35 results about "Image integrity" patented technology

The invention provides an automatic operation process management method and device based on multi-sensor fusion, and relates to the technical field of automatic processes, and the method comprises the steps: constructing an instrument pose flow and operation field geometric model under a unified coordinate system through unified timestamp alignment and spatial geometry solution of multi-source sensor data; semantic segmentation and three-dimensional reprojection are combined to generate a shielding probability graph, cross-channel compensation reconstruction is carried out, and the image integrity is improved. And forming a conflict risk set through voxel field discretization and short-time prediction, and performing combined solution with standardized operation process constraints to generate a scheduling instruction and a safety time window. And finally, mapping the image, the pose and the physiological signal to a knowledge graph, and outputting consistency judgment and deviation correction suggestions in combination with a time sequence attention recognition process node. According to the method, the problem that the operation process management is not accurate enough due to the problems of view overlapping and the like of multi-source sensor data can be solved.

The invention discloses a nighttime light remote sensing image super-division method and system using multi-source remote sensing data, and the method comprises the steps: collecting an NPP-VIIRS low-resolution nighttime light image, a Landsat-8 image and a Luoma No.1 high-resolution nighttime light image, carrying out the preprocessing, feature texture extraction, resampling, and data set construction. Constructing a U-Net neural network model for increasing a channel attention mechanism to carry out super-resolution processing from a low-resolution image to a high-resolution image; according to the method, detail information in the low-resolution image is effectively supplemented, the image super-resolution precision and the image integrity are improved, compared with the prior art, the high-quality and richer night light super-resolution image is provided, and the method has the advantages of being advanced in algorithm, high in precision and high in intelligent degree and is suitable for popularization and application. And a high-quality data basis is provided for subsequent remote sensing image analysis and data extraction.

The invention discloses a medical image robust watermarking algorithm based on a re-parameterized high-efficiency attention network, and relates to the field of image data processing methods, and the algorithm comprises the steps: obtaining an original medical image; a pre-trained RepEA-Net model is used for extracting multi-scale deep features with good generalization performance from an original medical image, and then a mean perceptual hash algorithm is used for generating feature vectors. Obtaining an original watermark image; the watermark image is encrypted by using a Logistic chaotic encryption algorithm, the security of the watermark image is improved, and finally, the encrypted watermark image and the binary feature vector are subjected to XOR operation to generate the zero watermark. Through the innovative design of the re-parameterization efficient attention network, the contradiction among robustness, generalization and image integrity of a traditional medical image watermarking algorithm is broken through, and a solution with technical advancement and clinical practicability is provided for copyright protection and safe transmission of medical images in the medical Internet of Things.

Embodiments of the present disclosure provide a video processing method and apparatus, and a device. The method comprises: acquiring a reference image and text information; determining a target action video corresponding to the text information; if first human body key point information of the reference image fails to match second human body key point information of a target image frame in the target action video, performing inpainting processing on the reference image to obtain a target reference image; and generating a target video on the basis of the target reference image, the text information, and the target action video. In this way, an electronic device can automatically determine the target action video on the basis of the text information, and a user does not need to manually upload a guiding action video; and additionally, automatic inpainting processing for the reference image can be achieved, avoiding limitations on image integrity, enriching interaction forms of the user, improving the flexibility of user interaction, and meeting diversified requirements of the user.

The invention relates to the technical field of defect detection imaging, and discloses a high-precision three-dimensional imaging method and system based on continuous magnetic flux leakage data. Collecting surface magnetic flux leakage signals of a measured target to form an initial signal set, and extracting feature vectors by using a convolutional neural network model; separating three-dimensional space data, and obtaining initial three-dimensional position coordinates of the defect through an iterative mapping algorithm; mining spatial geometric features, determining potential geometric boundaries, and fusing data to construct a refined position model; extracting a detection subset, correcting a shape error, constructing a space reconstruction grid, filling holes, and obtaining a complete three-dimensional shape representation; and through precision calibration and signal matching verification, a high-precision three-dimensional image is output. According to the method, the defect positioning and shape reconstruction precision can be effectively improved, the imaging integrity and accuracy are guaranteed, the problems of fuzzy positioning and shape distortion of traditional magnetic flux leakage imaging are solved, and the defect detection requirements of a complex detected target are met.

The invention provides an electric power communication image authentication method, which constructs a key system based on quantum cryptography, improves the robustness of authentication mapping by using a perfect Hash mechanism, and realizes accurate identification and self-recovery of a tampered area in combination with an image coding mechanism and a hierarchical extension watermark embedding strategy. The method is especially suitable for scenes with extremely high requirements on image integrity and credibility in a power system.

Embodiments of the present application provide a structured light camera parameter correction method, device, storage medium and program product. The method corrects the light source output intensity of the structured light camera based on the collected image when the brightness difference degree of the image collected by the structured light camera is greater than or equal to a brightness difference degree threshold, to compensate for the brightness of the underexposed area and / or suppress the brightness of the overexposed area; until the brightness difference degree of the image collected by the structured light camera is less than the brightness difference degree threshold, the corrected light source output intensity is determined as the final light source output intensity, which can supplement the effective signal intensity of the edge and both sides of the field of view, suppress the effective signal intensity of the center area of the field of view, make the brightness values in the full field of view range consistent, solve the problem of uneven brightness distribution of the field of view, and improve the imaging integrity while meeting the timeliness requirements of industrial real-time imaging.

This invention relates to a method for automatically adjusting the initial depth of an image in an ultra-high frequency ultrasound system, comprising the following steps: Step 1: During image scanning, checking image stability; Step 2: Detecting the position on the skin surface; Step 3: Cropping the image. This invention provides image integrity, facilitating observation.

This disclosure provides a display control method and device, electronic equipment, and storage medium for a mine safety monitoring system, relating to the field of monitoring technology. By constructing display modules to splice together a mine display surface, a distributed signal processing system is used to uniformly process multi-source heterogeneous monitoring signals from underground mines and generate a network data stream that can be visualized and dragged for layout. The system performs regional time-sequential power-on management on the mine display surface and adaptively adjusts the driving parameters of the corresponding display areas based on the operating status information collected by sensors. Simultaneously, when a pixel-level anomaly is detected, a pixel compensation mechanism is triggered, and an anomaly report with precise location identifiers is generated synchronously. Therefore, it can solve the problems in existing technologies such as poor protection performance of display devices, complex and rigid multi-source signal processing, inconvenient layout operation, loss of image integrity when pixels are abnormal, and difficulty in fault location and maintenance.

The invention relates to the technical field of image detection, in particular to a territorial change investigation and monitoring-oriented proof image quick import and quality detection method, which comprises the following steps of: importing proof images from a plurality of heterogeneous image sources in parallel, analyzing geographic coordinates, shooting time and image format attributes through a metadata extraction engine, and determining the quality of the proof images according to the geographic coordinates, the shooting time and the image format attributes; and a standardized template is adopted to complete metadata structure unification. And then constructing a multi-dimensional quality detection chain, automatically detecting the space consistency, the time effectiveness and the image integrity of the proof image, generating a multi-dimensional quality score based on a weighted scoring mechanism, and outputting a high-quality, qualified and unqualified image quality grade set according to a preset threshold value. And for unqualified images, defect types are automatically identified, quality improvement rules are matched to generate improvement suggestions, re-acquisition scheduling is executed, and tasks are assigned to acquisition terminals. According to the invention, full-process automation of evidence-proof images from import, detection to improvement is realized, and the reliability of land change investigation evidence-proof data is improved.

This invention discloses a skin analyzer based on mechanical motion and multi-angle imaging with a reflector, belonging to the field of skin analyzer technology. It includes a housing, a lifting assembly inside a fixed frame, an angle adjustment assembly on one side of a moving rod, a reflector surface on one side of the angle adjustment assembly, and a rotating assembly on the other side of the moving rod. A light panel is symmetrically arranged inside the housing, and a moving assembly is located at the bottom of the moving frame, with a forehead support at the bottom of the moving assembly. This invention uses the moving rod to move the connecting seat and the moving plate, thereby causing the lifting frame and lifting ring to move upwards. The lifting ring and rollers then rotate the rotating frame, which in turn rotates the rotating rod and rotating seat fixedly connected to the rotating frame, causing the reflector surface to rotate. This ensures that the reflector can completely cover the side profile area of ​​different face shapes, avoiding missed images and ensuring full-angle image integrity without manual intervention.

The invention provides a reversible data hiding method and device for an encrypted image, a medium and a product, and relates to the technical field of reversible data hiding, and the method comprises the steps that each data hiding person end converts a pixel value of a share image into a binary sequence, and modifies the last bit of the binary sequence to obtain a first sequence; and taking the first sub-sequence and the second sub-sequence as new pixel value pairs, and sequentially converting pixel values of the share image into new pixel value pairs to obtain a marked share image. According to the method, reversible data hiding of the encrypted image is completed through three-end cooperation of the data owner end, the multiple data hiding person ends and the data receiver end in combination with block scrambling, secret sharing and Hamming coding, and the data security and the image integrity are guaranteed under the condition that a single data hiding person end is attacked or breaks down; and moreover, the embedding rate is improved by embedding the secret data for three times, the requirements of high-capacity information transmission and storage can be met, the calculation complexity is reduced, and the image recovery precision is improved.

This invention discloses a method, apparatus, device, and storage medium for color image protection based on a neighboring pixel difference strategy, belonging to the field of information security technology. The invention generates a target embedded watermark based on the original color image; embeds the target embedded watermark into the original color image to obtain a target color image; performs tamper detection on the image to be detected to obtain an image tamper detection result; if the image tamper detection result indicates tampering, the tampered image is restored to obtain the target color image. This invention first embeds the generated target embedded watermark into the original color image, and then performs tamper detection on the image to be detected, thereby effectively judging the integrity and authenticity of the image and achieving the protection of image data.

The invention discloses a vision-based train running distance SIL4 measurement method, which comprises the following steps of: S1, respectively mounting two sets of cameras on the left side and the right side of a train body, and downwards facing a steel rail; s2, when the train moves on the track, the camera collects images below the track in real time; s3, averaging the collected image gray values, and adjusting the image of which the image gray average value exceeds a preset range through the brightness of a light source until the image reaches the preset range; s4, on the premise of judging that the image integrity is good and the light source state is good, real-time displacement is calculated for each visual channel; and S5, comparing displacement calculation results of the visual data sources on the two sides, voting the consistency of calculation, and taking a displacement value passing the consistency voting as final train displacement measurement data. According to the invention, distance measurement of the highest SIL4 security integrity level can be realized.

The application relates to the technical field of defect detection imaging, and discloses a high-precision three-dimensional imaging method and system based on continuous magnetic flux leakage data. A magnetic flux leakage signal of a measured target surface is collected to form an initial signal set, and a convolutional neural network model is used to extract a feature vector; three-dimensional space data is separated, and a preliminary three-dimensional position coordinate of a defect is obtained through an iterative mapping algorithm; spatial geometric features are mined, potential geometric boundaries are determined, data is fused to construct a refined position model; a detection subset is extracted and shape errors are corrected, a space reconstruction grid is constructed and holes are filled, and a complete three-dimensional shape representation is obtained; through precision calibration and signal matching verification, high-precision three-dimensional imaging is output. Through the application, the positioning and shape reconstruction precision of defects can be effectively improved, the imaging integrity and accuracy are guaranteed, the problems of traditional magnetic flux leakage imaging positioning ambiguity and shape distortion are solved, and the defect detection requirements of complex measured targets are adapted.

The application belongs to the technical field of computers and specifically discloses a box clamping point estimation method and device based on a depth camera and electronic equipment, the method comprising: obtaining a pretreated image and a pretreated point cloud of a box through a depth camera; fitting a horizontal plane based on the pretreated point cloud, determining the horizontal plane, and obtaining a projected point cloud by projecting the point cloud to the horizontal plane; obtaining the positions of the four intersection points of the rectangular bottom surface of the box based on the projected point cloud and the size of the rectangular bottom surface of the box; and estimating the box clamping point based on the clamping point height and the positions of the four intersection points of the rectangular bottom surface. The application calculates the clamping point through the geometric features and size constraints of the point cloud, avoids the cumbersome operation of pasting a two-dimensional code, and improves convenience. Meanwhile, the calculation through plane fitting, point cloud projection and straight line intersection point determination reduces the dependence on the completeness of the box image, has better robustness, and reduces the instability of the result caused by incomplete images.

The invention belongs to the field of oral cavity skin flap shooting, and provides an oral cavity endothelial flap state shooting device which comprises a flexible shell, one side of the flexible shell is fixed and communicated with a sleeve, an inner cavity of the sleeve is provided with an extension tube, one side of the extension tube is provided with a plurality of angle adjusting mechanisms, and each angle adjusting mechanism comprises a connecting tube; through cooperative cooperation of the shooting mechanism, the flexible and adjustable extension tube and the angle adjusting mechanism, multi-angle and non-blind area imaging can be realized in a narrow oral space, key area omission caused by operation experience difference is avoided, the image integrity and comparability are improved, and the imaging efficiency is improved. The integrated camera module is combined with a high-resolution sensor, an infrared mode and annular illumination, the skin flap image definition and the blood supply monitoring accuracy are improved, imaging is more reliable, the extension tube is rapidly locked to the sleeve through the butt joint block and the insertion rod, tool disassembly and assembly are not needed, maintenance is simplified, and sealing performance and portability are improved.

This invention relates to the field of image processing and discloses an image filtering method based on machine learning. The key technical points of this method include image acquisition, light source feature acquisition, partitioning calculation, processing strategy matching, and image processing. A pre-trained machine learning model identifies regions affected by image illumination and accurately extracts multi-dimensional light source features. After partitioning the image, the confidence scores and influence scores of bright and dark areas are calculated by combining the light source features with the region's own features. Differential processing strategies and intensity parameters are then matched to optimize each region accordingly. This method effectively distinguishes between illumination changes and the intrinsic features of the detected object, solves the image distortion problem under complex illumination, fully preserves the features of the detected target, improves image integrity and usability, enhances the robustness and accuracy of the filtering method, and is suitable for complex detection scenarios in rail transit.

The invention relates to the technical field of fan detection, in particular to a method and a device for detecting fan operation parameters of a wind power tower drum, and the method comprises the steps: carrying out the detection of the fan operation parameters of the wind power tower drum based on fan blade images continuously collected by image collection equipment disposed on the wind power tower drum in the fan operation process; obtaining a central axis equation of the target fan blade closest to the image acquisition equipment; based on the central axis equation of the target fan blade corresponding to the multiple frames of fan blade images, the hub center coordinate of the fan is obtained; based on the hub center coordinate and the contour equation of the target fan blade, the maximum value and the minimum value of the rotation angle of the target fan blade are obtained; based on the maximum value and the minimum value of the rotation angle, the yaw angle of the fan is obtained; and obtaining the rotating speed of the fan based on the interval time of the maximum value of the rotating angle appearing in the multiple frames of fan blade images. According to the technical scheme, the inherent requirement for fan blade image integrity can be broken through, and the flexibility and accuracy of fan operation parameter detection are improved.

The present application provides an image correction method, device, and equipment, which includes: obtaining a pixel point to be corrected in an original image, and obtaining a first image area corresponding to the pixel point to be corrected from the original image, wherein the central pixel point of the first image area is the pixel point to be corrected; dividing the first image area into K pixel blocks, where K is a positive integer greater than 1; selecting a target pixel block from the K pixel blocks based on the pixel features corresponding to each pixel block; correcting the pixel value of the pixel point to be corrected based on the pixel features corresponding to the target pixel block to obtain the corrected pixel value of the pixel point to be corrected; and generating a corrected image based on the corrected pixel value of the pixel point to be corrected. The technical solution of the present application solves the problem of severe loss of detail information and effectively improves the detail restoration and image integrity of the image.

The application discloses an archive image data management system and method based on deep learning, and relates to the technical field of archive image data management.The method comprises the following steps: identifying an archive image and extracting a feature set thereof; monitoring keywords based on archive text features, verifying a first element and a second element in the archive; when an archive text feature tki appears in the archive image, determining whether the first element exists, and if not, adjusting the image integrity according to preset rules; if the first element exists, calculating the probability of the appearance of the text feature according to the frequency of the existence of the corresponding demand image when the text feature appears in historical data; comparing the calculated probability with a set probability threshold value, and if the calculated probability exceeds the set probability threshold value, increasing the archive image integrity by a set percentage point amplitude, and taking the adjusted integrity as the initial value for the next demand image probability calculation of the text feature, so that the archive image data management is realized.

The application provides a kind of multi-sensor fusion surgical procedure automatic management method and device, it is related to the technical field of automated process, method includes: by multi-source sensor data uniform timestamp alignment and space geometry solution, constructs the instrument pose flow and operating field geometric model under uniform coordinate system.Combining semantic segmentation and three-dimensional back projection generates occlusion probability graph and carries out cross-channel compensation reconstruction, improves image integrity.Through voxel field dispersion and short-time prediction, a conflict risk set is formed, and a standardized surgical procedure constraint is jointly solved to generate a scheduling instruction and a safety time window.Finally, the image, pose and physiological signal are mapped to the knowledge graph, the process node is identified by combining the timing attention, and the consistency discrimination and correction suggestion are output.The application can solve the problem of inaccurate surgical procedure management caused by the overlapping field of view of multi-source sensor data.

The invention discloses a robust zero watermark method based on Chebyshev-Fourier complex moment. The method aims at achieving high-robustness and lossless image copyright protection and is completed through three key steps of complex moment feature extraction, wavelet edge enhancement and zero watermark generation. The method specifically comprises the following steps: (1) a global image feature extraction module firstly maps an original image to a unit circle domain, calculates a Chebyshev-Fourier complex moment of the original image, extracts amplitude features with rotation and scaling invariance, and constructs stable initial feature representation; (2) a local feature enhancement module which introduces one-dimensional wavelet transform to process an amplitude sequence, captures a feature change trend by using a high-frequency coefficient, enhances the response ability to image edges and local details, and improves the feature stability under the attacks of cutting, noise and the like; and (3) the robust zero watermark generation module binarizes the enhanced features to form an image feature map, and generates a final zero watermark through XOR operation in combination with chaotic encrypted watermark information, thereby realizing copyright binding without modifying a carrier image. According to the method, on the premise that the image integrity is guaranteed, the resistance of a watermark system to geometric attacks and signal interference is remarkably improved, and the method is suitable for digital copyright protection and content authentication scenes with high safety requirements.

The application discloses an image integrity authentication method based on digital signature and image transformation and relates to information security, which comprises the following steps: using a digital certificate to perform digital signature on an original image; performing wavelet transformation on the original image; embedding a digital signature value of the original image in a high frequency domain; performing wavelet reconstruction to obtain an embedded signature image; extracting the digital signature value during verification; and verifying the extracted digital signature value; the application can embed a digital signature value of an owner of a digital certificate in an image without changing the visual effect of the image.

An image editing method and device, electronic equipment, storage medium and program product are disclosed. The specific implementation scheme comprises: determining a to-be-edited image and an embedding feature vector corresponding to the to-be-edited image; extracting a key point vector of the to-be-edited image; determining control information and an attribute control code corresponding to the control information; and generating an edited image based on the to-be-edited image, the embedding feature vector, the key point vector and the attribute control code. By determining the embedding feature vector of the to-be-edited image, the identity feature of the target object is extracted, the position of the target object is controlled through the key point vector, the occurrence of geometric misplacement is reduced, the multi-modal control is realized through the control information, the editing of the to-be-edited image is completed under the condition of ensuring the integrity of the image, and the accuracy of image editing is improved.

The invention relates to a vascular ultrasound image three-dimensional reconstruction method based on a depth camera and an IMU (Inertial Measurement Unit). High-precision three-dimensional reconstruction of a vascular region is realized by fusing data of a multi-source sensor. In the scanning process, a medical worker holds an ultrasonic probe by hand to obtain a two-dimensional ultrasonic image, meanwhile, a plurality of depth cameras distributed around the probe synchronously collect a depth image of a marker, and an IMU sensor synchronously obtains acceleration and angular velocity data of the probe. First preliminary three-dimensional pose information is extracted through depth image registration, a second preliminary pose is estimated in combination with an IMU pre-integration model, the two kinds of pose information are further fused through nonlinear optimization, and the precise three-dimensional pose of the ultrasonic probe at each moment is obtained. And for abnormal image frames appearing in scanning, image restoration is carried out based on pose trajectory interpolation and spatial interpolation reconstruction. And finally, the repaired two-dimensional image is registered with the corresponding pose, so that high-quality three-dimensional reconstruction of the blood vessel region is realized, and the image integrity and the reconstruction precision are improved.

This application discloses a method and related apparatus for generating text and images, relating to the field of computers. This application overlays elements onto an original underlying image based on the template features of a template image to generate initial text and images. Since the template features include the text style, layout, and background features of the template image, the text elements in the initial text and images can replicate the template style. Furthermore, the generated initial text and images undergo a base image integrity check. If the check passes, the initial text and images are output as the target text and images, ensuring that the final generated text and images possess base image integrity. Therefore, applying this application can achieve text and images generation tasks that meet the design requirements of text and images products, and can also achieve accurate replication of template images.

The invention belongs to the technical field of computers, and particularly discloses a box clamping point estimation method and device based on a depth camera and electronic equipment, and the method comprises the steps: obtaining a preprocessed image and a preprocessed point cloud of a box through the depth camera; fitting a horizontal plane based on the preprocessed point cloud, determining the horizontal plane, and obtaining a projected point cloud by projecting the point cloud to the horizontal plane; based on the projected point cloud and the size of the rectangular bottom surface of the box body, obtaining the positions of four intersection points of the rectangular bottom surface of the box body; and estimating the box body clamping point based on the height of the clamping point and the positions of the four intersection points of the rectangular bottom surface. According to the invention, the clamping points are calculated through the geometric features of the point cloud and the size constraint, thereby avoiding the tedious operation of pasting the two-dimensional code, and improving the convenience. Meanwhile, through calculation of plane fitting, point cloud projection and straight line intersection point determination, dependence on box image integrity is reduced, better robustness is achieved, and result instability caused by image incompleteness is reduced.

The invention discloses an AI parking space state detection method based on multimode data, and the method comprises the steps: collecting historical multimode data and same-period image data of a target parking space, building a training sample set after marking, inputting a pre-training model, and outputting the calibration weight of each sub-mode; multi-modal data and environment parameters are collected in real time, weighted calculation is carried out after weight is dynamically adjusted, and the state of no vehicle, standard parking or non-standard parking is judged according to a score interval; and if the integrity detection is not qualified, the image is complemented based on the calibration weight in combination with the multi-view and color features, and the state is verified. The method solves the problems that the prior art is susceptible to environmental interference, depends on image data and is low in detection accuracy, improves the robustness and environmental adaptability of parking space state detection, can achieve accurate recognition without images, and reduces the labor cost.

According to the image encryption method and decryption method based on fractal adaptive optical transformation, in the encryption process, fractal parameters are generated through quantum random seeds, a fractal phase diagram is generated through Julia set iteration, FFT, frequency domain phase modulation and IFFT are carried out on an original image through channels, mixing is enhanced through pixel scrambling, encrypted data and a visual blurred image are output, and the fractal adaptive optical transformation is realized. And storing the fractal parameters, the phase diagram and the data range metadata. In the decryption process, the encrypted image and the metadata are loaded, inverse pixel scrambling and channel FFT are executed, phase conjugation and IFFT are applied, the original data range is recovered according to the metadata, and MD5 is adopted to verify the integrity of the image. According to the method, optical transformation and digital image processing technologies are combined, so that the encrypted image is difficult to identify in the frequency domain and the space domain, and meanwhile, imaginary part information is reserved to realize perfect restoration during decryption. Metadata generated in the encryption process ensures the accuracy and integrity of decryption.