18 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 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.

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 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 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.

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 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 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 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 invention provides a pinhole image splicing truth value acquisition and splicing method based on heterogeneous camera combination, and the method comprises the steps: symmetrically installing two pinhole cameras on a support, installing a fisheye camera between the two pinhole cameras, calibrating the three cameras based on a double-spherical camera model, and carrying out the calibration of the three cameras, the method comprises the following steps: obtaining internal parameters and external parameters of three cameras, simultaneously acquiring a left-eye pinhole view, a right-eye pinhole view and a middle-eye fisheye view of a target scene by using the three cameras, performing equidistant rectangular projection on the middle-eye fisheye view, and obtaining a target scene according to the internal parameters and the external parameters of the three cameras. And respectively projecting the left-eye pinhole view and the right-eye pinhole view to a view plane of equidistant rectangular projection to complete unification of a multi-camera coordinate system and obtain a splicing true value. Core advantages are formed by means of hardware structure design and a heterogeneous camera image registration algorithm, images which are free of splicing seams and consistent in time sequence can be stably obtained, and powerful support is provided for precision verification of follow-up panoramic video splicing and truth value reference of model training.

The application relates to a matching block search method, device and storage medium in image registration, wherein the matching block search method in image registration comprises the following steps: acquiring a reference image, a to-be-matched image, control point information and preset search features, wherein the preset search features comprise a preset matching size; determining an initial matching block according to the control point information and the preset matching size; determining image information of the initial matching block, and determining target search features according to the image information; determining a reference matching block in the reference image according to the control point information and the target search features, and searching for a target matching block corresponding to the reference matching block in the to-be-matched image. Through the application, when the method is applied to X-ray contrast image registration, the problem that the existing X-ray contrast image registration algorithm cannot adaptively determine the size or search range of a matching block can be solved.

The invention provides a Seidel aberration sensor for optical imaging system measurement, and relates to the technical field of optical measurement. The sensor comprises a lighting system, a customized dot matrix target, an optical system to be measured, a collimation optical system and a Seidel aberration sensor, wherein the Seidel aberration sensor consists of a micro-lens array and a camera. Quantitative measurement of five kinds of Seidel aberrations including primary spherical aberration, coma aberration, astigmatism, field curvature and distortion is realized by presetting and calibrating a customized dot matrix target and calibrating an exclusive calibration system of a Seidel aberration sensor in combination with mass center offset calculation of a sensing image, global view multi-point wavefront reconstruction and Zernike polynomial distribution coefficients. The method does not need a complex high-resolution image registration algorithm and double-dimension reduction aberration coefficient matrix calculation, is high in measurement precision and efficiency, can avoid a high-frequency evaluation blind area and error accumulation, is suitable for optical performance evaluation of various imaging systems with large visual field and high flux, and improves the quality control capability and the assembly efficiency in the production process of the optical system.

Methods and systems for laser speckle contrast imaging with motion correction and motion compensation are disclosed. The method includes exposing a target region to coherent first light of a first wavelength, the target region including living tissue, and capturing at least one image sequence including first speckle images, and determining one or more transformation parameters of an image registration algorithm for registering the first speckle images to each other. The transformation parameters can be based on a similarity measure of pixel values of a group of pixels in a plurality of images of the at least one image sequence, the images in the plurality of images being selected from or associated with the first speckle images.