164 results about "Local matching" patented technology

Fingerprint recognition and matching systems and methods are described that utilize features at all three fingerprint friction ridge detail levels, i.e., Level 1, Level 2 and Level 3, extracted from 1000 ppi fingerprint scans. Level 3 features, including but not limited to pore and ridge contour characteristics, were automatically extracted using various filters (e.g., Gabor filters, edge detector filters, and / or the like) and transforms (e.g., wavelet transforms) and were locally matched using various algorithms (e.g., the iterative closest point (ICP) algorithm). Because Level 3 features carry significant discriminatory and complementary information, there was a relative reduction of 20% in the equal error rate (EER) of the matching system when Level 3 features were employed in combination with Level 1 and Level 2 features, which were also automatically extracted. This significant performance gain was consistently observed across various quality fingerprint images.

A portable communication apparatus for match-making with a plurality of remote communication apparatuses has memory means adapted to store match-making data, including local match-making data associated with the portable communication apparatus. A transceiver is adapted for wireless communication with a first remote communication apparatus, so as to transmit the local match-making data to the first remote communication apparatus, as well as to receive first remote match-making data associated with the first remote communication apparatus. A processing device is adapted to perform a correlation analysis between the local match-making data and the first remote match-making data and-in case a result of the correlation analysis indicates a match between the portable communication apparatus and the first remote communication apparatus-provide an alert to a user of the portable communication apparatus. The memory means is adapted to store the first remote match-making data, and the transceiver is adapted to transmit the first remote match-making data, in addition to the local match-making data, to a second remote communication apparatus.

Systems and methods are disclosed for customizing, distributing and processing audio fingerprint data. One or more items of audio content are processed to generate pre-recorded audio fingerprints After identifying one or more specific devices in accordance to panelist and / or household data from a central site, an activation message is communicated to the identified devices, together with the pre-recorded audio fingerprint in accordance with a predetermined schedule. After receiving the activation message, the portable device records the audio content, forms an audio fingerprint, and performs local matching to determine if a match exists. The matching result is then communicated back to the central site for further processing and analysis.

A system and a method are disclosed for sensitive document management. The system includes one or more agents, a behavior analysis engine, a local policy engine, and a local matching service. The method identifies whether a document is sensitive, identifies behaviors applied to the document, determines whether the document contains sensitive information and determines whether to allow the identified behavior to continue based on security policies.

The invention discloses a multiple time phase remote sensing image registration method based on an edge and spectral reflectivity curve. The multiple time phase remote sensing image registration method based on the edge and spectral reflectivity curve mainly solves the problems that stability is insufficient and accuracy is low when registration is conducted on two time phases of multiple spectral image sets with variation regions and whole luminance difference in the prior art. The multiple time phase remote sensing image registration method based on the edge and spectral reflectivity curve comprises the following steps: small wave high frequency coefficient matrixes are added and divided, the small wave high frequency coefficient matrixes are added simultaneously, the input two time phases of the multiple spectral image sets are preprocessed, and thus two time phases of strong edge images are acquired; registration parameters of edge alignment metric of the two time phases of the strong edge images are calculated to register the two time phases of image sets and acquire coarse registration image sets; the coarse registration image sets are converted into opposite object spectral reflectance image sets, small wave high frequency coefficients of time phases 1 of the object spectral reflectance image sets are reconstructed to acquire coarse registration edge images, and the coarse registration edge images conduct local matching on opposite object spectral reflectance images of the time phases 1 and time phases 2 to acquire a final registration image set. The multiple time phase remote sensing image registration method based on the edge and spectral reflectivity curve can be used for change detection, integrating and embedding.

Method and system for the detection of interval change in medical images. Three dimensional images, such as previous and current section images in CT scans, are obtained. An anatomic feature, such as the lungs, is used to select sections containing lung by a gray-level thresholding technique. The section correspondence between the current and previous scans is determined automatically. The initial registration of the corresponding sections in the two scans is achieved by a rotation correction and a cross-correlation technique. A more accurate registration between the corresponding current and previous section images is achieved by local matching. A nonlinear warping process which is also based on the cross-correlation technique is applied to the previous image to yield a warped image after the matching. The final subtracted section images were derived by subtracting of the previous section images from the corresponding current section images. Interval changes such as a change in tumor size and a newly developed pleural effusion are enhanced significantly.

The invention discloses a quick binocular stereo matching method based on superpixel segmentation. The method comprises the following steps that: (1) adopting a SLIC (Simple Linear Iterative Clustering) superpixel segmentation method to carry out regional division on an original reference diagram and a target diagram; (2) on the basis of a local matching algorithm of adaptive weighting, calcuating an original parallax spatial diagram; (3) carrying out regional parallax plane fitting based on a confidence point; (4) applying a clustering algorithm to combine adjacent regional parallax planes; and (5) on the basis of a superpixel region, constructing an energy cost function to carry out stereo matching. A stereo matching unit is the superpixel region combined on the basis of the edge information of an image, so that the algorithm is guaranteed to be suitable for a large no-texture region, a depth boundary can be accurately positioned, a matching cost better than the matching cost of a traditional stereo matching method is obtained and is combined with a parallax postprocessing method to effectively obtain a high-accuracy parallax diagram, and the method exhibits good instantaneity.

Provided is an apparatus and method for determining stereo disparity based on two-path dynamic programming and GGCP. The apparatus includes a pre-processing unit for analyzing texture distribution of an input image by using a Laplacian of Gaussian (LOG) filter and dividing the input image into a homogeneous region and a non-homogeneous region; a local matching unit for determining candidate disparities to be included in an each pixel of all pixels; a local post-processing unit for removing candidate disparities in a pixel of low reliability by performing a visibility test betweens candidate disparities in each pixel to improve the reliability of the candidate disparity; and a global optimizing unit for determining a final disparity for candidate disparities in an each pixel by performing a dynamic programming.

The invention relates to a face automatic labeling method and a face automatic labeling system. Firstly, faces are detected from a captured video, a face image set is acquired, then the face image set is filtered, an HSV (Hue, Saturation, Value) color histogram difference value of an image of an adjacent frame is simultaneously acquired, shot segmentation is carried out by adopting a spatial color histogram shot edge detecting algorithm, angular points in a target region of a first frame are detected for the faces from the adjacent frame, the angular points are deferred to a next frame by using a local matching method, corresponding updating is carried out, a matched number is subjected to statistics, and according to a threshold value of the matched number, the operation is sequentially carried out to acquire face sequences; then speakers and unspeaking people are detected by a lip motion detection module according to lip motion of the speakers in the face sequences and the speakers, talk contents and talk time are fused to be labeled; and finally, the faces on each sequence are read in and are gradually positioned, then affine transformation is carried out according to a positioning result and pixel gray values in a round region with a fixed size near a transformed feature point are extracted to be used as features of the faces. The face automatic labeling method and the face automatic labeling system which are disclosed by the invention are convenient to use and have high accuracy.

The invention discloses a contour-based two-dimensional fragment splicing method which comprises the steps of: a first step, obtaining a scanned fragment image and extracting a fragment contour curve; a second step, performing polygonal approximation and feature extraction on the contour, thereby obtaining two feature sequences, namely a rotation angle sequence and a side length sequence; a third step, searching for partial candidate matching segments between random two fragments based on the feature sequences, thereby searching for partial matching among the N fragments, comparing random two fragments of the N fragments, thereby obtaining a final partial matching set; and a fourth step, in the final partial matching set, searching a global path for partial matching based on a rotation angle which is required for splicing the fragments according to partial matching, and integrating all determined path to a path which contains all fragments, thereby realizing splicing. Compared with a best priority method, the contour-based two-dimensional fragment splicing method is advantageous in that the global path searching method based on partial matching splicing rotation angle measurement sufficiently utilizes local matching pairs; a correct matching path and a fragment reconstruction path are determined; and the matching efficiency is improved.

A system and method of delivering and accessing information including advertisements targeted to a user that assures the privacy protection of the user, and allows the user to access the advertisements without interrupting the flow of desired information content. The system includes at least one computerized user device and at least one ad matching entity communicably coupled to at least one network. The ad matching entity includes a master computer system and at least one computer sub-system, in which each sub-system is associated with a respective user device. The user device creates a user profile based upon data obtained from observing various user actions, including the consumption / abandonment of content programs or advertisements, the visiting of web pages, the use of web search terms, etc. The user profile data is provided by the user device to the sub-system of the ad matching entity, which is a trusted third party. The ad matching sub-system locally matches information contained in the user profile against information contained in a target profile, and sends the results to the master system. Based on these results, the master system transmits at least one advertisement targeted to the user to the user device. The ad matching entity then permanently deletes all records and copies of the user profile from its data storage. At a later time chosen by the user, the user can consume the advertisement in an out-of-line fashion independently of the consumption of any desired information content.

The present invention relates to an image search method capable of expressing one color feature related to a spatial color feature of a still image based on a multilevel image grid and similarity-based searching images using the thusly expressed multilevel image grid. In the present invention, hierarchical grids of different levels are generated with respect to one feature for thereby obtaining a data structure in which each cell corresponding to the grid is expressed based on a reliability on a region representative color and the region representative color, so that it is possible to fast and accurately search images with respect to a user's content-based query based on a cell matching of the same level as two image grids and different levels or a color local matching of the grid match.

The invention relates to a multi-visual-angle great-depth micro stereo visual-features fusion-measuring method, which comprises the following steps of: acquiring an original stereo-image pair through a barrel-type node structure by using a compound stereomicroscope visual system, and providing accurate matching-parallax data through the image registration and the stripe registration at different node positions on the same depth surface, the fusion of original composite-image sequences on different depth surfaces and the local matching of original images, so that high-precision three-dimensional figures can be reconstructed. The method can be used for solving the problems of sheltering in micro stereo measurement and precise visual measurement of large-scale microscopic objects, and technical bottlenecks existing in an existing stereomicroscope visual-measuring method are essentially overcome.

The invention relates to a computer binocular vision matching method based on global and local algorithms, which comprises the following steps: (1) obtaining a layered matching result from a left image and a right image which are obtained by a binocular three-dimensional vision sensor by using an image cutting method; (2) obtaining different local matching results in a local matching result by using a window matching method with different windows; (3) putting the local matching results into a markov random field with a second-order smooth energy function for iterating and optimizing to obtain the matching result. The computer binocular vision matching method can integrate global optimized and local characteristics and obtain a more accurate matching result.

The invention discloses an industrial graph fusion method based on a graph convolutional neural network. The method is based on a plurality of constructed industrial sub-graphs, and the method comprises the following steps: constructing a local entity sub-graph of a graph; converting the structure embedding of the entity into the same vector space by using the attribute embedding of the attributetriple in the graph, forming an entity embedding vector, converting an entity alignment problem into a graph matching problem, and further forming a local matching vector by using a graph attention method; propagating local matching information in a graph through GCN to form a graph-level matching vector, and finally obtaining entity alignment in the graph through a double-layer feedforward neuralnetwork. According to the invention, the structural embedding of entities is converted into the same vector space through attribute embedding, the problem that pre-aligned entities are insufficient is solved, and the entity alignment problem in the graph is further converted into the graph matching problem through graph attention. Intelligence support is provided for optimizing the industrial structure, optimizing the regional structure and improving the industrial core competitiveness.

The invention discloses a remote sensing image semantic segmentation method based on self-supervised contrast learning. The method comprises the following steps: constructing a semantic segmentation network model (such as Deeplab v3 +); carrying out pre-training on an encoder of the network model by adopting unlabeled data; after the pre-training is completed, performing supervised semantic segmentation training on the network model on a labeled sample; carrying out semantic segmentation on the remote sensing image by adopting the network model subjected to supervised semantic segmentation training, wherein in the pre-training process, a mode of combining global style comparison and local matching comparison is adopted to carry out comparative learning. Compared with the prior art, comparison self-supervised learning is applied to a remote sensing semantic segmentation data set, a global style and local matching comparison learning framework is provided, and the remote sensing image semantic segmentation method based on self-supervised comparison learning is formed, so that the semantic segmentation method is wider in application range and better in segmentation effect.

The invention provides a stereo matching method based on deep learning. The stereo matching method based on deep learning utilizes the deep learning method to extract characteristics, wherein the receptive field of each point of the obtained characteristic spectrum very large, and at the same time, the foreground expansion effect caused by a traditional local matching method is avoided, and the problem that the local matching method is hard to select windows is solved. Besides, the high dimension characteristic spectrum obtained through deep learning fully describes the data distribution characteristics of the area and has significant guiding meaning for the subsequent similarity detection. The stereo matching method based on deep learning utilizes the deep learning method to output a W*H*D cost body according to the left and right views, utilizes the WTA strategy that the winner takes it all to obtain an initial parallax graph, and finally utilizes the original left view as the guiding image to guide filtering. The stereo matching method based on deep learning has higher accuracy, and can reasonably operates GPU parallel acceleration to enable the method to achieve high operatingspeed as the parallelization degree of the neural network is high.

A speech recognition apparatus and speech recognition method are provided for reducing such events as erroneous recognition and disabled recognition and improving a recognition efficiency. The speech recognition apparatus generates a word model based on a dictionary memory and a sub-word sound model, and matches the word model with a speech input signal in accordance with a predetermined algorithm to perform a speech recognition for the speech input signal, wherein the apparatus comprises main matching means, operative when matching the word model with the speech input signal along a processing path indicated by the algorithm, for limiting the processing path based on a course command to select the word model most approximate to the speech input signal, local template storing means for previously typifying local sound features of spoken speeches for storage as local templates; and local matching means for matching each of component sections of the speech input signal with the local templates stored in the local template storing means to definitely determine a sound feature for each of the component sections, and generating the course command in accordance with the result of the definite determination.

The invention discloses a method, client side, cloud server and system for recognizing a suspicious phishing web page in combination with a local content rule base. The local content rule base comprises at least one rule and rule identification corresponding to each rule. The method includes the steps that when a browser loads a web page, content information of the web page is obtained, and appointed information is extracted from the content information of the web page; the appointed information is matched with the rules in the local content rule base; if the appointed information is matched with at least one rule in the local content rule base, the rule identification of the rule matched locally is sent to the cloud server, so that the cloud server recognizes whether the web page is the suspicious phishing web page or not according to the rule identification of the rule matched locally. Local matching and cloud recognition are combined, the detection range of the phishing web page is widened, the recognition accuracy of the phishing web page is improved, and resources of the cloud server are saved.

The present invention discloses a neighborhood Gaussian structure and video feature fusion motion identification method. The method comprises: a 3D LARK operator is employed to extract the local structure feature of the video, and a neighborhood structure assessment algorithm based on the multivariate Gaussian is provided for expressing the integrated structure; the neighborhood structure assessment algorithm and the 3D LARK features are subjected to the local matching and statistical process of the multi-scale template and the video to be detected to obtain the statistic probability matrixes of two object motions; and the two statistic probability matrixes are fused to extract the object, and the double restraints improve the accuracy of the object motion. The neighborhood relation restraint integration idea is provided on the traditional LARK operator, and a new motion identification model is provided. Compared to the current method, the neighborhood Gaussian structure and video feature fusion motion identification method is more accurate in extraction of the object motion, high in identification accuracy and is applied to the visible light and the infrared videos at complex scenes.

Provided is a stereo image object segmentation method based on rapid local stereo matching. The stereo image object segmentation method based on rapid local stereo matching comprises the steps of obtaining a reliable matching point on an image, and using Delaunay triangulation to carry out interpolation so as to obtain the parallax; building a graph, using a pixel as a vertex, and using connecting lines formed between the pixel and eight-site neighborhood pixels of the pixel as edges of the graph, wherein the weight of each edge is determined by the colors of the connected pixels and parallax information; determining whether the areas where every two connected pixels are located belong to the same segmentation area or not through a Kruskal minimum spanning tree strategy according to the weights of the edges, if yes, combining the areas, and if not, keeping the areas unchanged; judging whether the obtained segmentation area belongs to an object needing to be segmented out or not, taking out the segmentation area, and obtaining the final object. The stereo image object segmentation method based on rapid local stereo matching is rapid and effective, areas with the discontinuous parallax, such as edges of articles can be effectively processed, a plurality of objects can be rapidly segmented out, time efficiency is high, the segmentation effect is good, and the requirement for automatic and rapid object segmentation can be met.

The invention discloses a local matching method of a three-dimensional model. The method comprises the following steps of: calculating the bending salience of any vertex of the three-dimensional model; generating a sequencing list according to the bending salience and carrying out region growing to form a local vertex set; carrying out secondary surface fitting according to the local vertex set formed by the region growing; identifying a fitting region to be a three-dimensional model local subblock and extracting the features of the three-dimensional model local subblock; carrying out featurecomparison and local matching on the three-dimensional model local subblock; and carrying out overall feature comparison and overall matching on the three-dimensional model. The method disclosed by the invention can be used for matching locals of the three-dimensional model, realizing the local-to-local retrieval and the local-to-overall retrieval of the three-dimensional model and extracting obvious region features of the locals, thereby increasing the matching precision of the method; and shape normalization is not needed any more in a feature extracting process, thereby the stability of feature extraction is guaranteed.

A system and a method are disclosed for sensitive document management. The system includes one or more agents, a behavior analysis engine, a local policy engine, and a local matching service. The method identifies whether a document is sensitive, identifies behaviors applied to the document, determines whether the document contains sensitive information and determines whether to allow the identified behavior to continue based on security policies.

The invention relates to a fast synchronous tracking method and device for a TDD-OFDM downlink. The method comprises the following steps of (S110) generating a synchronous sequence; (S120) mapping the synchronous sequence into a corresponding subcarrier to obtain a synchronous signal, putting the synchronous signal on a frame header of a radio frame and generating a TDD-OFDM downlink signal; (S130) carrying out initial capture on the link signal; (S140) carrying out accurate capture on the link signal; and (S150) keeping the link signal synchronous in real time. According to the fast synchronous tracking method for the TDD-OFDM downlink, initial capture is firstly carried out by using a conjugate associated characteristic window signal, accurate capture is carried out by using training sequence correlation (local matched filtering), and accurate real-time tracking is finally carried out by using a pilot frequency, fast capture for the TDD-OFDM downlink can be achieved and synchronous tracking is achieved.

The invention relates to a method and device for loading a sequencing website. The device comprises a receiving module, a matching and requesting module, an acquiring and receiving module and an outputting module, wherein the receiving module is used for receiving input content of a user at an address bar; the matching and requesting module is used for carrying out local matching according to the input content and also requesting the sequencing website in a browser server according to the input content, wherein the sequencing website is one or more websites; the acquiring and receiving module is used for acquiring a local matched website and receiving the sequencing website from the browser server; and the outputting module is used for outputting the sequencing website and the local matched website in the address bar. According to a method for loading the sequencing website based on a browser side, disclosed by the invention, category information of a browser user is added so that the accuracy of an output result is improved.

The invention provides a pose estimation method suitable for a monocular vision camera in a dynamic environment. The pose estimation method comprises the steps: obtaining an image, and carrying out ORB feature point detection on each frame of image; carrying out feature point local matching on two continuous frames of images; judging whether the feature points meet constraint conditions or not, and if the feature points do not meet the constraint conditions, marking the feature points as dynamic points; performing instance-level segmentation on each frame of image to obtain an object contour,and marking all feature points in the object contour as dynamic points when the number of the dynamic points in the obtained object contour exceeds a threshold value; and performing feature matching on the feature points of the unmarked dynamic points by using an RANSAC algorithm, calculating a basic matrix of camera pose transformation, obtaining a camera rotation matrix and a translation vector,and realizing camera pose estimation. According to the invention, the pose accuracy of the camera can be improved, so that the precision of the whole SLAM system is improved.

The invention discloses a detection method for parallax scope influencing the comfort level of a stereo image, wherein the method comprises the following steps: processing a selected stereo image via a translation viewpoint method and a stepwise approximation method to obtain test images; calculating vertical aggregation matching costs of pixel points via an adaptive weight local matching method to obtain a parallax corresponding to the minimum vertical aggregation matching cost of the central pixel point so as to obtain a disparity map; dividing the disparity map, using a foreground region, a background region and a central region as study regions, and obtaining a parallax value of each region via a connectivity detecting method; carrying out curve fitting for subjective testing values of each test image and the parallax values of each region to obtain a parallax scope of the comfort stereo image. In combination with attention characteristics of human eye vision, the method of the invention can be used for obtaining accurate parallax scope of the comfort stereo image, thereby meeting a plurality of requirements in a practical application.

The invention belongs to an image processing technology and particularly relates to an automatic splicing method of regular shredded paper. The technical scheme of the invention is achieved through six steps of (1) preparing an image data set and preprocessing; (2) classifying the shredded paper according to Chinese and English as well as a single face and two faces; (3) extracting local regional characteristics of each image, such as a position and a grey level of a boundary pixel point of the shredded paper as well as an upper (lower) boundary height; enlarging an extraction range of the characteristics of the English shredded paper, wherein the supplementary features include a row height of the English shredded paper, a horizontal position of the English shredded paper and a vertical spacing of the English shredded paper; (4) reclassifying the shredded paper according to feature values extracted in the step (3); (5) carrying out local matching, line matching and column matching on the shredded paper; and (6) restoring the matched images. According to the automatic splicing method provided by the invention, a large amount of the shredded paper can be more accurately spliced.