531results about How to "Realize automatic extraction" patented technology

The invention discloses an automatically-extracting power line method in random laser point cloud data. According to the automatically-extracting power line method, a ground point cloud is segmented and filtered through a point cloud of an elevation; on direction projection of the segmented point cloud, a straight line segment is detected and further back-projected to three-dimensional space so as to obtain a three-dimensional line segment; while the three-dimensional line segment serves as a clustering nuclear, a distance clustering method is used to obtain an accurate point cloud of the power line and generates a power line vector node based on the accurate point cloud of the power line; and a power line vector is outputted, so that automatic extraction of the power line is realized. The automatically-extracting power line method in the random laser point cloud data is efficient in extracting, and can automatically extract the power line.

The invention provides a road zebra crossing automatic extraction method based on vehicle-mounted laser scanning point cloud, and relates to public traffic road zebra crossings. According to the method, global positioning system data for recording vehicle positions and tracks in real time is used for extracting a plurality of cross sections from the vehicle-mounted laser scanning point cloud data, and the road and non-road classification is realized through detecting the elevation mutation of road shoulders of the roads in the scanning line data; then, the three-dimension road data is converted into an intensity characteristic image with space distribution characteristics, the laser scanning point normal distribution characteristics are utilized for dynamically cutting the road zebra crossings, the GPS (global positioning system) track data is used again for calculating the linear morphology closed operation direction and size, and the extraction of the road zebra crossings is realized. Through the cross section subdivision on the vehicle-mounted moving scanning data, and the three-dimension road surface data detection is converted into the detection of the elevation mutation of the road shoulders of the roads in the two-dimension profile for realizing the road and non-road classification. Compared with a method of directly processing mass three-dimension data, the method has the advantages that the calculation quantity is small, and the efficiency is high.

The invention provides a method for registering a remote sensing image based on a local contour covariance matrix, which combines a corner feature, a local split image and a local edge contour together as a local feature to implement an extraction of control points, has the local contour covariance matrix introduced into a registering processing, uses the local contour covariance matrix to implement an automatic extraction of a rotating and scaling factor, and combines a technology of self adaptive selection of a local window to reduce an effect of the twiddle and scaling factor on the registering processing so as to improve the robustness of the registering processing, thereby implementing an accurate registering between remote sensing images in a mode of large rotation and scaling without human participation.

The invention discloses a robot welding path autonomous planning method based on 3D point cloud data. The robot welding path autonomous planning method comprises the following steps of acquiring the original three-dimensional cloud data of a workpiece weld profile, and preprocessing the original three-dimensional cloud data; according to the workpiece weld characteristics, constructing ruler CAD models with the same characteristics, and converting characteristic surface information of ruler CAD models as three-dimensional point cloud data; performing local registration operation on the three-dimensional point cloud data of the ruler CAD models and the three-dimensional point cloud data generated after the workpiece weld profile is preprocessed; according to the local registration operation, performing continuous characteristic searching, thereby obtaining complete workpiece weld information; extracting weld position and posture information marked in the complete workpiece weld information; and processing the extracted weld position and posture information, and planning the robot welding path. The self-adaptability of robot welding can be improved, and the workload of scene teachingand off-line programming of operating staff can be remarkably reduced.

The invention discloses an intelligent heart sound diagnostic system and method based on in-depth learning and relates to the fields of bio-signal processing, pattern recognition, big data and in-depth learning. The method comprises the following steps: 1) acquiring heart sound audio data by a user through heart sound acquisition equipment or intelligent wearable equipment; 2) transmitting the data to a cloud server through a network, and storing and archiving the heart sound audio data; 3) segmenting the heart sound data on the cloud server by adopting a heart sound segmentation algorithm based on a logistic regression-hidden semi-Markov model, and performing automatic characteristic extraction and classification on the segmented heart sound data by using a one-dimensional convolutional neural network; 4) feeding diagnostic results to the user through a network and storing the results on a cloud so as to be provided for related institutions and designated hospitals as clinical historyreference of the user; and 5) expanding the heart sound data of the user confirmed by a professional doctor serving as training data into a heart sound database of a cloud server, so that the diagnostic capability of the heart sound diagnostic system is continuously improved.

The invention relates to a method and a system for identifying a form in a layout file and belongs to the technical field of mode identification in the field of computer information processing. The conventional mode identification technology cannot effectively identify and automatically extract the form of a layout. In the method and the system, firstly, independent characters of the layout are combined and organized into content blocks by utilizing automatic combination technology; and secondly, form identification and content combination are performed according to spatial positions, character information and typesetting information of the content blocks. Through the method and the system, the form can be rapidly identified at high efficiency, and the form content is accurately organized through the analysis of the position and the typesetting information of the content of the paper layout.

The invention discloses an improved image splicing key frame fast extraction method, and relates to the field of computer vision. The method eliminates the influence of image distortion through image preprocessing, detects feature points by using the SIFT, realizes the automatic extraction of key frames by taking a matching ratio of the feature points of adjacent frames as the similarity measure of images, splices the key frame images, greatly reduces the splicing time of the sequence images, screens initial matching pairs by using an improved RANSAC algorithm, calculates an accurate transformation matrix between the images to achieve image registration, and finally achieves seamless image splicing by using a weighted smoothing fusion method. The method has strong robustness, and the spliced images are natural and clear.

The invention discloses a video region-of-interest extraction method based on visual perception characteristics and encoding information, and relates to the field of video encoding. The video region-of-interest extraction method comprises the following steps of (1) extracting luminance information of a current encoding macro-block from a primary video stream, (2) identifying a space domain visual characteristic saliency region through an inter-frame prediction mode type of the current encoding macro-block, (3) using a mean motion vector, in the horizontal direction, of a previous encoding macro-block and a mean motion vector, in the perpendicular direction, of the previous encoding macro-block as dual dynamic thresholds, identifying a time domain visual characteristic saliency region according to the result of comparison among a motion vector, in the horizontal direction, of the current encoding macro-block, a motion vector, in the perpendicular direction, of the current encoding macro-block and the dual dynamic thresholds, and (4) defining a video interest priority through combination of the identification result of the space domain visual characteristic saliency region and the identification result of the time domain visual characteristic saliency region, and achieving automatic extraction of a region of interest of a video. According to the video region-of-interest extraction method, the important encoding basis can be provided for the video encoding technology based on the ROI.

The invention relates to a system and method to filter the wasted mails on internet. At present there is a lot of wasted mails, human use keywords to filter it, build black name list, and set regulation to prevent, but the result is unobvious, hard to maintain, high requirement for professional skill. The invention consists of hardware, software which is installed on hardware and supported network, the software includes Linux operating system, analyzing engine for wasted mails, extended black name list, internet library and management interface. The periphery supporting network includes complain device for wasted mails, analyzing system for wasted mails, which can work as transparent gateway before LAN or mail sever, take over MX interface to work before mail sever. The method includes the hardware connection, telnet management, management of wasted mails and anti-waste setting, and the operation is convenient, easy to maintain, high identifying rate, high stability, low misjudgment rate, and plug and play.

The invention discloses an atmospheric correction method for multispectral data of a remote sensing satellite. The method comprises the following steps of: (1) reading data, and converting the data into apparent radiance data and apparent reflectivity data; (2) calculating decision factors, i.e. a ratio vegetation index, a soil adjustable vegetation index and a normalization water body index in adecision tree method according to the apparent reflectivity data; (3) acquiring apparent reflectivity data in a dark target area according to the apparent reflectivity data, and calculating air path reflectivity; (4) determining the aerosol optical depth of each multispectral waveband according to the relation among the air path reflectivity, a Rayleigh reflectivity ratio and the aerosol optical depth, and determining the total optical depth of a position of 550 nanometers according to the aerosol optical depth and the Rayleigh scatting optical depth of each multispectral waveband; and (5) acquiring an inversion parameter from a lookup table according to the total optical depth of the position of 550 nanometers, and solving land surface reflectivity through a radiative transfer equation to finish atmospheric correction.