881 results about "Perspective transformation" patented technology

Aspects of the subject disclosure relate to a vehicle camera system for view creation of view locations. A device may include a processor that obtains first data and second data from different cameras of a vehicle. The first data may include an image representation of a scene in a first field of view being observed from a first perspective view and the second data may include an image representation of the scene in a second field of view being observed from the first perspective view in a second field of view. The processor may modify the first data and the second data by a perspective transformation to adjust the image representation to a second perspective view. The processor may create a stitched image representing the scene in a combined field of view observed from the second perspective view by stitching the modified first data with the modified second data.

The invention discloses a self-adaptive three-dimensional scene reconstruction method and system based on a single panorama, and belongs to the field of computer vision processing. The method comprises the following steps: firstly, generating a depth map through an indoor scene panorama and constructing an initial three-dimensional grid; then generating a multi-view image and a shielding mask thereof based on view conversion, forming a training sample pair for fine tuning of the diffusion completion model, and injecting scene prior information for the model; then extracting a grid boundary contour and calculating a central axis, and adaptively constructing a camera pose set; after the integrity of the grid is optimized through iteration completion, the grid is converted into a 3D Gaussian sputtering field, and Gaussian point parameters are optimized through multi-view data; in the optimization process, an up-sampling strategy of rendering error feedback and edge Gaussian points is adopted, and finally a scene model with complete geometric textures is output. According to the method, a high-quality three-dimensional scene is reconstructed from a single panorama through a structure self-adaptive completion and Gaussian refining technology, and the method is particularly suitable for immersive roaming reconstruction of indoor scenes.

The invention discloses a rice plant segmentation method and system based on view angle transformation and dense point clouds, and the method comprises the steps: scanning a rice field through employing an unmanned plane laser radar system, and obtaining the dense point clouds of a rice canopy; performing angle transformation processing on the dense point cloud by adopting an overlooking angle to obtain a two-dimensional image of the dense point cloud at the overlooking angle; calculating a homography matrix from the dense point cloud to the two-dimensional image, and establishing an accurate mapping relation between the three-dimensional point cloud and the two-dimensional image; for the two-dimensional image, carrying out segmentation marking on the rice plant by adopting a region marking method so as to realize accurate segmentation and individual marking of the rice plant on a two-dimensional plane; and endowing each point in the point cloud with a corresponding region mark number by using a mapping relationship between the three-dimensional point cloud and the two-dimensional image, and further obtaining a rice plant segmentation result of the whole dense point cloud. According to the method, high-precision rice plant segmentation is realized, and more reliable and efficient technical support is provided for precision agricultural management and phenotype analysis of rice.

The invention provides a method, device and equipment for determining the needle insertion depth in a fundus needle insertion image and a medium, and the method comprises the steps: obtaining a target fundus needle insertion image, and determining a plurality of first key points of a surgical needle in the target fundus needle insertion image based on a FAST corner detection algorithm; determining a plurality of second feature points of the target fundus needle insertion image based on the plurality of first key points, a plurality of first feature points of the reference image and a feature point matching algorithm; based on the plurality of second feature points and the first feature points, carrying out perspective transformation on the plurality of second feature points to a plane where the reference image is located, and obtaining a plurality of third feature points of the target fundus needle insertion image after perspective transformation; and based on the plurality of third feature points and the first feature point, determining the needle insertion depth of the surgical needle in the target fundus needle insertion image. The fundus needle insertion images of different shooting visual angles are converted to the same shooting visual angle as the reference image, the proportion of image pixels to the actual distance is unified, and the accuracy of needle insertion depth measurement in the fundus needle insertion images is improved.

The invention discloses a control method for an underwater cleaning robot, and the scheme can comprise the steps: S1, collecting an environment image of a to-be-cleaned region through a global camera, and carrying out the distortion correction and perspective transformation preprocessing, and obtaining a preprocessed image; s2, generating a static environment map according to the preprocessed image, wherein the static environment map comprises obstacles and dirt sub-regions; s3, adopting a multi-scale path planning strategy: firstly, dividing a map by using a first-scale grid, determining a cleaning end point, and planning an access sequence based on an A * algorithm; setting the first dirt sub-region as a target, and planning a path to a boundary turning point of the first dirt sub-region; dividing a map by using a second scale grid, and planning a path from a turning point to a cleaning end point; and updating the operation starting point and removing the processed area, and circulating until the operation path sequence is generated. And S4, the underwater cleaning robot completes cleaning operation on all the dirt sub-areas according to the planned path.

The invention provides a human body action recognition method based on machine learning, and solves the problem of action recognition in fitness training. According to the method, a Mediape framework is used for processing a video, key points of a human body are recognized, and a human body model is constructed; matrix perspective transformation is used for correcting video distortion, and the accuracy of the human body model is ensured; and the human body key points extracted by the Mediape are used as feature pairs to classify actions by using an SVM (Support Vector Machine). In addition, different training objects are distinguished by means of a YOLO-v7 model so as to adapt to the scene that multiple persons exercise at the same time. The high accuracy and performance of the method in action classification prove the potential of the method as a real-time feedback and guidance tool in fitness training. By accurately identifying and evaluating the athletic action, an individual can be helped to improve the athletic form and prevent athletic injury. The accurate motion recognition technology provides better fitness guidance and quality control for individuals.

The embodiment of the invention provides a GIS (Geographic Information System)-based metropolitan area safety video monitoring method and system. The method is applied to the technical field of image processing and comprises the following steps: acquiring a video picture of a coverage area in real time through a camera; performing real-time analysis on the video picture by using a target detection algorithm, and identifying a target in the video picture; converting the position of the target in the video picture into an actual geographic coordinate based on coordinate system conversion; continuously tracking the target in different camera coverage areas through the geographic coordinates; based on perspective transformation, converting the video image into an aerial view angle, and splicing aerial views to form a panoramic view; and visualizing the geographic coordinates of the target in the aerial view. In this way, the efficiency and accuracy of the city monitoring system can be improved, and therefore the requirement for city safety monitoring can be better met.

The invention discloses a method for a mowing robot to move along a lawn boundary based on a local grid map, and relates to the field of mowing robot edge navigation movement, and the method comprises the steps: recognizing a target region and an obstacle region through a semantic segmentation algorithm, constructing a dynamically updated local grid map through the combination of improved inverse perspective transformation and depth point cloud information, and carrying out the navigation of the target region and the obstacle region; no physical boundary dependence is realized, the deployment cost is reduced, and the real-time processing efficiency of acquired images can be improved; according to the local grid map, the edge navigation deflection angle is calculated through lawn boundary feature extraction in combination with the position of the robot, precise navigation of the robot along the lawn boundary is achieved, rapid response of dynamic obstacles is supported, and the edge movement precision and operation efficiency of the mowing robot are remarkably improved. The problems that an existing mowing robot is low in edge movement precision and poor in operation efficiency due to the fact that an edge track cannot be decided in real time and calculation efficiency cannot be considered at the same time are solved.

The invention provides an evidence obtaining method and system based on image processing, and the method comprises the following steps: S1, generating a pixel-level depth-of-field distribution diagram of an input image through a multi-scale encoder-decoder network, employing an edge perception optimization layer in a decoding stage, and improving the depth-of-field boundary precision through minimizing a local gradient consistency loss function; s2, performing depth-of-field rationality verification based on an optical imaging physical model, and triggering a first-level tampering alarm by calculating a defocusing fuzzy radius and a gradient direction of a selected region when a difference between the defocusing gradient directions of a target region and a background region exceeds a preset threshold value; and S3, dynamically positioning a key pixel region, identifying a depth-of-field mutation boundary by using an edge detector, calculating by combining local texture complexity, screening a pixel set of which the entropy value is higher than a threshold value and which is located at the mutation boundary, correlating metadata to verify the rationality of the physical size and the spatial position of an object, and eliminating false detection caused by perspective transformation.

The invention discloses a heading equipment cutting head position calibration method based on image acquisition, which comprises the following steps: S1, acquiring image data and preprocessing the image data; s2, extracting cutting head feature points, and constructing a two-dimensional feature point set; s3, calculating a three-dimensional coordinate by using perspective transformation, and generating a point cloud set; s4, performing rigid registration on the point cloud set and a standard structure model of the tunneling equipment, and iteratively solving a rotation matrix and a translation vector to obtain pose parameters; s5, simulating change tracks of the feature points in continuous frames, constructing a time consistency constraint, and optimizing pose parameters; s6, the optimized three-dimensional coordinates are converted to a reference coordinate system, space alignment is completed, and a position calibration result is generated; and S7, outputting a calibration result for control instruction generation and path planning. According to the invention, high-precision and non-contact three-dimensional position calibration of the cutting head of the tunneling equipment is realized, and operation automation and control precision are improved.

The invention relates to the technical field of information, and discloses a parking lot panoramic safety monitoring method and system, and the method comprises the steps: obtaining a real-time video stream of a parking lot, and carrying out the denoising preprocessing of each frame of image, and obtaining a clear image; adjusting the brightness and the contrast ratio of the clear image by adopting a self-adaptive illumination compensation algorithm to obtain an illumination compensation image; according to the angle and distance change of the vehicle, correcting the vehicle image visual angle in the enhanced image by adopting a perspective transformation algorithm to obtain a perspective transformation image; identifying a vehicle position and a bounding box in the perspective transformation image by adopting a vehicle detection model based on deep learning, and determining a specific position of the vehicle in the image; and in the vehicle dense area, a multi-target tracking algorithm is combined with the moving tracks and the feature information of the vehicles, the shielding relation between the vehicles is judged, and the positions of the shielded vehicles are determined. The method can realize panoramic safety monitoring of the parking lot.

The invention discloses an inclined pointer instrument accurate reading identification method based on a cascade model. The problem that a traditional method is low in reading accuracy under the scenes of complex backgrounds, inclined shooting and the like is mainly solved. The method comprises the following steps: constructing a cascade model: positioning an instrument area through an instrument detection model, cutting the instrument area, analyzing scale line and pointer features through an instrument feature extraction model, and extracting a dial center, a main scale line and a pointer position in combination with key point detection and a semantic segmentation technology; inclination correction optimization: calculating a perspective transformation matrix according to the main scale line endpoint coordinates, performing rotation correction on the inclination instrument image, and eliminating a visual angle inclination error; and angle method reading calculation: based on the corrected image, realizing accurate reading by combining the angle relation between the pointer and the adjacent scale lines with OCR identification scale values. According to the method, the recognition accuracy and robustness in a complex scene are remarkably improved, computing resources are reduced, and the recognition precision of instrument reading is improved.

Mechanisms are provided for automated document image annotation and data extraction. A received document image is processed to identify a document type of the received document image, and retrieve a corresponding document template having key point location data and annotation location data for documents of the document type. First key points of the received document image are matched with second key points of the corresponding document template and a mapping is generated to map locations of the document template to locations of the received document image. A perspective transformation is applied, based on the mapping, to first annotation locations specified in the document template data structure to generate second annotation locations corresponding to locations in the received document image. Data extraction is performed on data associated with the second annotation locations based on the annotations corresponding to the second annotation locations.

The invention discloses a coal mine belt deviation real-time lightweight detection device and a coal mine belt deviation real-time lightweight detection method based on image sub-pixels, firstly, the device captures video streams of belt operation in real time through an image acquisition device, analyzes the video streams in real time by means of edge computing nodes, and monitors the running state of a belt in real time to determine the deviation of the belt; once the belt starts to work, image distortion caused by a shooting angle or environment is immediately corrected through perspective transformation. Secondly, automatically selecting a high-contrast reference strip through an image preprocessing method, and accurately extracting a region near the belt edge as a minimum region of interest, namely a belt edge region; then, a lightweight sub-pixel convolutional neural network is used to carry out deep analysis on the areas, and a high-quality super-resolution image is generated, so that the accuracy of edge detection is further improved. And finally, accurately identifying and positioning the edge position of the belt by introducing a bidirectional edge tracking method with an abnormal detection function, thereby realizing real-time and accurate detection on the deviation condition of the belt.

The invention relates to a monocular vision tower span measurement method based on RTK correction, and belongs to the technical field of space distance measurement. Comprising the following steps: acquiring ambient light intensity and quality in real time based on an environment where a power transmission and distribution tower is located, and obtaining ambient light adaptation parameters by analyzing ambient light data and adjusting ISO sensitivity and shutter speed of a camera. According to the method, real-time environment light data analysis and camera parameter automatic adjustment are introduced in the monocular vision tower span measurement process, the image quality is effectively improved, tower recognition is more accurate, background interference is reduced, the geographic position and the shooting angle of a shooting point are corrected through the RTK technology, and the measurement accuracy is improved. And perspective transformation correction is carried out on the image in cooperation with a perspective projection theory, and the accuracy of distance measurement data is improved to centimeter level.

The invention discloses a pavement disease positioning and size calculation method and system, and relates to the technical field of road disease detection.The method comprises the steps that the rolling angle of a pavement image is corrected to obtain a corrected image, and the position and shape coordinates of a pavement disease in an image coordinate system of the corrected image are determined; determining the position and shape coordinates of the pavement disease in the overlook coordinate system according to the position and shape coordinates of the pavement disease in the image coordinate system of the corrected image by adopting a perspective transformation matrix of the image coordinate system of the corrected image and the overlook coordinate system; determining the position of the pavement disease in the world coordinate system according to the position coordinate of the pavement disease in the overlook coordinate system by adopting the conversion relation between the overlook coordinate system and the world coordinate system; and calculating the size of the pavement disease in the overlook coordinate system according to the shape coordinates of the pavement disease in the overlook coordinate system. The perspective transformation relation from the image coordinate system to the overlook coordinate system is corrected in real time, and then the accuracy of pavement disease size and positioning data calculation is improved.

Three-dimensional Gaussian splatting mechanisms that initialize a set of 3D Gaussian distributions, un-project pixels from two-dimensional (2D) planes to 3D space by applying queries to the 3D Gaussians at expected un-projected ray depth positions, and splat the 3D Gaussian distributions on the 2D planes based on the expected un-projected ray depth positions.

The invention discloses an appearance detection multi-camera image splicing method and system and a related device, which are used for improving the overall quality and accuracy of image splicing in a multi-camera vision field non-overlapping scene. The method comprises the following steps: respectively calibrating a main camera and an auxiliary camera through a calibration board in combination with a weighted error minimization model; determining a pixel plane transformation matrix from the auxiliary camera to the main camera; transforming an initial image shot by the auxiliary camera to a pixel plane of the main camera according to the pixel plane transformation matrix; projecting the vision fields of all the cameras into a world coordinate system, and judging whether the projection positions of the vision fields are overlapped or not; if yes, feature points are extracted from the to-be-spliced image, the feature points are screened through a distance threshold value and a quality threshold value, and a feature point pair set is obtained; and calculating a perspective transformation matrix between the to-be-spliced images based on the feature point pair set, and splicing and fusing the to-be-spliced images according to the perspective transformation matrix and the vision field projection position.

The invention discloses a pixel equivalent measuring method based on mobile terminal pupil distance intelligent measurement, which comprises the following steps: calibrating a camera, and correcting distortion through internal and external parameters obtained through calibration; image preprocessing, including image pre-identification and image enhancement, and highlighting the edge and angular point features of the image; coarse positioning of the calibration object: acquiring rough positions of corner points at four corners of a square frame of the calibration object; carrying out angular point coordinate coarse positioning, and carrying out mask processing on the image by taking an obtained angular point and a two-dimensional neighborhood thereof as a range; refining the coordinates of the angular points, correcting and compensating the angular points, and obtaining the coordinates of the four corrected angular points; performing perspective transformation; determining a pixel equivalent and a transformation matrix; carrying out verification measurement; and verifying and optimizing the determined pixel equivalent. According to the invention, an image processing technology is utilized to solve the calibration problem during the pupil distance measurement of the mobile end, and a small-range straight angle point precision compensation method is utilized to automatically compensate error defects, so that the pupil distance measurement precision is improved, and a new idea is provided for the existing method.

The invention belongs to the technical field of autonomous vehicles, and particularly relates to a vehicle end visual angle accident scene restoration method based on an automobile data recorder video. Comprising the following steps: step 1, preprocessing an accident video; 2, performing semantic understanding on the scene; step 3, extracting pixel tracks of the traffic participants; step 4, carrying out joint calibration on the inverse perspective mapping parameters; 5, carrying out inverse perspective transformation; step 6, carrying out post-processing on the road contour and track data; for accident video data with unknown and different camera parameters and lack of multi-source synchronization information, the invention provides a vehicle-end visual angle accident scene restoration framework taking a camera inverse perspective mapping parameter joint calibration strategy as a core. Scene space-time information including a road contour and a traffic participant track can be extracted from an automobile data recorder video without any prior information support, accident scene data is established for testing an automatic driving automobile, and the testing process of the automatic driving automobile can be effectively improved.

The invention discloses a multi-view construction personnel tracking method and system based on attention perception. The method comprises the following steps: giving synchronous images from S cameras, and inputting the synchronous images into an encoder for feature extraction to obtain a multi-view feature map; transforming the multi-view feature map into a unified aerial view space by using perspective projection, and aggregating features after projection transformation of all views by using a convolutional layer; inputting the aggregated aerial view features into a decoder for decoding; a cross attention module is introduced, bird's-eye view features of a current frame and an adjacent frame are processed through 3D position coding, instance tokens are extracted as query, keys and values, an affinity matrix is generated through CNN coding similarity, features are propagated through matrix multiplication, and the bird's-eye view features of the current frame are updated. According to the method, the multi-view feature map is projected to the aerial view to realize early fusion, and a cross-frame attention mechanism is introduced, so that the problem of appearance feature distortion caused by perspective transformation is solved.

The invention provides a core photograph automatic correction and cutting method based on YOLOv8-seg and perspective transformation, and belongs to the technical field of image processing, and the method comprises the steps: S1, collecting a core box image; s2, polygonal point sequence labeling; s3, obtaining an optimal segmentation model; and S4, cutting. Aiming at the problems of much manual intervention, low efficiency and poor adaptability in the existing core photograph processing, the invention provides a set of full-automatic end-to-end solution without preprocessing, realizes rapid and stable correction and cutting of the core photograph in a complex scene, relieves the mechanical labor burden of geological personnel, focuses on the core exploration work, and improves the core exploration efficiency. And the practical application requirements of large-scale geological exploration projects are met.

The embodiment of the invention discloses a video generation method and device, electronic equipment, a computer readable storage medium and a computer program product, and the method comprises the steps: generating a rough three-dimensional world of a target scene formed by a three-dimensional Gaussian ball set, and automatically searching a multi-angle offset view angle at the same coordinate position as a new view angle. According to the method, a multi-view-angle combined repairing mechanism is realized, geometric and semantic consistency of image data among different view angles is ensured, consistency of scene structures, textures and semantic information at different observation angles is realized, and a continuous, coherent and high-quality three-dimensional world is constructed. According to the method, the problem of multi-view inconsistency in a traditional method is solved, the new view image quality under large view conversion is improved, the image quality problems of floating objects, artifacts, structural distortion and the like in the image are eliminated, the generated image is more stable and real, the spatial continuity is improved, and the immersion and exploration experience of a user are enhanced.

The invention provides a core photograph processing method based on perspective transformation and a graphical user interface. The core photograph processing method comprises the following steps: S1, collecting a high-definition core photograph; s2, establishing a graphical user interface; s3, defining and designing a user-defined function for selecting the core photos, and acquiring file paths of all the core photos to be processed in batches by using the function; s4, defining and designing a user-defined function to obtain four angular points of the core picture selected in the S3, performing perspective transformation, and storing the four angular points; s5, creating a'batch selection photo 'button and an'interactive perspective transformation' button, and binding the buttons with the custom functions in S3 and S4; and S6, performing packaging on the steps S2 to S5 by using Anacoda, and creating an exe executable file. According to the method, on the premise that the core box does not need to be preprocessed, a method for rapidly and accurately correcting deformation and cutting a large number of core photos is provided for geologists based on the graphical user interface.

The invention relates to the technical field of scene matching navigation, and provides a multi-mode scene matching navigation positioning method and device for a self-adaptive variable-structure unmanned aerial vehicle. According to the method, geographic coordinates corresponding to all pixel points in an aerial image are determined according to pose information in the aerial image of the unmanned aerial vehicle, and the geographic position of the unmanned aerial vehicle with errors is corrected based on difference information between the pixel coordinates of the central point of the aerial image of the unmanned aerial vehicle and the geographic position corresponding to the center of a camera. Based on the corrected geographic position of the unmanned aerial vehicle, determining a reference image pixel coordinate corresponding to the angular point pixel coordinate of the aerial image, and obtaining a simulated aerial image under the view angle of the unmanned aerial vehicle through perspective transformation so as to determine a homography transformation matrix; according to the method, the satellite reference image pixel coordinates of the interest point in the aerial image are determined based on the homography transformation matrix and the perspective transformation matrix, and finally the longitude and latitude of the interest point are determined, so that the limitation of the traditional method in view angle difference compensation, computing resource constraint and cross-modal processing is solved, and the universality, robustness and positioning accuracy of the system are improved.

The invention provides an indoor human body positioning and track generation method and device, equipment and a medium, and the method comprises the steps: obtaining target Bluetooth data and position data with timestamps, achieving the data fusion through a data fusion algorithm, and obtaining a first moving track point set; based on a preset data acquisition period and timestamp information of each track point of the first moving track point set, when the track points are missing, detecting by using a computer vision algorithm and determining a corresponding target by using a tracking detection algorithm based on video data acquired by monitoring equipment, and obtaining an image sequence containing the target; determining an actual physical coordinate of a target in each image based on camera calibration and perspective transformation, obtaining an image positioning result and a second moving track point set, and aligning with a timestamp of the first moving track point set and realizing data fusion to obtain a third moving track point; and according to the map information, matching each track point of the third moving track point set to a grid map to form a target track map.

The invention discloses an automatic cattle checking method and system based on two-dimensional panoramic vision, and belongs to the technical field of computer vision and intelligent breeding, and the method comprises the following steps: reasonably arranging a plurality of fixed cameras in a cattle farm area, obtaining the internal reference and distortion coefficient of each camera through employing a camera calibration technology, and obtaining the internal reference and distortion coefficient of each camera; performing real-time distortion correction on the collected video frames; on the basis of side-by-side splicing or homography matrix perspective transformation, all paths of corrected images are fused into a complete two-dimensional panoramic image, and a view blind area of a single camera is eliminated; calling a lightweight target detection model on the panorama, and extracting bounding boxes and confidence coefficients of all cattle at one time; sorting according to the confidence from high to low, performing IOU non-maximum suppression de-duplication on the detection frame, and ensuring that the same cattle only counts once in an overlapping region; and the whole process is completed through the edge computing node. According to the invention, efficient, real-time and accurate on-site cattle checking of a large-scale cattle farm can be realized.

The invention discloses a display screen fault detection method, system and device and a storage medium, and the method comprises the steps: obtaining a monitoring video stream of a display screen, and obtaining a display screen monitoring image set according to the monitoring video stream; performing perspective transformation on the display screen monitoring image set to obtain a display screen correction image set; performing feature extraction on the display screen correction image set to obtain a display screen feature image set; detecting the display screen feature image set by using a pre-trained fault detection model to obtain fault types corresponding to the display screen feature images in the display screen feature image set one by one; and when the fault types of all the display screen feature images meet a preset condition, determining that the display screen has a fault, and outputting a target fault type corresponding to the display screen. According to the invention, real-time intelligent fault detection of the display screen can be realized, the accuracy is high, various types of display screen faults can be detected at the same time, full-automatic intelligent detection alarm is realized, manual inspection by operators on duty is not needed, and the operation and maintenance efficiency is improved.

The invention discloses a multi-camera synchronous electronic image stabilization method and device based on virtual camera imaging, and the method comprises the steps: obtaining and splicing images captured by all cameras in a multi-camera cooperative imaging system, and constructing a virtual camera image; calculating the translation offset of the virtual camera according to the perspective transformation matrix between the adjacent cameras, and calculating the internal reference of the virtual camera; converting the pixel coordinate system into a to-be-stabilized virtual camera coordinate system according to the internal reference of the virtual camera; converting the compensation amount to a virtual camera coordinate system to be stabilized; calculating an image stabilization rotation matrix for converting the coordinate system of the virtual camera to be stabilized into the coordinate system of the stable virtual camera; and converting the to-be-stabilized image from the stable virtual camera coordinate system to the pixel coordinate system according to the image stabilization rotation matrix and the internal reference of the virtual camera to obtain a stabilized image. The method can be applied to multi-camera synchronous electronic image stabilization in a multi-camera collaborative imaging system, and high-quality anti-shake video real-time output is realized.

The invention discloses a digital watermark registration positioning method based on linear Hough transform, which is applied to positioning and identification of a digital watermark on a digital image, and comprises the following steps: encoding input data, adding random offset, generating basic unit watermark blocks, paving the basic unit watermark blocks, and reserving intervals for a linear detection positioning algorithm. In the extraction algorithm, firstly, preprocessing and a Hough straight line detection algorithm are carried out on a carrier image, detected straight lines are grouped, intersection point information between two groups is calculated, vertex positions of basic unit watermark blocks are positioned by calculating the mutual position relation between intersection points, and then perspective transformation correction is carried out on each basic unit watermark block. And the embedded basic unit watermark block information is obtained. And then extracting coding information from the basic unit watermark block, and sequentially carrying out mask removal, error correction and decoding to recover original embedded information. The invention further discloses a system and application for implementing the method, and the system and the application have wide application value.