8results about How to "Improve matching speed" patented technology

The invention provides a shape-based template matching method, and belongs to the technical field of machine vision, and the method comprises the steps: obtaining a plurality of template images with different scales and angles; respectively calculating the gradient, the feature vector and the feature point at each pixel point on each template image; for a test image, calculating feature vectors and feature points of the test image, performing gradient direction expansion on each feature point to obtain a gradient direction quantized value, and enabling the gradient direction quantized value to correspond to a unique binary character string; a plurality of lookup tables are created, the index number of each lookup table corresponds to each binary character string, and the index value corresponds to the cosine value of the feature point and the feature vector corresponding to the binary character string; extracting template images and feature information of the template images, performing sliding window matching on the template images on the test images in the horizontal and vertical directions, acquiring overall similarity, and judging whether the test images are successfully matched with the corresponding template images or not; according to the invention, the matching speed and accuracy can be effectively improved.

The application discloses an automatic matching embroidery thread color embroidery method for embroidery plate making, and belongs to the technical field of embroidery embroidery, and has the technical scheme as follows: S1, a numbering database is established, corresponding embroidery thread numbers are set according to the RGB values of embroidery thread colors, the numbering database is adapted to plate making software, and the numbering database is stored on a tablet computer of an embroidery machine; S2, plate making software generates embroidery plate making with embroidery thread numbers through the numbering database, and the embroidery plate making is input to the tablet computer of the embroidery machine; and S3, the embroidery plate making is read on the tablet computer of the embroidery machine, the embroidery thread numbers of the embroidery threads placed on a thread drum placing rack of the embroidery machine are identified, the embroidery threads with colors corresponding to the embroidery thread numbers in the embroidery plate making are selected, and the embroidery threads are controlled to perform embroidery. The application can improve the matching accuracy of the embroidery threads in embroidery machine embroidery processing, and ensure the matching speed of the embroidery threads.

The application provides a power grid frequency modulation method and system, the method comprising: a power grid node generates frequency modulation demand information and synchronizes the frequency modulation demand information to a block chain; each EV aggregator node generates first frequency modulation resource information corresponding to the node, and if first target demand information is matched in each frequency modulation demand information according to the first frequency modulation resource information, first frequency modulation supply and demand information is generated and synchronized to the block chain; the power grid node performs device line safety checking on the first frequency modulation supply and demand information according to pre-established power grid device line information, and when the checking is passed, a first smart contract signed between the power grid node and the EV aggregator node corresponding to the first frequency modulation supply and demand information is generated, and the first smart contract is synchronized to the block chain; each EV aggregator node pushes charging and discharging task information to each electric vehicle corresponding to the node according to the first smart contract signed by the node, so that each electric vehicle accesses the power grid.

The application provides a multi-image array splicing method for large cement prefabricated components, and the splicing method comprises the following steps: step one: collecting original images of the cement prefabricated components, dividing the original images into regions, and adjusting the gray scale of each region to obtain preprocessed images; step two: searching for feature points between every two adjacent images in each row in the images, identifying and extracting key feature points in the images through a SIFT algorithm, and then matching the key feature points of the adjacent images through a KNN algorithm to determine the relative position relationship between the key feature points; step three: searching for feature points between every two adjacent images in each column and matching the feature points; and step four: calculating the boundary positions of each image in the splicing area, and then splicing. The application realizes high-precision splicing of the cement prefabricated components, can effectively improve the shape detection precision of subsequent cement components, and improves the product detection quality.

The invention belongs to the technical field of scene matching, and particularly relates to a rapid scene matching method for a large-range search area, which greatly improves the scene matching speed during large-range search and solves the problem of high time consumption in initial positioning of current scene matching. According to the method, a four-dimensional descriptor is firstly designed, so that the robustness of a back-end matching strategy can be greatly improved; furthermore, on the basis of the multi-dimensional reference descriptor and the multi-dimensional real-time descriptor, a convolution coarse matching and fine matching strategy is designed, firstly, the multi-dimensional reference descriptor is segmented to perform software acceleration, coarse matching is performed on the obtained nine regions by using convolution, and fine matching is performed on the obtained nine regions; cutting an image with the same size as the real-time image on the original reference image according to the matching position for accurate matching, and finally designing a matching judgment rule to judge a matching result. According to the method, a mode of combining segmentation rough matching and fine matching is adopted for a large-range search region, so that the matching speed of the large-range region is greatly improved.

The application discloses a virtual power plant user sensitive data identification method and device based on graph learning, and the method comprises the following steps: obtaining to-be-identified user data; generating a to-be-identified graph network according to the relationship of keywords in the to-be-identified user data; inputting the to-be-identified graph network into a pre-trained graph convolutional neural network model to obtain a minimum connected dominating set corresponding to the to-be-identified graph network; generating a simplified graph of the to-be-identified graph network based on the minimum connected dominating set corresponding to the to-be-identified graph network; and performing matching degree calculation on the simplified graph of the to-be-identified graph network and a simplified graph corresponding to standard sensitive level data to obtain a sensitive identification result of the to-be-identified user data. Through the implementation of the application, the minimum connected dominating set is generated by using the graph learning method, the complexity of subsequent graph matching is reduced, the matching speed is improved, and the application has higher efficiency compared with a traditional sensitive identification method.

The application relates to the field of FPGA debugging technology and discloses an FPGA signal observation method, system, device, equipment and storage medium, wherein the method comprises the following steps: setting a unique identifier for a to-be-observed FPGA function module where a target observation signal is located, and setting the same identifier in an FPGA top-level module; constructing a signal transmission link between the function module and the top-level module based on the identifier, so that the target observation signal is transmitted to the top-level module; and transmitting the signal to a debugging interface through the top-level module to complete online observation. The method solves the problems that the signals need to be repeatedly and manually connected and the observation target cannot be dynamically switched in the prior art through identifier matching and link construction, and the debugging efficiency is significantly improved.

This invention discloses a robot relocalization method, apparatus, and robot. In the method, laser point cloud data and image data acquired by the robot at its current position are received; keyframe information corresponding to the image data is determined according to a visual dictionary; physical location information corresponding to the keyframe information is obtained from a visual map; feature point information of the image data is matched with feature point information corresponding to the keyframe information; and calculation is performed by combining the physical location information of the feature points in the visual map and the pixel location information of the feature points in the image data. After obtaining the robot's first pose data, a predetermined area is set based on the first pose data, and iterative matching calculations are performed within the predetermined area using the laser map and laser point cloud data to obtain the robot's second pose data. By using the above scheme, the iteration range of laser matching can be reduced by utilizing the initial pose data, thus accelerating the matching speed and quickly achieving robot relocalization.