87 results about "Cut" patented technology

Methods, and program storage devices, for performing model-based optical proximity correction by providing a region of interest (ROI) having an interaction distance and locating at least one polygon within the ROI. A cut line of sample points representative of a set of vertices, or plurality of cut lines, are generated within the ROI across at least one lateral edge of the polygon(s). An angular position, and first and second portions of the cut line residing on opposing sides of an intersection between the cut line and the lateral edge of the polygon are determined, followed by generating a new ROI by extending the original ROI beyond its interaction distance based on such angular position, and first and second portions of the cut line. In this manner, a variety of new ROIs may be generated, in a variety of different directions, to ultimately correct for optical proximity.

The invention provides a high energy beam processing method with an ejection point as a control target. The high energy beam processing method with the ejection point as the control target comprises the following steps of (1) vectorizing cut graphs and dividing the cut graphs into line segment units; (2) designing a pitching-in line and a pitching-out line; (3) designing a planned route of the ejection point moving on the lower surface of a processed workpiece; (4) designing a cutting scheme; (5) calculating multi-dimensional space tracks of the ejection point moving on the lower surface of the processed workpiece; and (6) processing the workpiece according to a multi-dimensional space of the ejection point. The high energy beam processing method with the ejection point as the control target selects an optimized strategy (the cutting scheme) according to the cutting route tracks of the ejection point moving on the lower surface of the processed workpiece and can effectively eliminate shape errors caused by different flow beam expression forms of the ejection point and an incidence point. Compared with the prior art, the high energy beam processing method with the ejection point as the control target adopts a cutting head backward inclining and quick cutting method to replace an original cutting-speed slowdown method, improves the cutting efficiency and avoids the shape errors caused by slowdown in the existing method.

The invention discloses a repeated image recognition method and device, equipment and a medium. The method comprises the following steps of: intercepting a cut image from the to-be-identified image; converting the cut image to obtain a grayscale image, a hue saturation image and a color video image; obtaining all normalized values of a local phase quantization characteristic histogram of the grayscale image through a local phase quantization method; obtaining all standard values of a first adjacent local binary pattern feature histogram of the hue saturation image through an adjacent local binary pattern method; and meanwhile, obtaining all standard values of a second adjacent local binary pattern feature histogram of the color video image through an adjacent local binary pattern method, performing sorting according to a mantissa zero padding method to obtain a matrix graph, inputting the matrix graph into a deep convolutional neural network model, and extracting texture signal frequency statistical features to obtain an identification result. According to the invention, whether the certificate or the image is copied or not can be quickly, effectively and conveniently recognized, and the recognition accuracy is improved.

The invention discloses an image foreground extraction method based on a graph cut model. The method is used for accurate segmentation of a human eye area in an image and belongs to the field of image recognition based on machine vision, and the method is suitable for automatic detection driving fatigue state of a driver. According to the invention, the problem that a present detection system cannot accurately recognize human eye opening and closing states in a complex driving environment is solved. According to the method, a graph cut model is firstly established on an original image; then, based on a segmentation target, an energy function of the graph cut model is constructed; and finally, the function is solved by a max-flow min-cut method so as to obtain the final segmentation result. By the segmentation algorithm, a binary image with a white background and a black eye area is constructed, thus providing stable feature description for follow-up human eye state recognition. It proves validity of the extraction method through experiments. The method provided by the invention can be widely applied in automatic detection of fatigue state of drivers of trains, interurban coaches and ''three danger'' vehicles.

The invention provides a water supply pipe network valve layout design and optimization method which comprises the following steps: S1, abstracting valves and pipe points in a pipe network into points, abstracting pipe sections into edges, and constructing an NE graph; S2, identifying a turn-off unit by using the NE graph; S3, constructing an SV graph; S4, utilizing the SV graph to calculate the weighted deficient supply quantity; and S5, solving an optimal valve layout scheme set based on NSGA-II. The water supply pipe network valve layout design and optimization method has the beneficial effects that under certain economic cost, the NSGA-II algorithm is used for optimizing the valve layout, and the water consumption which cannot be supplied after the pipe network has an accident is reduced to the minimum, so that the reliability of the pipe network is improved; the reconstruction of the SV graph can be realized only by performing local modification on the SV graph, and the time complexity of the algorithm is effectively reduced by using the cut points in the graph theory when the weighting lacking supply is calculated; and the water supply pipe network valve layout design and optimization method can be applied to the design of new pipe network valve layout and the transformation process of an existing pipe network, so that engineering cost can be controlled easily, and valvescan be scientifically and reasonably arranged.

The invention relates to the technical field of artificial intelligence, in particular to a photovoltaic cell panel solder strip offset detection method and device based on artificial intelligence. The method comprises the steps: acquiring a front view of the surface of a photovoltaic cell panel, and cutting the front view to obtain and number a cut graph of each solder strip; carrying out edge detection on the cut image of the solder strip, and sampling an edge binary image to obtain coordinate information of sampling points; performing linear fitting on the sampling points to obtain a linearequation; carrying out polynomial fitting on the sampling points, setting an error function to evaluate and optimize the coefficient of the polynomial, establishing a fitting degree evaluation indexto determine the highest power of the best fitting degree, and obtaining a polynomial equation reflecting the actual trend of the edge of the solder strip; and determining whether the solder strip deviates or not through difference operation of the polynomial equation and the linear equation to obtain position information of the deviated solder strip. According to the method, the problems that thecurrent solder strip offset depends on manual detection, the efficiency is low and the assembly power is attenuated can be improved.

The invention discloses a batch cutting placement graph generation method and device. The method comprises the following steps of responding to a data import command of a main menu in an EXCEL cuttingdetail table, automatically importing part cutting information of N parts into the table from a process flow card, responding to a data import command in a menu corresponding to CAD software, obtaining the cutting information of the N parts from the table, drawing N blank block diagrams, filling the N blank block diagrams with part cutting information, receiving N cutting graphs input by a user,responding to operation of the user for frame selection of the cutting graphs, judging the type of the cutting graphs, and crushing a face domain and converting the face domain into a closed multi-segment line contour if the type of the cutting graphs is the face domain; judging the contour type; according to materials and the plate thickness of the cut parts, automatically searching for a corresponding placement allowance from a cutting allowance comparison table in the table, placing an inner contour inwards, and placing an outer contour outwards; and generating cutting placement graphs. Thecutting placement working efficiency and correctness are improved.

The invention discloses a distributed SPARQL query optimization method based on minimum attribute cut, which belongs to the field of distributed systems, and comprises the following steps: (1) reading an original RDF data graph, and storing an edge attribute set L; (2) calculating a weak connected component and a corresponding cost of each edge attribute; (3) selecting internal attributes as many as possible to obtain a coarsened graph of the data graph; (4) carrying out vertex division on the coarsened image, and carrying out anti-coarsening processing to obtain a final partition; (5) decomposing the SPARQL query into a group of sub-queries which can be independently executed; and (6) executing the decomposed sub-queries in each partition in parallel to obtain a matching result. According to the method, the query types which can be independently executed in the distributed RDF system are expanded, the connection among the partitions is reduced, the data communication time is shortened, and the query efficiency is improved.

When each pixel forming image data is classified into one of N labels (where N>2) which are ordered from 0 to N−1, a binary graph setting unit sets a binary graph where the i-th layer i is a boundary between the label i−1 and the label i of the N labels, a class to which a label equal to or higher than i is assigned corresponds to a virtual label 0, and a class to which a label equal to or smaller than i−1 is assigned corresponds to a virtual label 1, a layer-by-layer labeling unit performs a graph cut operation on the binary graph of each layer, and then a label determining unit determines which of the N labels each pixel belongs to based on the virtual labels assigned to all the binary graphs.

The invention discloses a layer exporting method and device, equipment and a storage medium, and belongs to the field of UI design. The method comprises the steps that a node tree of a visual draft file of a user interface is acquired, the node tree comprises visual element nodes, and the visual element nodes correspond to graph layers of visual elements forming the user interface; visual elementnodes which do not support code construction in the node tree are determined; the visual element nodes belonging to the same level in the visual element nodes which do not support code construction are combined to obtain combined visual element nodes; and exporting the graph layers corresponding to the merged visual element nodes as first cut graph layers. In the image cutting process, manual operation is not needed, and the cut image layer can be exported only by processing the node tree of the visual draft file through computer equipment. The problems that errors are prone to occurring and efficiency is low due to manual operation can be avoided, and the technical scheme of full-automatic exporting and image cutting is provided.