326results about How to "Improve registration efficiency" patented technology

The invention discloses a boundary feature point registering method for point cloud splicing in a three-dimensional scanning system. The method comprises the following steps that (1) a three-dimensional laser scanner acquires space sampling points on the surfaces of a real object in different view angles; (2) a boundary detecting method of a point cloud gravity center distance feature is used for extracting point cloud boundary feature points in different viewing angles; (3) an improved iterative closest point (ICP) algorithm is used for registering point cloud according to the extracted point cloud boundary feature points; (4) the registering precision is evaluated according to a registering error standard, and whether a registering result meets a registering request or not is verified. According to the boundary feature point registering method for point cloud splicing in the three-dimensional scanning system, boundary feature point extraction is conducted on the point cloud to be registered, the defect that all points in point cloud data need to be traversed to search for the corresponding points in a traditional ICP algorithm is overcome, on the basis that the registering precision is guaranteed, the complexity of the algorithm is effectively lowered, and meanwhile the efficiency of point cloud registering is obviously improved.

The invention provides an automatic registration method of an airborne laser point cloud and an aerial image. The automatic registration method comprises the following steps of: extracting a building outline from the point cloud without interpolation for the laser point cloud; obtaining building angular characteristics as a registration element through outline regularization; automatically matching the point cloud with the image according to the homonymic angular characteristics with the aid of an approximate exterior orientation element of the aerial image; and utilizing bundle block adjustment and a cyclic iterative policy so as to realize overall optimal registration of aerial image and point cloud data. The registration method provided by the invention has the following advantages that: the building outline is directly extracted from the laser point cloud without interpolation for the laser point cloud so as to obtain the building angular characteristics as the registration element, which prevents interpolation errors and improves the registration accuracy; and the exterior orientation element of the image is solved by virtue of bundle block adjustment, and meanwhile overall optimal registration between the aerial image and the airborne laser point cloud is realized by adopting the cyclic iterative registration policy.

The present invention uses geographic location co-ordinate as centre, taking single frame or continue photo in 360-degree range, to proceed indifferent split-join to single frame to constitute a new panoramic picture. The photo taking adopts pre-taking and formal taking two stages for realizing panoramic imagery. Said pre-taking obtains imaging range and other parameters. In formal photo taking, the video camera obtains the first picture of continue single picture, and intercepting picture minimal final leg data field, continue judging second picture exposure value, adjusting required amount of exposure, obtaining second picture and intercepting minimal start picture edge data field and tail end picture edge data field, utilizing picture adjacent matching algorithm to proceed optimum matching, to form new image data, then to make optical lens accuracy rotation to precalculated position according to Kn value, continue taking one picture until completing panoramic imagery, then ending.

The invention discloses a fingerprint identification system and a fingerprint processing method and device of the fingerprint identification system, and belongs to the technical field of fingerprint identification. The method includes the process that under a registration mode, when fingers of a user pass through a designated area in a sensor scanning area in a sliding mode, a plurality of pictures are obtained by scanning the designated area; according to the same characteristic value of the pictures, the pictures are spliced to form fingerprint images; the fingerprint images or the characteristic value of the fingerprint images is stored in a registration template. Due to the adoption of the fingerprint identification system and the fingerprint processing method and device of the fingerprint identification system, the scanning time can be shortened, operation is easy, and the fingerprint registration efficiency is improved.

The invention provides an overall registering method for carrying out automatic global optimization on registering initial values of existing multi-view laser point clouds. The overall registering method is characterized in that firstly, a multi-view laser point cloud registering global optimization overall adjustment model is established and detailedly deduced, and by estimating the density of the point cloud, all two-view clouds with a certain overlapping degree are automatically detected; then a K-D tree is used for searching for approximate homonymy points in the two-view clouds with the certain overlapping degree, the approximate homonymy points are used as observed values to be substituted into the global optimization overall adjustment model, respective optimal rotation and translation transformation parameters of the multi-view laser point clouds are obtained at the same time through iterative adjustment calculation, and therefore overall precise registering of the multi-view three-dimensional laser point clouds is achieved. The method lays emphasis on improvement of the overall registering precision of the multi-view three-dimensional laser point clouds, disordered and messy multi-view three-dimensional laser scanning point clouds can be treated at the same time, registering experiments are carried out through actual multi-view three-dimensional laser point cloud data, and results prove that on the basis of guaranteeing registering efficiency, the overall registering precision is improved effectively.

The invention discloses a method and a system for registration or login via a third-party website, and belongs to the field of the internet. The method includes that a verification link for using the third-party website for verifying account numbers is set on a registration webpage of a source website, a user jumps to the third-party website after triggering the verification link, and logins the third-party website by using a third-party account number, the account number is verified, and authority for reading personal information is granted to the user; the source website acquires the authorized personal information of the user from the third-party website via a port provided by the third-party website; then the source website fills the personal information in corresponding registration information of the registration webpage and stores the personal information, and registration is completed; or the source website judges whether the user is a registered user of the source website or not according to the personal information, a session key is generated if the user is the registered user, a login status is displayed, and login is completed. The method and the system have the advantages that when the user is registered via the third-party website, the amount of information required to be inputted by the user in a website registration process is reduced, and the registration efficiency is improved.

The invention provides a mobile robot V-SLAM method of a three-stage point cloud registration method. The V-SLAM method comprises the following steps: S1, acquiring RGB information and Depth information of the surrounding environment; 2, generate three-dimensional point cloud data; 3, extract that ORB image feature from the obtained RGB image, and match the feature of the point set elements by adopting FLANN; S4, screening the point pairs of the RGB map through the RANSAC sampling strategy so as to obtain the interior points to complete the preprocessing stage; S5, completing the initial registration stage of the point cloud by adopting the corresponding point double distance threshold method based on the rigid body transformation consistency; S6, a dynamic iterative angle factor ICP precision registration method is introduced to complete the precision registration phase when the initial posture is good; S7, the key frame selection mechanism of sliding window and random sampling is introduced in the back end, and the g2o algorithm is used to optimize the robot posture trajectory, so as to realize the reconstruction of three-dimensional point cloud environment The invention can improve the registration accuracy and registration efficiency of the point cloud map in the environmental three-dimensional reconstruction.

The invention discloses a point cloud registration method for three-dimensional reconstruction. The point cloud registration method comprises the steps of S101, acquiring three-dimensional point clouds at multiple view angles, and adopting three-dimensional point clouds at two view angles as a source point set and a target point set respectively; S102, constructing a KD-tree; S103, figuring out the normal vectors of all points in the source point set; S104, calculating an average value of the included angles of the normal vectors; S105, classifying points in the source point set and setting amaximum resolution, wherein the initial resolution is 1; S106, calculating the sampling proportion of each stage in the source point set at the current resolution and extracting a sampling point; S107, figuring out the matching point of the sampling point in the target point set on the basis of the matching degree in the method; S108, calculating a rotation matrix and a translation matrix by usinga quaternion method; S109, converting the source point set to obtain a new source point set; S110, repeating the steps from S107 to S109 until a objective function is the minimum; S111, if a preset condition is met, ending the process; otherwise, adding 1 to the current resolution, and returning to the step S106. According to the invention, low-resolution matching points are used for rapidly completing the registration. The high-resolution matching points are used for improving the precision. Meanwhile, matching points are searched for through the matching degree. The registration speed and the registration precision of large-scale point clouds are greatly improved.

The invention provides a registration and login method and system for a third party application. The method includes the steps that after the third party application starts to be registered, biological feature information of a registered user is acquired and authenticated, and if authentication passes, a registration instruction is sent to a server; after the server receives the registration instruction, identification of the third party application and corresponding user information of the third party application are acquired, a user account and a token value which correspond to the third party application are generated, the mapping relation among the identification of the third party application, the user account and the token value is stored, and the token value is sent to the third party application; after the third party application receives and stores the token value, it is confirmed that registration is successful; when the third party application receives a login trigger instruction of a login user, biological feature information of the login user is acquired and authenticated, and if authentication passes, the identification and the token value of the third party application are sent to the server; the server finds out the user account corresponding to the third party application through the identification and the token value, the user account is sent to the third party application, and then the user logs in the third party application. Registration efficiency is improved through the method and system.

The invention relates to a three-dimensional mapping method of a lidar based on semantic point cloud registration, which comprises the following steps of: (1) acquiring point cloud data of an object to be scanned; (2) extracting semantic feature points from the collected lidar point cloud data; (3) According to the triangle similarity principle, registering the feature points based on semantics; (4) Constructing 3D point cloud image by using registration point cloud pairs. The feature points extracted by the invention have poles, three categories of intersections and vertices, the probabilityof mismatch decreases during registration, Reduced Matching Complexity, improve real-time performance of map structure, The accuracy of calculating the moving posture of the laser radar is improved byusing the registration point cloud, the position information of the point cloud is corrected by using the moving posture, and the map constructed by projecting to the world coordinate system is moreaccurate. The invention only utilizes the scanning data of the laser radar to complete online drawing of the high-quality three-dimensional point cloud image, and has the advantage of error caused byaccurate mismatch.

The invention discloses a network selection method and a device based on a shared network. The network selection method based on a shared network comprises: when a mobile station (MS) fails to register to a first public land mobile network (PLMN), searching whether a first PLMN assembly exists in a first selection level belonging to the first PLMN, wherein, the first PLMN assembly comprises one or a plurality of PLMNs positioned in the same shared cell with the first PLMN; if the first PLMN assembly is found, selecting a PLMN from the first PLMN assembly for registering. Thus, when PLMN is selected, the shared information can be used, other PLMNs belonging to the same shared cell are selected preferably without re-lingering, so that the network selection process is simplified, and register efficiency can be improved.

The invention provides novel dye-labeled ribonucleotide analogs and methods for synthesizing those analogs. The compounds of the invention are especially useful for DNA sequencing by the polymerase chain reaction.

The invention provides a point cloud registration method for point neighborhood scale difference description. The method comprises the following steps: performing least square surface fitting on discrete points in a source point cloud and a target point cloud to obtain a local surface, solving a shape index SI of the surface, i.e., the shape index of the discrete points, and selecting a point of which the shape index is maximum or minimum in a neighborhood and meets a threshold value as a key point of the point cloud; carrying out feature descriptor construction, and calculating feature normalization vector difference values and normal vector included angle difference values of the key points under different neighborhood radiuses to be combined into a point domain scale difference descriptor; finding out corresponding points according to the similarity degree of the feature descriptors, and filtering out error point pairs and estimating the corresponding relation through double screening and an optimal searching algorithm based on the global distance. The key points obtained by the method have good representativeness and distinctiveness, the effect on the condition that the point cloud distribution density difference is large or noise points exist is obvious, the calculation is simple, the point cloud registration speed and precision are improved, and the method has good anti-interference capability.

The invention relates to a multimodal medical image registration and visualization method. Based on FLTK, VTK, and IRTK technologies, the method provides a friendly operation interface and visualization functions, simplifies the complex algorithm parameter configuration process, facilitates registration operations, and realizes multi-modal medical image registration; provides image denoising preprocessing to Improve image quality and reduce the impact of noise on registration accuracy; in the case of large coordinate position differences between the target image and the source image, a point set registration method is provided to complete the coarse registration of the coordinate position, which provides a basis for subsequent rigid, affine and nonlinear registration. Accurate implementation for initialization; support cascade working mode of multiple registration methods to improve registration efficiency; use multi-threaded programming technology to realize real-time dynamic display of the registration process, which is convenient for understanding and monitoring the registration process; registration The result is automatically output and saved; using the transformation matrix of the registration result and adding a smooth limit item, the function of diffeomorphism transformation and fast segmentation can be realized.

The invention provides a video splicing system and method for a binocular robot, and belongs to the technical field of robot visual images. The system comprises a robot video frame acquisition module,an image splicing system processing module, a wireless transmission module and a terminal display module, wherein the image splicing system processing module comprises an overlapping area positioningmodule, a feature point parallel directional registration module, an image color correction module, an image deformation module, a dynamic planning suture line module and an image smooth fusion module; the system can carry out system, video frame coincidence area positioning, feature point directional registration, image color correction, image deformation, dynamic suture line planning and imagesmooth fusion processing on an image frame collected by a robot in a binocular mode to obtain high-quality spliced video; the visual field of the robot is greatly expanded, purposes of movement, positioning, identification and the like can be better completed, and the image frame splicing speed and the splicing efficiency are improved.

Disclosed a multi-station scanning global point cloud registration method based on graph optimization, including acquiring multi-station original three-dimensional point cloud data; based on initial registration of targets, completing initial registration of point cloud data at adjacent stations by virtue of the target at each angle of view; calculating a point cloud overlap area at adjacent angles of view, and calculating areas of overlap regions of adjacent point cloud by a gridded sampling method; constructing a fine registration graph structure, and constructing a fine registration graph by taking point cloud data of each station as a node of the graph and taking an overlap area of the point cloud data of adjacent stations as a side of adjacent nodes of the graph structure; and based on loop closure fine registration based on graph optimization, gradually completing point cloud fine registration of the whole aircraft according to a specific closure sequence.

Disclosed are an access session controller, an IP multimedia subsystem and registration and session establishment methods thereof, where the access session controller includes a message reception module, a service trigger configuration module, a session control module and a message transmission module. The IP multimedia subsystem includes the access session controller and a network-wide home subscriber server system. The registration method includes: initiating, by the access session controller, an authentication information request to the network-wide home subscriber server system. The session establishment method includes: directly process, by the access session controller, the request message initiated from a user to establish a session. The foregoing solutions can simplify the signaling processing flow and reduce the network complexity.

This invention relates to network system membership register method, which comprises the following steps: network system visitor pre-edits one account file with register information with name and load codes; visitor sends register require and extracting account register file; network system analyzes above account register file for certain data type; if account register file meets and then extracting its information automatic register list and validating account name legality; if it is legal, then visitor validities register; if the account file is wrong then indicating visitor for repairing till fulfilling register.

The invention provides a point cloud registration method based a neighbourhood rotary volume and belongs to the technical field of three-dimensional images. The point cloud registration method based the neighbourhood rotary volume aims at solving the technical problems of low registration speed and poor anti-noise performance exist in an existing point cloud registration method. The method comprises the steps of loading and separately calculating a source key point set and a target key point set of source point cloud and target point cloud of which visual angles are adjacent; for each key point, using n times of surface resolution as a neighbourhood, calculating out the rotary volume of neighborhood inner points and using the rotary volume as a description vector, and obtaining a source key point description vector set and a target key point description vector set; according to a calculation result of the last step, calculating a rotary translation matrix; using the rotary translation matrix to rotate and translate the source key point description vector set, and obtaining a middle key point description vector set; according to a final rotary translation matrix, converting the source point cloud to a coordinate system in which the target cloud is located, and obtaining middle point cloud; using an ICP algorithm to precisely registrate the middle point cloud and the target point cloud.

The invention discloses an electric power line inspection LiDAR data automatic registration method based on tower characteristic points, and the method comprises the following steps: S1, extracting two stages of tower point cloud data, and extracting characteristic point clouds at corners of a tower through employing a random sampling consistency algorithm; S2, based on a principal component analysis method and a direction cosine rule, determining a corresponding relation between point cloud centroid coordinate systems of the two stages of towers, and solving an initial transformation matrix;S3, on the basis of initial transformation, adopting kd-based (kd-based) transformation; and carrying out fine matching on the tower characteristic points by using an iterative nearest point algorithmof tree optimized matching point search, obtaining a final transformation matrix, and carrying out spatial coordinate system conversion on the initial point cloud based on the target point cloud. According to the invention, under the condition that the electric power line inspection LiDAR data has data loss and lack of ground feature characteristics; The method comprises the following steps: extracting a tower area, extracting tower characteristic point cloud by utilizing a Ransac straight line fitting algorithm, calculating a transformation matrix by combining PCA coarse registration and ICPfine registration, and finally realizing transformation from an initial point cloud coordinate system to a target point cloud coordinate system.