46 results about "Minimum bounding rectangle" patented technology

The invention provides a textile surface defect detection method and system based on image features, and relates to the technical field of textile surface defect detection.The method comprises the steps that an RGB image of a to-be-detected textile is obtained and zoomed to 512 * 512 pixels, and then at least five semantic tags are output through a semantic segmentation model; the method comprises the following steps: adopting hyperspectral imaging with the wavelength of 400-1700 nm and the resolution of 10 nm, calculating the pixel reflectivity through a reflectivity formula, comparing the reflectivity of 5-8 characteristic wavebands, marking as a pollutant if the average deviation exceeds a threshold value, matching the type and position of a stain with a spectral angular distance, and after a standard sample and a semantic region are converted into an LAB color space, extracting a minimum rotation enclosing rectangle and dividing a grid, invalid pixels are filled with 3 * 3 neighborhood effective pixel weighted mean values, and a grid LAB mean value is calculated. A grid pollutant pixel corresponding to an image to be detected is filled with a standard sample in a mean value mode, then channels A and B are clustered through a sliding window, a pilling area is preliminarily judged according to the standard deviation of a channel L, and the pilling area is confirmed by combining the structured light three-dimensional point cloud and comparing with a threshold value.

The invention relates to the technical field of image processing, and provides a power equipment installation inclination degree identification method and system, a medium and equipment, and the method comprises the steps: obtaining a power equipment inspection image, and carrying out the segmentation of a power equipment box through a deep learning instance segmentation method, and obtaining a box mask image; based on the box body mask image, carrying out box body minimum enclosing rectangle fitting by adopting an equal-interval rotation search method to obtain an inclination angle of the box body; wherein the equal-interval rotation searching method comprises the following steps: continuously rotating a box mask image for multiple times in the same direction, increasing the rotation angle at equal intervals, recording the minimum enclosing rectangle of the box mask image in each rotation, and calculating the area of the minimum enclosing rectangle obtained in each rotation; and finally, the minimum enclosing rectangle corresponding to the minimum area is selected as the minimum enclosing rectangle obtained by fitting, and the rotation angle of the minimum enclosing rectangle obtained by fitting is taken as the inclination angle of the box body, so that the calculation amount and the calculation complexity are effectively reduced.

The invention provides an outdoor power transmission channel hidden danger identification method and system based on semantic segmentation, and the method comprises the steps: marking a small target region in long-tail distribution from an outdoor power transmission channel image, carrying out the geometric transformation after cutting out the small target region, and carrying out the cross-image migration to generate a migration image; performing illumination correction on the migrated image to generate an enhanced image; constructing a semantic segmentation model for hidden danger recognition, and inputting the enhanced image into the semantic segmentation model to extract each semantic region and corresponding mask in the enhanced image; screening out abnormal masks from the masks and deleting the abnormal masks, and then removing existing cavity areas to obtain residual masks; and clustering and merging the remaining masks to generate a minimum enclosing rectangle with a rotation angle as a final detection frame. Based on the method, the invention also provides an outdoor power transmission channel hidden danger identification system based on semantic segmentation. According to the method, the outdoor power transmission channel hidden danger identification precision and efficiency are remarkably improved, and safe and stable operation of a power transmission line is ensured.

The invention discloses a bulk cargo cabin real-time fusion detection method based on a laser point cloud, and the method comprises the steps: obtaining a real-time three-dimensional scene point cloud of a port scene, and obtaining a deck plane equation and a normal vector; projecting the three-dimensional scene point cloud to a two-dimensional deck plane, and constructing an intensity image taking point cloud intensity as information and a depth image taking projection distance as information; obtaining an intensity mask image from the intensity image; acquiring a depth edge image according to the depth image, and fusing the depth edge image and the intensity mask image to obtain a fused edge image; contour extraction is carried out on the fused edge image, polygon fitting is carried out, a quadrangle in the fused edge image is reserved as a candidate cabin, and a minimum enclosing rectangle of the quadrangle is obtained; and obtaining four vertex coordinates of the minimum bounding rectangle, and back-projecting the four vertex coordinates to the three-dimensional space to obtain three-dimensional space rectangular coordinate points of the final cabin. The method is suitable for a complex environment and a dynamic scene in a port operation area, and the cabin in the dynamic scene can be obtained in real time.

This invention discloses a method and system for quality monitoring and defect localization in a selected area laser melting process. The invention involves real-time acquisition of molten pool images during the selected area laser melting process; extraction of molten pool contours from images belonging to the same printing layer, calculating the molten pool area and the center point of the minimum bounding rectangle of the molten pool contour; creation of a blank image of the same size as the molten pool images, and marking the center point of the minimum bounding rectangle of each molten pool contour at the corresponding position in the blank image; grid division of the blank image, filling the marked grid with the corresponding molten pool area value to generate a grid matrix; segmentation of the grid matrix, converting each segment into a grayscale sub-image; and inputting the grayscale sub-images into a trained neural network model to obtain quality classification results.

This invention discloses a method and system for accurate counting of dense copper sheets based on semantic segmentation and image processing. The method includes: acquiring a large field-of-view image of dense copper sheets; labeling and cropping the copper sheets in the image, and inputting the cropped image and labels into a Unet semantic segmentation network for training to obtain a trained Unet network model; setting the input image of the trained Unet network model to the original image size, and performing inference on the original image to obtain a preliminary inference map; performing an opening operation on the preliminary inference map to filter out small imperfections, and performing dilation to obtain large columns of copper sheets; correcting the angle of the minimum bounding rectangle of the large columns of copper sheets; and forming a peak-and-valley image through affine transformation, projection integration, and filtering, and counting the number of copper sheets in all large columns of copper sheets in the image by counting the number of peaks. This invention effectively solves the problem of achieving high-precision counting in scenes with mottled and densely arranged copper sheets.

This invention discloses a method and system for small target detection in remote sensing images based on multi-scale features. The method involves: acquiring a remote sensing image to be detected; performing dehazing and brightness enhancement processing on the remote sensing image; inputting the brightness-enhanced image into a trained remote sensing image small target detection model to obtain the small target detection result; and the working principle of the trained remote sensing image small target detection model includes: extracting multi-scale features from the brightness-enhanced remote sensing image; performing feature fusion and feature enhancement on the extracted multi-scale features to obtain a feature map; fixing the size of regions of interest of different sizes in the feature map to obtain proposed candidate boxes for the target; applying non-maximum suppression to the extracted proposed candidate boxes to obtain the predicted bounding box coordinates of the target; drawing the minimum bounding rectangle of the target's region; and using the minimum bounding rectangle as the predicted bounding box of the target to obtain the target detection result in the remote sensing image.

The invention discloses a face dynamic feature detection method and system based on continuous frames. The method comprises the following steps: performing face detection on a preprocessed video frame by adopting a RetinaFace model of a quantized adaptive edge device NPU to obtain a face bounding box with the highest confidence coefficient; inputting the adjusted face image into the quantized PFLD model, extracting 98 key points and mapping the key points back to an original image space; eye and mouth key points are extracted according to a predefined index, and three sub-regions are obtained through minimum enclosing rectangle expansion cutting; inputting the sub-region images into a quantized ResNet binary classifier, and outputting eye opening and closing and mouth closing / yawning states; n frames of results are recorded through a sliding window, facial dynamic features and fatigue levels are judged according to a majority voting aggregation state, and finally the results are packaged into a JSON format and transmitted in real time through a UDP protocol. The method is light in weight, high in real-time performance, capable of accurately detecting the face dynamic features and adaptive to edge device deployment.

The invention provides a time sequence ROI multiplexing human body posture serial detection method and device, equipment and a medium, and the method comprises the steps: carrying out the full-image target detection of a key frame of an input video sequence, outputting the coordinates of a human body bounding box through a lightweight target detection algorithm, and filtering a redundant box with the confidence lower than a preset threshold value; then executing local posture estimation on the human body bounding box area, outputting 35 key joint point coordinate sets and confidence degrees thereof, and filtering low-confidence-degree joint points of which the confidence degrees are lower than a preset joint point threshold value; performing local attitude estimation on an extended ROI (Region of Interest) region of a previous frame multiplexed by an adjacent non-key frame, wherein the extended ROI region is obtained through equal-proportion extension based on a minimum bounding rectangle of effective articulation points of the key frame; sequentially processing the video frame sequence according to a preset key frame interval N, and upgrading the current frame into a key frame when a full-image detection triggering condition is met; ensuring; on the premise that the precision is not sacrificed basically, the processing speed of human body target detection and posture estimation in the video stream is greatly improved.

The application discloses a kind of supporting million-level vector data online real-time editing method, equipment and medium, it is related to spatial data collaborative processing technical field, including, based on real-time state notification to the dynamic rendering of standardization element sequence, renderable standardization element is rendered to green, standardization element of multiple-user operation is rendered to yellow, render standardization element that cannot be operated to red;When the standardization element of user operation is yellow or red, real-time interception is carried out and push prompt is pushed, and structured operation log is generated;The adjacency, connectivity and conflict-free containing relationship of element change coordinates in structured operation log and topological snapshot index are verified, processing patch is generated by identifying topological fracture point and executing spatial interpolation connection, while marking the element coordinate set needing to be processed, the minimum bounding rectangle is calculated to output reprocessing area coordinates.The application realizes memory occupation essential optimization by density adaptive streaming processing mechanism.

The invention discloses a building spacing intelligent calculation method based on a spacing standard analysis model. The building spacing intelligent calculation method comprises the following steps: S1, normalizing a designed building scheme general plan; s2, calculating an effective building height; s3, extracting an effective building outline range, removing parts which do not need to participate in building spacing calculation from the building outline range, and extracting an effective building outline range which is reserved to be included in spacing calculation; s4, generating a convex hull of the effective building contour; s5, generating a minimum bounding rectangle corresponding to the convex hull according to the convex hull generated in the step S4; s6, determining a minimum spacing standard under different conditions; s7, calculating the minimum distance of the building under different conditions in the design scheme; and S8, a calculation result is generated, if the minimum building distance obtained through calculation in the step S7 is larger than or equal to the corresponding minimum distance standard in the step S6, the distance meets the standard requirement, and otherwise, the design does not meet the standard requirement.

This invention provides a method and system for identifying and segmenting mixed-issue documents. The method includes the following steps: after detecting the documents, multiple mask data of individual documents are obtained; the mask data is filtered according to a set threshold to obtain mask data that meets certain conditions; after merging the mask data that meets the conditions, the minimum bounding rectangle is calculated; and the positions of the obtained minimum bounding rectangle are segmented using an array method. This method for identifying and segmenting mixed-issue documents detects different documents without missing any, achieving high accuracy and effectively improving the efficiency and accuracy of document classification while saving manpower, thus possessing significant application value.

This invention discloses an adaptive template registration method based on image grayscale. First, FAST corner points are extracted from the image to be registered. Then, the corner points are clustered, and the minimum bounding rectangle of each set is extracted. The region enclosed by the minimum bounding rectangle in the image to be registered is used as the template to complete adaptive template extraction. Next, a normalized cross-correlation algorithm is used for matching in subsequent image sequences. Finally, the affine transformation coefficients of the image are calculated using the coordinates before and after template matching, and the image to be registered is subjected to an affine transformation to achieve image registration. This invention, through its grayscale-based adaptive template image registration method, provides an adaptive template selection method under different background conditions, solving the problems of fixed template position and limited template information in previous methods, improving the template matching accuracy, and showing good application prospects.

A method for determining a spatial two-tuple is performed by a computer device. The method comprises: obtaining a given spatial distance and multiple spatial objects, wherein each spatial object belongs to a first spatial object set or belongs to a second spatial object set (101); determining a global area according to a minimum bounding rectangle (MBR) and an extended minimum bounding rectangle (EMBR) corresponding to the first spatial object set and an MBR and an EMBR corresponding to the second spatial object set (102); performing subspace division on the global area to obtain multiple subspaces (103); partitioning the multiple spatial objects according to a positional relationship between each spatial object and each subspace to determine spatial objects comprised in each subspace (104); and according to a spatial distance between the spatial objects of each subspace, determining a spatial two-tuple comprised in each subspace that matches the given spatial distance (105).

This application belongs to the field of digital twin basic data management technology. This application provides an automated method and apparatus for generating spatial identity codes for basic geographic entities. The embodiments of this disclosure acquire the geometric and classification information of basic geographic entities under a unified spatiotemporal reference, automatically calculate the minimum bounding rectangle / minimum outer cube, adaptively select the minimum grid level that can contain the geometric range, and generate two-dimensional or three-dimensional location codes level by level according to the BeiDou grid location code rules. These are combined with classification codes and sequence codes to form a standard field; then, a proprietary identification field is formed by combining this field with root identifier codes and special codes, and extended fields are added as needed to achieve interaction with external codes. This can realize the automated generation, verification, parsing, and traceability of spatial identity codes in scenarios such as provincial, municipal, and county collaborative production updates, two-dimensional / three-dimensional integrated database construction, semantic association, and service publishing, providing unified support for the data organization and management of basic geographic entities and cross-industry interconnection.

This invention provides a method, computer device, and storage medium for processing geometric data of layout files. The method includes acquiring a layout file of a 3D chip, extracting polygonal entities and layer information, assigning polygonal entities to corresponding layer containers, and creating an independent R-tree index for each layer; performing connectivity analysis on the polygonal entities, returning a set of connected components and performance analysis statistics; when creating an independent R-tree index for each layer, acquiring data for all polygonal entities in a single layer, generating a minimum bounding rectangle for each polygonal entity, constructing R-tree indexes in parallel for different layers using multiple threads, and determining whether the number of node entries in the R-tree index exceeds a splitting threshold; if so, splitting the node; and verifying the consistency between the created R-tree index and the original data. The computer device and storage medium are capable of implementing the above method. This invention can improve the efficiency of geometric data processing of layout files.

This invention provides a method, apparatus, electronic device, and storage medium for determining GeoHash codes. First, the minimum bounding rectangle of the region to be identified is determined. Next, the GeoHash codes corresponding to the vertex grids containing any three vertices of the minimum bounding rectangle are determined. Then, based on the GeoHash codes of the three vertex grids, a preset character table is looked up multiple times to determine the GeoHash codes of all grids within the minimum bounding rectangle. Finally, from the GeoHash codes of all grids, the GeoHash codes of each target grid that overlaps with the region to be identified are selected. In this invention, the preset character table includes 32 characters from a Base32 encoding table, and the positions of these 32 characters in the preset character table are determined based on the encoding principle of GeoHash codes. Therefore, the GeoHash codes of all grids within the minimum bounding rectangle can be determined by looking up the table. Compared to the multiple encoding conversions in existing technologies, this invention uses a table lookup method, reducing the computational load and improving the computational speed.

The application discloses an intelligent chessboard control method and device based on an ink screen, equipment and a medium, and relates to the fields of electronic display technology and chess game equipment. The method comprises the following steps: detecting a chess game state change event, determining a logical grid with a state change; calculating a minimum bounding rectangle based on the mapping relationship between the logical grid and the pixel; expanding the minimum bounding rectangle into a final refresh rectangle containing the affected logical grid according to a preset chess rule; dynamically configuring driving waveform parameters according to the area ratio of the final refresh rectangle; and performing a local refresh operation only on the display area corresponding to the final refresh rectangle. Through rule-aware local refresh and waveform adaptive adjustment, the application significantly reduces refresh delay and screen flicker, prolongs the service life of the equipment, optimizes system power consumption, and improves the user's playing experience.

The invention discloses a laser bar center extraction method, which comprises the following steps of: 1) training a segmentation module so that the segmentation module can segment a laser bar in a to-be-measured image, and outputting a Mask binary image; 2) inputting a to-be-tested image into a segmentation module, outputting a corresponding Mask binary image, screening foreground connected domains, and obtaining a reasoning Mask binary image; 3) performing morphological processing, extracting a connected domain, and obtaining a minimum bounding rectangle as an ROI region; 4) respectively acquiring F1, F2 and F3 by utilizing the ROI of the image to be detected, and then judging whether the ROI is a good area or a non-good area; and 5) for a good area, directly utilizing the ROI area corresponding to the image to be measured to perform light stripe center extraction, and for a non-good area, utilizing the ROI area corresponding to the reasoning Mask binary image to perform light stripe center extraction, and acquiring coordinates of a laser stripe central point. According to the method, the precision can be ensured, external interference can be effectively reduced, and the robustness is relatively high.

This application discloses a method and apparatus for constructing a ciphertext spatial index based on hierarchical order-preserving encryption, relating to the field of ciphertext spatial index construction. The method includes: embedding a security policy into the nodes of an R+ tree index to obtain an AR+ tree index; generating multi-level keys based on the AR+ tree index; using the multi-level keys to perform hierarchical order-preserving encryption on the plaintext index data, mapping the plaintext index data to ciphertext intervals; parsing the query statement to obtain a query rectangle and user access permissions; performing hierarchical order-preserving encryption on the query rectangle based on the AR+ tree index and multi-level keys, and finding the intersection with the minimum bounding rectangle of each layer's nodes; verifying user access permissions and filtering out all data IDs that meet the conditions; determining the original data ciphertext based on the filtered data IDs; and decrypting the original data ciphertext using the encryption algorithm used when encrypting the original data to obtain the plaintext data. This application enables fast retrieval and querying of spatial indexes in ciphertext mode.

The invention belongs to the technical field of aquaculture intelligent detection, and discloses a trachinotus ovatus weight prediction method. An original image of the trachinotus ovatus is obtained through target design and image acquisition, and accurate segmentation of a trachinotus ovatus body is realized by adjusting a YOLOv11 model. A Shii-Tomasi corner detection algorithm is adopted to extract center coordinates of a target, a perspective transformation technology is utilized to correct an image, and a proportional relation between a pixel size and an actual physical size is established. And inputting the corrected fish body image into the adjusted YOLOv11 model, performing segmentation to obtain a fish body contour coordinate point set, measuring the length and the width of the fish body through a minimum bounding rectangle method, and calculating key parameters such as the perimeter and the area of the fish body contour. Based on the obtained size parameters of the trachinotus ovatus body, a regression model between the size parameters and the weight is established, the adjusted R2 serves as an optimization index, nonlinear fitting and iterative parameter solving are conducted through 1stOpt software, a quality prediction model is established, and non-contact prediction of the trachinotus ovatus weight is achieved.

This invention discloses a machine vision-based method for measuring the trajectory of an electromagnetic needle selector. The method includes: acquiring a continuous image sequence of the needle selector during operation using a high-speed industrial camera; adaptively cropping the Region of Interest (ROI) using sparse optical flow fusion and image differencing; performing Otsu thresholding, connected component extraction, minimum bounding rectangle fitting, and gray-level centroid calculation on each needle selector region within the ROI to extract feature points of multiple needle selectors; constructing an inter-frame feature matching and trajectory reconstruction algorithm to continuously identify and sort the temporal trajectory of each needle selector; and finally outputting a complete and smooth multi-target motion trajectory. Compared to traditional single-point measurement methods, this method has advantages such as non-contact operation, high concurrency, and high precision, and is suitable for applications such as electromagnetic needle selector status assessment, fault detection, and performance analysis.

The invention provides a two-dimensional map annotation collaborative editing method based on geometric perception, which constructs a time and space information fusion architecture of map annotation by introducing a geometric vector clock and a minimum boundary rectangle. According to the method, by means of an operation merging layering mechanism, the merging efficiency of visual node operation in a large-scale node scene is improved; and semantic loss of translation operation is reduced through combination of topology anomaly detection and spatio-temporal joint operation, automatic error correction of most topology errors is realized, and the precision of collaborative editing of the two-dimensional map is improved.

Systems and methods of the inventive subject matter are directed to artificial intelligence systems that are configured to receive an uploaded file from a user, where that upload contains images of one or more documents. Documents can be, e.g., receipts, identification cards, and so on. Once received, the system converts the image to a tensor to facilitate identifying mask images. The AI system then converts any identified mask images to grayscale before converting the image to black and white. White spaces are identified, and contours are identified that surround the white spaces. Next, white spaces with areas below a threshold size are discarded and white spaces with areas above that threshold have their contours stored. The AI system finds a minimum bounding rectangle for each contour and then crops the image around each white space accordingly. In this way, documents can be found within an image file and segmented to later processing.

The present disclosure provides an image processing method and an image processing apparatus. The image processing method including: performing line detection on a boundary of an object in a scene image to obtain a plurality of candidate lines; taking one of the plurality of the candidate lines, which has the largest number of pixels overlapping with the boundary, as a first reference line; generating a minimum bounding rectangle of the object in the scene image; generating a transformed area, wherein each of four vertexes of the minimum bounding rectangle is on one of four sidelines of the transformed area; transforming a preset image into the transformed area to generate a transformed image; and overlaying the object with the transformed image to update the scene image.

The invention relates to the technical field of surveying and mapping geographic information, and discloses an error continuous surface detection method and system based on a geographic region, and the method comprises the steps: obtaining a plurality of interest surface sets of the same category in a target geographic region; obtaining a minimum bounding rectangle of all interest surfaces in the interest surface set; comparing the distance from the midpoint of the external rectangle to the angular point with the distance from the midpoint of the external rectangle to the original point, performing initial judgment on the error continuous surfaces of the external rectangle, and extracting all the error continuous surfaces to construct an initial error continuous surface set; according to the position relation between the external rectangles in the initial error continuous surface set, secondary judgment of the error continuous surfaces is carried out, non-error continuous surfaces in the secondary judgment are deleted, and updating of the error continuous surface set is completed. According to the method, the algorithm time complexity is reduced, and the requirement of large-scale data set rapid detection can be met.

The present application relates to the technical field of 3D printing, and more particularly to a method and a device for placing a 3D model, a computer-readable storage medium, and a 3D printer. The method includes: performing a dimension reduction processing to a first 3D model and a second 3D model, respectively, to obtain a first plane graphics corresponding to the first 3D model and a second plane graphics corresponding to the second 3D model; determining a minimum bounding rectangle of the first plane graphics; determining a convex hull of the second plane graphics, and determining an insertion point in the convex hull; and performing a successive insertion attempt to the minimum bounding rectangle at the insertion point, and determining a final placement position.

This invention discloses a non-destructive testing method for early damage in apples based on time-varying reflectance characteristics. The method utilizes a hyperspectral imaging system to continuously acquire hyperspectral images of sample apples. The average spectral reflectance of each pixel in the characteristic band is extracted as a feature value based on the hyperspectral image. The relationship between the feature value and the sampling time is fitted to obtain a fitting curve. Then, the slope and range K of the curve are obtained by differentiating the fitting curve. R , range K R After the distributed data is normalized and converted into a grayscale image, the grayscale image is segmented, and finally, the damage is accurately segmented and located using the minimum bounding rectangle. This invention utilizes hyperspectral image processing technology to achieve non-destructive detection of early-stage damage in apples, exhibiting good accuracy and practicality.

The invention provides a GeoHash code determination method and apparatus, an electronic device and a storage medium. The method comprises the steps of firstly determining a minimum enclosing rectangle of a to-be-identified region; then determining GeoHash codes corresponding to vertex grids where any three vertexes of the minimum enclosing rectangle are located; then, on the basis of the GeoHash codes of the three vertex grids, a preset character table is looked up for multiple times, so that the GeoHash codes of all the grids in the minimum bounding rectangle are determined; and finally, from the GeoHash codes of all the grids, screening out the GeoHash code of each target grid which is overlapped with the region to be identified in position. In the invention, the preset character table comprises 32 characters in the Base32 coding table, and the positions of the 32 characters in the preset character table are determined based on the coding principle of GeoHash coding, so that the GeoHash codes of all grids in the minimum enclosing rectangle can be determined by looking up the table, and compared with multiple coding conversion in the prior art, the coding efficiency is improved, and the coding efficiency is improved. By adopting a table look-up mode, the calculation amount is reduced, and the calculation rate is improved.