154 results about "Image deformation" patented technology

The invention relates to the technical field of surface defect recognition, and discloses an intelligent recognition method and system for surface defects of an autoclaved aerated concrete member. The method comprises the following steps: carrying out omnibearing shooting and spatial transformation matrix mapping on the surface of the autoclaved aerated concrete member to obtain a preprocessed image; performing texture feature extraction on the preprocessed image to obtain texture feature data; performing spatial feature analysis on the preprocessed image and the texture feature data to obtain spatial relation feature data; performing feature importance weighting and bidirectional cross fusion processing on the texture feature data and the spatial relation feature data to obtain comprehensive defect feature representation; and performing surface defect analysis on the autoclaved aerated concrete member based on the comprehensive defect feature representation, and outputting a surface quality comprehensive score and grade division result. According to the method, the problems of dead angles and image deformation existing in traditional single-view-angle detection are solved, and the completeness and accuracy of defect detection are ensured.

The invention discloses an identification photo generation method and electronic equipment, and relates to the field of image processing, after an original user image and an original template image (identification photo template) aiming at the original user image are acquired, image deformation is carried out on the original template image according to the original user image and an image deformation algorithm, and the identification photo is generated. A target template image which aims at an original user image and conforms to one or more of facial key point constraints, light and shadow consistency constraints and facial structure constraints is obtained, and the original user image and the target template image are input into a trained image generation model (obtained by optimizing and training a diffusion algorithm); the corresponding areas are processed according to the different processing weights corresponding to the face area and the non-face area, it is ensured that the obtained target identification photo is more natural, real and reliable in vision, the specification requirement of an actual scene for the identification photo is met, the calculation time and cost are reduced, and the requirement for large-scale identification photo batch generation is met.

The invention discloses a weight function phase shift method for deformation field measurement, belongs to the technical field of optical measurement, is suitable for phase extraction and deformation field measurement of periodic structure images such as gratings and stripes, and has the characteristics of high speed and high precision. Weight function windows (a rectangular window, a triangular window, a cosine window and a Gaussian window) are applied in image processing, discrete Fourier transform is carried out after pixel gray values in the windows are multiplied by corresponding weights, and image phases at the center pixel positions of the windows are obtained. After the weight function window traverses all image pixels, the phase distribution of the whole image is obtained. And solving an image deformation field by using the phase difference of the images before and after deformation. Compared with the existing phase-based deformation field method, the method does not need complex image processing operation, and can solve the high-precision phase in one step and obtain full-field deformation only by using the weight function and the global pixel gray scale.

The invention discloses a high-precision global quasi-static strain vision measurement method, and relates to the technical field of strain vision measurement, and the method specifically comprises the steps: 1, obtaining high-resolution continuous image deformation data, correcting the geometric distortion of a deformed image through an ortho-rectification method, and carrying out the correction of the geometric distortion of the deformed image; the method comprises the following steps: step 1, acquiring high-resolution and continuous image deformation data through a high-precision image acquisition device, and accurately correcting geometric distortion existing in a deformed image by using an orthographic correction method, step 2, carrying out noise reduction processing on the image through a singular value decomposition technology, carrying out image displacement analysis on the image subjected to the noise reduction processing, and carrying out image displacement analysis on the image subjected to the image displacement analysis. The method comprises the following steps: step 1, carrying out deep noise reduction processing on an image by using an advanced singular value decomposition technology to effectively remove various noise interferences in the image, and step 2, carrying out further processing on data obtained after strain calculation is completed, and visually displaying a strain result through visual output. The invention provides an efficient and reliable solution for complex structure global strain measurement.

The invention, which belongs to the technical field of remote sensing image processing and geological disaster monitoring, discloses a high-risk slope multi-temporal remote sensing image deformation monitoring and early warning system comprising a multi-platform remote sensing data acquisition module, a deep neural network registration module, a sub-pixel-level deformation detection module, a meteorological data fusion module and a dynamic early warning module. The centimeter-level registration precision is realized by introducing an adaptive feature registration mechanism based on a graph attention network, the deformation estimation precision of a texture sparse region is improved by adopting a time-space domain combined sub-pixel-level deformation field estimation algorithm, and the early warning timeliness is improved by establishing a dynamic early warning threshold self-adjustment mechanism fused with meteorological data. The system supports multi-scale multi-platform cooperative monitoring, the early warning advance period is prolonged by 7-15 days, and the system is successfully applied to high-risk slope monitoring projects along the expressway.

The invention belongs to the technical field of data processing, and provides a scale detection and scale conversion method and system based on an ultrasonic image, and the method comprises the steps: constructing a discrimination function fusing multi-modal features according to the spectral basis functions of different scales, and determining the scale contour of the scales in the ultrasonic image; the design can dynamically adapt to the spectral characteristics and structural characteristics of the scale, can effectively cope with the interference of scale diversity, ultrasonic speckle noise and the like of equipment of different manufacturers, and ensures the stability of scale positioning and subsequent conversion; the method comprises the following steps of: establishing a biomechanical-image deformation coupling model by taking a scale contour of a scale in an ultrasonic image as a geometric reference and combining biomechanical characteristics of an ultrasonic probe and tissues to obtain a corrected pixel distance between adjacent scale points of the scale; and curvature compensation for eliminating refraction errors of ultrasonic waves in curved tissues is introduced to correct a scale pixel-millimeter conversion coefficient, so that the pixel-millimeter conversion error rate is reduced to 1.2%, which is far lower than the level of a traditional method.

The embodiment of the invention provides a laser direct-writing image detection method, a laser direct-writing image detection system and related equipment, which realize accurate positioning of an image deformation area position on a complete exposure breadth and measurement of deformation quantity by detecting the offset of light spots of different lasers in the horizontal direction at the same moment. The method comprises the following steps: arranging a plurality of groups of non-repeated binary images to be ranked in the horizontal direction to form an image sequence, and carrying out binarization processing on the image sequence to obtain the position of a laser exposure point; in a synchronous scanning process of a plurality of lasers in the laser array, controlling each laser to expose a mapping position of an exposure point on a photosensitive coating in an image sequence by using a synchronous switch instruction so as to respectively form a latent image of the image sequence in a respective scanning area of each laser; and if the plurality of developing image sequences are not aligned in the horizontal direction from the target binary images in the same sequence, detecting coordinate values of difference points of the target binary images in each developing image sequence in the horizontal direction.

The present invention provides an image processing method, device and system, the method comprising: determining a first image according to resolution information of a pre-collected source device, pre-collected cone modeling parameters and pre-collected sample images; performing deformation processing on the first image to obtain a cone calibration map and cone calibration parameters; performing geometric correction on the cone calibration map to obtain a second image and geometric correction parameters; based on the cone calibration parameters and geometric correction parameters, correcting a pre-acquired original video image to obtain a target video image. This technology is applied to the scene of image virtual simulation. This solution adopts a combination of software and hardware, and is suitable for situations where the performance of the source device is not high, or the graphics card is not sufficient to support fusion processing, or when the source device has confidentiality requirements, to ensure the stability of the image deformation processing process, and the frame processing delay meets the requirements, which can improve the interactive response speed.

The invention discloses a cone beam CT full respiratory cycle image reconstruction method based on a four-dimensional neural network. The method comprises the following steps: step 1, acquiring cone beam projection data and a respiratory signal in a respiratory state; 2, a respiratory cycle is divided into N phases, multi-phase cone beam projection data Qi are obtained, i = 1, 2,..., N, the Qi is reconstructed through a filtered back projection algorithm, and a multi-phase under-sampling CT reconstructed image # imgabs0 # is obtained; 3, # imgabs1 # is input into a four-dimensional neural network, and a three-dimensional deformation field Di is obtained; 4, performing weighted summation after deformation on the # imgabs2 # by using the Di to obtain a reference phase reconstruction image Xref after motion correction; and step 5, performing inversion on the Di to obtain a three-dimensional reverse deformation field # imgabs3 #, for any breathing phase, performing image deformation on the reference phase reconstruction image Xref by using the corresponding # imgabs4 #, and performing reconstruction to obtain a motion correction image Xi. According to the method, the breathing movement correction can be quickly carried out on the cone beam CT image.

The invention provides a Chinese character image deformation method and device. A deformation control point and a corresponding deformation target point are selected from an original character image; calculating a corresponding weight for each deformation control point; calculating a first weighted center point based on the coordinate and the weight of each deformation control point, and calculating a second weighted center point based on the coordinate of each deformation target point and the weight of each deformation control point; calculating a transformation matrix corresponding to each pixel point based on the weight of each deformation control point and the first weighted center point; and based on each transformation matrix, the coordinate of each deformation target point and the second weighted center point, performing deformation operation on the original character image to obtain a new character image. According to the method, different influences are generated on pixel points in different areas of an image through weighted multiple control points, affine transformation needed by distortion deformation of the pixel points is calculated through the influences, smooth transition between a deformed area and a non-deformed area of the image is ensured, and therefore the purpose of improving the Chinese character image deformation effect is achieved.

The invention provides an image correction processing method and system for a vehicle-mounted ground projection system. The method comprises the following steps: S1, acquiring a current motor rotation angle and a vehicle front distance of a selected ground projection area; s2, calculating four angular points of a target image according to the current motor rotation angle and the vehicle front distance of the selected ground projection area; s3, calculating a transformation matrix of a corrected image according to the four corners of the original image and the four corners of the target image, and correcting the original image to obtain the target image; and S4, transmitting the target image data to a DLP (Digital Light Processing) for projection. According to the invention, the image deformation problem in the vehicle-mounted ground projection process can be corrected in real time by combining the rotation angle of the motor and the selected front distance of the ground projection area in front of the vehicle; it is ensured that no matter how the vehicle moves or the projection angle is adjusted, the projected image can be kept clear and does not deform, and the visual experience of a user is greatly improved.

The invention relates to the technical field of automatic visual detection, and discloses a bottle body label quality detection-based model automatic generation method, which comprises the following steps of: acquiring a multi-angle image of a bottle body, carrying out denoising, enhancement and brightness equalization processing, extracting a curved surface label through target detection and a perspective transformation algorithm, and carrying out image processing on the curved surface label; further generating a distortionless complete label image through an image registration and fusion technology, and taking the distortionless complete label image as a training sample set of a label defect detection model constructed based on a double-branch deep learning network; and performing hot updating on the label defect detection model through a closed-loop feedback and continuous learning mechanism. According to the method, the technical problems of imaging deformation of the curved surface label, diverse defects, difficulty in detection and performance degradation after model deployment are effectively solved, and high-precision, high-robustness and sustainable-evolution automatic label quality detection is realized.

The invention provides an endoscope image stabilization control method, which comprises the following steps of: acquiring an original dithering image sequence and inertial data of an endoscope, fusing the original dithering image sequence and the inertial data, acquiring an initial mixed motion field, performing operation semantic segmentation on the original dithering image sequence, and acquiring a collaborative attention map in combination with a physical motion mechanism. Obtaining a space-time adaptive filtering kernel through the collaborative attention map, filtering the initial mixed motion field according to the space-time adaptive filtering kernel, obtaining a stable motion field, carrying out image deformation and interpolation synthesis processing on the stable motion field, and obtaining a stable image sequence; through the integrated technical scheme of operation semantic segmentation, dynamic image stabilization optimization and accurate jitter suppression, the problem of interference of endoscope jitter on the neurosurgery operation visual field is solved.

The invention discloses a streaming media and back-up rearview shared high-definition camera shooting system, which relates to the technical field of back-up rearview camera shooting and comprises a camera shooting acquisition module, a camera shooting correction module, an image analysis module, a path analysis module and an execution display module. The shooting correction module is used for correcting the shot image and adjusting the shooting angle of the wide-angle camera; the image analysis module performs analysis based on the data of the camera shooting correction module to obtain a lane changing safety coefficient, a vehicle static safety coefficient and an inverted safety coefficient; the path analysis module analyzes an image transmission path to analyze the quality of a transmitted image to obtain a quality reduction amount, and analyzes the image transmission path and delay to obtain a channel matching number; the execution display module receives the signal for execution display; the system corrects the photographed image, reduces the deformation of the image, effectively improves the quality and usability of the photographed image, and provides safer and more convenient driving experience for a driver.

The invention provides a defect detection method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a template image and a product image of a to-be-detected product; performing feature matching on the template image and the product image, and performing non-rigid alignment on the product image based on feature point pairs obtained by feature matching to obtain an alignment image of which the geometric view angle is consistent with that of the template image; and defect detection is carried out based on the aligned image and the template image to obtain a detection result, so that the problem of image deformation caused by the fact that the surface of the to-be-detected product is a curved surface and the shooting angle is not correct in a traditional scheme is effectively solved, and local and global deformation of the product image can be corrected, thereby greatly improving the alignment precision of defect detection, and improving the detection accuracy of the to-be-detected product. Therefore, the real difference of the product surface can be more focused during defect detection, non-defect geometric deformation interference is effectively shielded, and the accuracy and robustness of defect detection of complex surfaces of household electrical appliances and the like are greatly improved.

The invention relates to the technical field of medical treatment, in particular to a deformation registration method and system, a self-adaptive treatment planning method and a treatment planning system which are used for improving the accuracy of image deformation registration, and the method comprises the steps: obtaining a plan image, a fractional image and dose distribution data corresponding to an initial treatment plan of a patient; inputting the plan image, the graded image and the dose distribution data corresponding to the initial treatment plan of the patient into a trained deformation registration model, performing deformation registration on the graded image and the plan image, and outputting a deformation field; wherein the trained deformation registration model is obtained based on dose distribution consistency loss training between dose distribution data corresponding to the initial treatment plan and deformation dose distribution data corresponding to the deformation field.

The invention discloses an image registration method, a model training method, equipment, a medium and a product, and belongs to the technical field of medical image processing. The method comprises the following steps: acquiring a fixed image and a floating image to be registered; the fixed image and the floating image are input into a pre-trained registration model, a target deformation result of the floating image is obtained, and the target deformation result is a registration image of the fixed image; wherein the pre-trained registration model comprises a pre-trained image registration module and a pre-trained image post-processing module; the pre-trained image registration module is used for performing image registration processing on the fixed image and the floating image to obtain grid sampling parameters; the pre-trained image post-processing module is used for determining an image deformation result, corresponding to the grid sampling parameters, of the floating image and performing image post-processing on the image deformation result to obtain a target deformation result, and the image post-processing comprises denoising and / or image restoration.

The invention relates to an image registration method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a first image and a second image obtained through image collection of a target physiological region, the first image data being a three-dimensional image, and the second image being a two-dimensional image; and determining a deformation field describing a mapping relation between the first image and the second image, and performing nonlinear deformation on the first image according to the deformation field to obtain a deformed image. And projecting the deformed image to obtain a two-dimensional third image capable of measuring a registration effect with the second image. According to the embodiment of the invention, through the architecture for image deformation and projection and image registration based on the deep learning automatic learning deformation field, the elastic registration between the images can be simply, quickly and accurately realized. Meanwhile, the image registration mode is realized by depending on a software algorithm without depending on the improvement of a hardware structure, so that the cost is low.

An apparatus includes a memory to store first volumetric image data representing a first volumetric image of an anatomical region having a volume of interest (VOI). The first volumetric image includes several first voxels at first locations in the first volumetric image. The first volumetric image data includes first uncertainty values corresponding to the several first voxels. The first uncertainty values represent probabilities that the corresponding plurality of first voxels are part of the VOI. The memory is to store second volumetric image data representing a second volumetric image of the anatomical region. The apparatus includes a processing device operatively coupled to the memory. The processing device is to determine a deformation field to map the several first voxels to second locations in the second volumetric image. The deformation field is based in part on the first uncertainty values.

The invention relates to the field of deformation monitoring, in particular to an image deformation monitoring method, device and equipment and a program product. The method comprises the steps that matching errors are remarkably reduced by combining a Zhang's calibration method with epipolar correction, and the signal-to-noise ratio and the contrast ratio of an image are enhanced through median + wavelet filtering and histogram equalization processing. Through multi-scale census transformation and weighted Hamming distance calculation, local and global information can be effectively combined, and the robustness of a cost matrix is enhanced; according to the eight-path aggregation optimization method based on dynamic planning, the precision and the calculation efficiency of parallax calculation are further improved. According to the full-image displacement calculation method based on SIFT feature guidance, the problem of displacement propagation error accumulation is solved through sub-region matching and Gaussian Newton iterative optimization, the displacement measurement precision of a low-texture region is remarkably improved, and good robustness and accuracy are achieved in a complex scene.

The invention relates to the technical field of computers, in particular to a block chain right-confirming forestry remote sensing data ontology feature recognition method and system, and the method comprises the steps: extracting the multi-scale features of forestry remote sensing image data through a pre-trained deep convolutional neural network, and generating a feature pyramid with an unchanged rotation and scale; a time-space fusion feature vector is generated by combining seasonal attention weight adjustment, and forestry remote sensing image fingerprints are formed after principal component analysis and dimension reduction; a fuzzy commitment is adopted to bind the random key after error correction coding with a forestry remote sensing image fingerprint to generate a block chain evidence storage commitment, and a storage architecture with on-chain evidence storage and under-chain metadata collaboration is constructed; and efficient right confirmation is realized. The problem that a traditional Hash method is sensitive to image deformation is solved, the problem of feature drift caused by seasonal changes is solved, verifiable right confirmation is achieved, the method has the advantages of being high in storage efficiency, high in response speed and the like, a credible ownership authentication basis is provided for forestry remote sensing data sharing, and the data circulation efficiency is remarkably improved.

The invention discloses a tunnel model test supporting structure wall surface full-field deformation test method, and relates to the technical field of tunnel similar model test design, and the method comprises the following steps: S1, building a tunnel model, filling the model with a soil body, and installing a supporting structure; s2, deformation measurement is carried out, the tunnel model is excavated, and a tunnel supporting structure wall surface image containing distance information is shot; and S3, deformation analysis: splicing the images into a ring for data analysis. According to the tunnel model test supporting structure wall surface full-field deformation testing method, three parts of tunnel model, deformation measurement and deformation analysis are adopted, non-contact high-density deformation measurement of a tunnel model supporting structure can be achieved, full-field strain, displacement, deformation, stress and the like of the supporting structure can be analyzed, and the testing accuracy is improved. The problems of complex operation, large interference and the like of tunnel model test supporting structure measurement are solved, and the method has the advantages of simplicity in operation and rapidness in measurement under the condition of meeting measurement requirements.

The technical scheme of the invention discloses a spatial segmentation radiotherapy auxiliary system based on a multi-modal image, and the system is characterized in that the system comprises a deformation registration module of the multi-modal image; a target area sketching and high-dose small ball target area sketching module; and a cooperation module. The system disclosed by the invention is used for guiding target region sketching through a multi-modal image deformation registration technology, supporting automatic / manual design of a high-dose small ball target region, and cooperating with a treatment planning system (TPS) to complete a staged treatment process. The system disclosed by the invention finally evaluates the overall treatment effect through deformation registration and dose superposition, and is suitable for precise SFRT treatment planning of equipment such as an accelerator, a TOMO, a cyber knife and the like.

The present disclosure relates to an method and apparatus for generating an image, an electronic device, and a storage medium. The method includes: obtaining M original images of a target scene captured by M image acquisition devices, wherein each image acquisition device of the M image acquisition devices provides a different viewpoint of the target scene, and M is a positive integer greater than or equal to 8; performing, for each original image of the M original images, an image deformation process on the original image, based on depth information of the original image and internal and external parameters of the image acquisition device to obtain a deformed image; and performing a splicing process on M deformed images subjected to the image deformation process, to obtain an omni-directional stereo panoramic image.

The invention is applied to the technical field of product communication, and discloses an FPGA (Field Programmable Gate Array)-based LCD (Liquid Crystal Display) screen replacement OLED (Organic Light Emitting Diode) system, which comprises an MIPI (Mobile Industry Processor Interface) decoding unit, an RAM (Random Access Memory) image cache unit, a clock recovery unit, a scaling interpolation unit, an output time sequence unit, an MIPI coding unit, a screen command unit and an ADC (Analog to Digital Converter) sampling unit, and the FPGA selected by the system is only Lattice-XO3. According to the FPGA-based system for replacing the OLED with the LCD screen, the problem that the resolution ratios of the LCD screen and the OLED screen are inconsistent is solved by adopting the scaling interpolation unit based on the RAM cache in the FPGA, high flexibility and adaptability are achieved, the system guarantees the quality and integrity of images through accurate interpolation calculation and scaling processing, the visual experience is improved, and the system is suitable for popularization and application. And the user can fully utilize the advantage of high resolution of the OLED screen after replacing the screen, and meanwhile, the problems of image deformation, blurring or incomplete display and the like possibly caused by mismatching of the resolution are avoided.

An information processing device includes: an own position / posture estimation unit that estimates a position and a posture of a device based on sensing information acquired by a sensor unit, and outputs own position / posture information; and an image deformation unit that performs deformation processing on an image based on the own position / posture information and distortion of an optical system included in the device.

The invention relates to the technical field of optical lenses, and discloses a small-head optical imaging system, and the optical imaging lens comprises a first lens, a second lens, a third lens, a fourth lens and a fifth lens which are sequentially arranged from the object side to the image side along an optical axis, and the object side surface of the first lens to the image side surface of the fifth lens are aspheric surfaces; the diaphragm is arranged in front of the first lens; the small-head high-definition imaging lens is of a five-lens type, the surface shape structures of all the lenses are combined with the optimal range of optical parameters, the head size of the imaging lens can be effectively shortened and the visual angle of the lens can be improved under the condition that imaging deformation is reduced while imaging is maintained, and the small-head high-definition imaging lens has high resolution brought by high pixels and is high in resolution ratio. The optical imaging lens is small in size and integrated, can adapt to the increasingly pursued light and thin design of a mobile phone, and enables a rear cover of the mobile phone to be flat as far as possible and not to protrude or only to slightly protrude.

The invention provides a chromosome straightening method and device, electronic equipment and a storage medium. The chromosome straightening method comprises the steps that a chromosome image forms a binary image; s2, acquiring a central axis of each single chromosome in the binary image; s3, segmenting the chromosome image into a plurality of first-level triangles; s4, mapping the ordinates of the first-level central axis sampling points corresponding to the first-level triangles to be the same to form second-level central axis sampling points; s5, according to transformation of each first-level central axis sampling point and the corresponding second-level central axis sampling point, obtaining a corresponding second-level triangle coordinate through the first-level triangle through a rigidity-keeping image deformation algorithm; calculating an affine transformation matrix corresponding to each first-level triangle according to transformation of the first-level triangles and the corresponding second-level triangles, and performing affine transformation on the chromosome image region corresponding to each first-level triangle to obtain a straightened chromosome image; the chromosome straightening method provided by the invention can effectively correct the chromosome image.

The invention relates to a method for generating a view for a camera system, in particular for a panoramic camera system for a vehicle (1), comprising a control device (2) and at least one camera device (3a-3d), the view being generated according to the following method steps: detecting at least one object from ambient data of the at least one camera device (3a-3d); generating a bounding box of the object; projecting the object onto the ground; creating a boundary shape including a bounding box and a projection object; a network structure or a grid structure is established for the boundary shape, and the network structure or the grid structure is arranged in the bounding box, and the boundary shape is adjusted, in particular by image scaling and / or image deformation, so that the boundary shape is adapted to the size of the bounding box.

The embodiment of the invention provides a method and device for image processing, equipment, a storage medium and a system for augmented reality. In the method, grid information corresponding to the pose of the augmented reality device is acquired. The grid information is used for image deformation processing of the augmented reality equipment. A first set of pixels of a first image acquired by the augmented reality device in the first memory is caused to be stored to the second memory based on the grid information. The read speed of the second memory is higher than that of the first memory. Further, positional information of a first pixel in the first image corresponding to a second pixel in the image-deformed second image is determined, and a value of the second pixel is acquired by reading a value of the first pixel from the first memory or the second memory based on the positional information. The priority of reading the value of the first pixel from the second memory is higher than that of the first memory. In this way, the delay of video perspective of the augmented reality device can be effectively reduced.