultrasonic scalpel device includes: a cutting path planning module and a cutting path calibration module. The present invention performs image recognition by inputting a cutting image annotation model to obtain a cutting object feature map, and utilizes an improved spatial trajectory planning algorithm and image registration algorithm to efficiently predict and optimize the initial cutting path and ensure the accuracy of the cutting path; by registering the simulated cutting object image and analyzing it based on a cutting error judgment model, potential cutting errors can be identified before surgery, and the cutting path can be adjusted in advance, thereby reducing the impact of the error. The initial cutting path is updated using the error judgment result, effectively preventing path deviations caused by errors.

The invention discloses a pathological section diagnosis area marking and archiving method, which comprises the following steps: acquiring multi-temporal pathological section image data of a target tissue area, the multi-temporal pathological section image data comprising section images of the target tissue area collected at different time points; based on the multi-temporal pathological section image data, constructing a cable pipeline topology network in the target organization area through an image registration algorithm and a topology refinement algorithm; for the pathological section image data of each time phase, identifying an abnormal diagnosis area in the pathological section image data through an image identification algorithm; calculating geometric topological relation data between the spatial position of the abnormal diagnosis area identified in each time phase and the nearest branch node in the cable pipeline topological network; and based on the geometric topological relation data, generating fault source coordinate data in one-to-one correspondence with the abnormal diagnosis areas, and storing the fault source coordinate data into a diagnosis area coordinate database.

This invention discloses a multi-directional differential phase reconstruction method. For synchronous phase-shifted transverse shearing interferograms in two directions, a phase-correlated image registration algorithm is used to match the positions of the shearing interferograms in both directions. A four-step phase-shifting algorithm is used to obtain the wrapped phase in both directions. An optimized DCT-based least-squares phase unwrapping algorithm is used to unwrap the wrapped phase. The shearing amount of the shearing interferogram is calculated through edge detection and fitting. The wavefront to be measured is reconstructed using a least-squares method based on differential Zernike polynomials. An anti-tilt algorithm eliminates the introduced tilt error, completing the differential phase reconstruction. This invention utilizes an optimized unwrapping algorithm to overcome the unwrapping failure problem caused by noise, making the unfolded phase smoother, more continuous, and closer to the true phase. Furthermore, data is processed in the circular domain, eliminating the need for Zernike polynomial orthogonalization. This invention can be applied to processing multi-directional transverse shearing interferometry.

An image processing method and an electronic device are applied to the technical field of image processing. The method comprises the following steps: acquiring a to-be-registered image and a reference image; the method comprises the following steps: performing first image processing (at least including demosaicing and gray level conversion processing) on an image to be registered to obtain a first gray level image, and performing second image processing (at least including demosaicing and gray level conversion processing) on a reference image to obtain a second gray level image; performing registration processing based on the first grayscale image and the second grayscale image to obtain a registration result (such as a homography matrix or an optical flow); and performing third image processing by using the to-be-registered image and the registration result to obtain an image alignment result, and executing image processing by using the image alignment result. According to the method, the image processing algorithm (such as Bayer image regeneration processing and demosaicing processing are introduced for the Quad image) is introduced into the pre-processing of image registration, so that the calculation precision of the image registration algorithm on spatial transformation can be improved, and the image alignment quality is improved.

This invention relates to the fields of image processing and computer vision, specifically to a method for registering CAD drawings and real-world images based on point affine transformation. The method includes image preprocessing, edge detection and contour extraction, point cloud registration, affine transformation, result fusion and display, and automatic correction feedback. By fully utilizing the edge information and contour features of the image, this invention can more accurately match CAD drawings and real-world images, effectively solving the discrepancy problem between them and improving the accuracy of operations such as cutting. The registration method based on contour point sets, compared to traditional global image registration algorithms, has lower computational load and faster speed, meeting the real-time requirements of actual production. The entire registration process is highly automated; users only need to input the CAD drawing and the real-world image to automatically complete the registration and display the results, without complex parameter adjustments or manual intervention. This method has good adaptability to different types of CAD drawings and real-world images.

According to a system for processing an unstructured multi-medical image registration algorithm and a method of using same, proposed in the present invention, the system comprises: a first image registration processing unit for performing image registration through a normalized cross-correlation (NCCS) process based on a Sobel operator; a second image registration processing unit for performing image registration through a normalized cross-correlation (NCCL) process based on a LOG operator; and a multi-resolution processing unit for performing image processing, with multiple resolutions, on each of registration images of the first image registration processing unit and the second image registration processing unit, thereby improving the accuracy of unstructured image registration by using a registration algorithm between unstructured multi-medical images using normalized cross-correlation based on the Sobel operator or normalized cross-correlation based on the LOG operator.

The application relates to a multi-focus photoacoustic imaging registration fusion method based on blind deconvolution, which comprises the following steps: acquiring photoacoustic images of different laser wavelengths and different depths of field by using a fast photoacoustic imaging device; establishing a blind deconvolution model and initializing a blind deconvolution blur kernel; based on the blind deconvolution model, deconvolving the photoacoustic image and updating the blur kernel to obtain an optimized photoacoustic image through blind deconvolution, and continuously optimizing by using an image quality judgment function; using an intensity-based photoacoustic image registration algorithm to determine optimal transformation parameters based on intensity information, and registering the photoacoustic images of different depths of field after blind deconvolution optimization; using an image fusion algorithm to fuse the registered photoacoustic images to generate a focused fusion high-quality super-resolution photoacoustic image. Compared with the prior art, the application has the advantages of non-invasiveness, non-destructiveness, convenience, fast realization of photoacoustic image feature registration and fusion of different depths of field, and recovery of high-resolution imaging.

The application belongs to the technical field of image processing, and discloses a fast splicing method for CBCT vertical scanning, which comprises the following steps: step S1, a plurality of scanning positions of a rotating platform are arranged along the Z direction, and a scanning object is scanned at each scanning position to obtain scanning data; step S2, the angle offset of adjacent scanning positions is calculated according to the scanning data; volume reconstruction is performed on each scanning position; step S3, a common reconstructed slice image at the adjacent scanning positions is extracted, and the feature points of the slice image are determined by using a SIFT algorithm; the rotation angle of the slice image is determined by using a RANSAC algorithm; and step S4, the reconstructed volumes of the adjacent scanning positions are spliced after being rotated according to the rotation angle calculated in step S3. The application introduces a high-precision motion calibration technology and an improved image registration algorithm, the image quality is significantly improved, the joint seam artifact is eliminated, and a reliable guarantee is provided for high-resolution three-dimensional reconstruction.

The present specification relates to an image sequence motion correction method and device based on intensity correction optical flow registration. The method comprises: determining a reference image of each deformed image in a deformed image sequence, performing motion correction on the deformed image by adjusting the weight of the mechanical regularization term of the reference image and the deformed image to obtain the displacement field of the deformed image relative to the reference image; based on the displacement field and the intensity correction value of the finite element node, intensity correction is performed on the reference image; adjusting the weight of the mechanical regularization term, performing motion correction on the deformed image, intensity correction is performed on the first corrected reference image based on the optimized displacement field, and the execution is repeated until the image residual function converges, the deformed image is determined to be corrected, the optimal solution of the weight value of the mechanical regularization term of the deformed image is recorded; and determining the true displacement of the deformed image according to the optimal solution of the weight value. The present specification integrates the mechanical model behind physiological motion and intensity correction technology into the image registration algorithm to reduce image noise and improve algorithm accuracy.

The invention provides a diagnosis and treatment effect evaluation method and system for constructing ICUAW based on multi-mode ultrasound and machine learning, and the method comprises the steps: carrying out the time and space alignment of B-mode ultrasound imaging data, elasticity imaging data, ultra-capillary imaging data and energy Doppler imaging data through an image registration algorithm, and generating comprehensive image data; extracting local features and time sequence features in the comprehensive image data by using a feature extraction algorithm, and fusing the local features to generate local fusion features; capturing a global relationship between the local features by using a relationship capturing algorithm and an attention module; and performing curative effect evaluation through the curative effect evaluation model by utilizing the global relationship, and outputting a curative effect evaluation result of the ICUAW patient. According to the method, the space-time evolution rule of muscle atrophy is quantified by constructing the dynamic space-time diagram network, multi-scale features are accurately extracted in combination with a scale perception attention mechanism, key pathological information is prevented from being lost, and the accuracy of ICUAW patient curative effect evaluation is improved.

This application discloses a method, apparatus, device, and medium for generating a standard template for a meter code breakage display, relating to the field of image processing. The method includes: acquiring a first target image of the meter code breakage display to be tested and a reference standard template of a reference meter code breakage display corresponding to the meter code breakage display; wherein the reference standard template includes a source image and label information; registering the first target image and the source image based on an image registration algorithm to obtain a perspective transformation matrix; projecting the label information onto the first target image using the perspective transformation matrix to obtain a second target image containing the projected label information; and performing character segmentation on the second target image based on the character frame position information in the projected label information to obtain character images and corresponding character names, so as to generate and save the standard template for the meter code breakage display to be tested. This method can improve the efficiency and standardization of secondary production of standard templates and reduce production costs.

The application discloses an infrared thermal image and visible light image registration and fusion method, relates to the technical field of semiconductor detection and failure analysis, and comprises the following steps: acquiring phase-locked infrared thermal image data of a chip in a working state based on a surface array phase-locked infrared thermal imager; and performing coordinate system alignment on the infrared thermal image data and visible light image data based on a feature point matching image registration algorithm to obtain spatially aligned infrared thermal distribution maps and visible light surface maps. The infrared thermal image and visible light image registration and fusion method can significantly improve the precision of chip defect positioning, the quantitative level of risk assessment and the reliability of detection results, reduces the probability of misjudgment and missed judgment, and has good engineering application value.

The application discloses an optical and SAR image registration method based on similar edge feature extraction and OFAST-BRISK algorithm, and mainly applies to the technical field of satellite remote sensing image processing and application.The application aims to solve the problems of low accuracy and poor stability of existing optical and SAR image registration algorithms.The application combines the advantages of deep learning algorithm and traditional feature matching algorithm.The improved Log operator is used in combination with the Deeplabv3+ network to realize the similar edge feature extraction of optical and SAR images, and the OFAST-BRISK algorithm is used in combination with the improved RANSAC algorithm to realize the extraction and matching of feature points.The optical and SAR image registration method based on similar edge feature extraction and OFAST-BRISK algorithm can realize the efficient and accurate registration of optical and SAR images with 10m resolution.

The application relates to the technical field of image processing, and provides an image registration method, a computer program product, a storage medium and electronic equipment. The image registration method comprises the following steps: acquiring a reference image and an intermediate image; taking the image registration reference image as a reference, calculating a homography matrix between the image registration intermediate image and the image registration reference image by using a registration algorithm based on the homography matrix, and calculating a homography optical flow corresponding to the image registration homography matrix; taking the image registration reference image as a reference, calculating a forward optical flow between the image registration intermediate image and the image registration reference image by using an optical flow-based registration algorithm; fusing the image registration homography optical flow and the image registration forward optical flow to obtain a fused optical flow; and transforming a to-be-registered image of image registration by using the image registration fused optical flow to obtain a registered image. The method realizes the complementary advantages of two types of image registration algorithms, and is beneficial to improving the image registration accuracy.

The application provides a CUDA acceleration-based thin-plate spline deformation parameter matrix calculation and linear interpolation method, which processes three-dimensional to-be-registered feature points and template feature points through three-dimensional affine transformation; the to-be-registered feature points and the template feature points processed by the affine transformation matrix are used to calculate a thin-plate spline deformation parameter matrix based on functions in cublas and cusolver in the CUDA architecture; the to-be-registered three-dimensional image coordinates are inversely transformed by the obtained thin-plate spline deformation parameter matrix, and three-linear interpolation is performed. Through parallelization of large matrix algebra operation and linear interpolation by using the parallel architecture of the GPU, fast calculation of thin-plate spline transformation deformation parameter matrix calculation and linear interpolation is realized, and the running efficiency of the image registration algorithm is effectively improved.