696results about How to "Improve matching speed" patented technology

The present invention discloses a face in-vivo detection method and system. The face in-vivo detection method comprises the steps of: simultaneously and respectively acquiring two images of an identification object by two cameras; positioning face regions in the two images by adopting a face classifier so as to acquire face images which respectively correspond to the two images; carrying out feature point positioning on the two face images; carrying out feature point rapid stereo matching on the face images subjected to feature point positioning; calculating parallax errors of the two face image at match feature points and acquiring depth information values of the match feature points; and according to the depth information values of a plurality of match feature points, judging whether the face of the identification object is a living body. According to the present invention, excessive cooperation of a user is not required; safety is high; hidden performance is high; attitude adaptability is high; the application range is wide; a matching speed is high; and user experience is good.

The invention discloses a system for visually detecting workpiece appearance defects based on image processing, comprising an industrial personal computer, a coaxial light source, a CCD (charge coupled device) industrial camera, an image acquisition card and a rejecting mechanism; both the coaxial light source and the rejecting mechanism are connected with the industrial personal computer; the CCD industrial camera is connected with the industrial personal computer through the image acquisition card; wherein the coaxial light source is used for providing a diffuse reflection light source for a workpiece to be detected; the CCD industrial camera is used for taking an image of the workpiece at a detection station; the rejecting mechanism is used for rejecting from a production line, workpieces detected to be defective; the industrial personal computer has a defect detection module based on image processing; the system is high in detection efficiency and easy to implement.

The invention relates to a fuzzy Chinese address geographic evaluation method based on a matching rule, which belongs to the field of the address evaluation of a geographic information system. The method comprises the following steps: firstly, reading in an address character string and a standard address base; inquiring and dividing administrative division parts in the address character string and filtering reduced target data sets; then realizing the segmentation and the matching of an address by means of a matching rule tree and a rule base in allusion to the fuzzy problems of address element incompletion, address ambiguity and the like frequently appearing in the address character string, and returning a matching record meeting requirements. The invention integrates two important links of address segmentation and database matching in geographic evaluation, realizes that the database matching of the address is completed while in segmentation, effectively solves the address matching problem of the fuzzy Chinese address and improves the accuracy and correctness of address matching.

The invention discloses a workpiece apparent defect detection method based on machine vision. Firstly, a visual system is used for guiding a robot, the pose of a target workpiece is precisely positioned according to a template matching algorithm based on a gray value, and then workpiece apparent defect detection is carried out and comprises the steps that firstly, a workpiece image is acquired and pretreated through median filtering; secondly, the target workpiece is divided through a global threshold value, and workpiece pose correction is carried out; thirdly, burr interference of the edge of the workpiece is removed through mathematical morphology open operation; fourthly, notches, material sticking, cracking, indentation, needle eyes, scratches and foaming apparent defects are detected. The method solves the problems that the artificial detection speed is slow, the efficiency is low and precision is poor; the problems that according to current vision detection, defect types are singular, the imaging quality is poor, and the false drop rate is high are solved, and the automation degree of precise workpiece production and product quality are improved.

The invention provides a contour vector feature-based embedded real-time image matching method. The method uses the linear feature based on X and Y direction vectors, and has strong capability of resisting image distortion, noise, shading, illumination changes, polarity inversion and so on. An image pyramid search strategy is used, templates are quickly matched in a high-layer low-resolution image to be tested, and then, a target position is found out accurately by stepwise downward search, so that matching time is reduced greatly. According to the template image specific information, the best pyramid hierarchy number and the best rotation angle step size for the pyramid template matching of each layer are calculated automatically. An image pyramid highest-layer three-level screening matching strategy is provided, treatment is carried out according to the specific content of the image to be tested, and the first level of screening and the second level of screening are carried out; the non-target position is eliminated just by the addition and subtraction and the conditional statements, which is more efficient in the embedded system than using the multiplication and division; and the third level only processes fewer positions meeting the requirements of the above two levels, so that the matching speed is improved greatly. The overall method can realize the work of matching and locating the target at any angle and any coordinate.

The invention provides an image multifeature extraction and fusion method and the system, comprising the following steps of, extracting color features from an image to be matched, matching color with the target image, making sure the color similarity degree, if the color similarity degree exceeds the given color similarity degree threshold, entering the next step; extracting additional feature from the image to be matched, matching the auxiliary features with the target image, determining the auxiliary feature similarity degree, the auxiliary features comprise at least one of texture feature and shape feature; on the base of color similarity degree and auxiliary features similarity degree, making synthesis judgment and acquiring the synthesis similarity degree between the image to be matched and the target image, or matching the target image with the auxiliary features extracted from the matching zone of the image to be matched. The method and the system of the invention apply a cascade connected way to match from roughness to exactness, and can determine exactly the similarity zone of the target image and the image to be matched. The method and the system of the invention achieve a rapid and highly effective matching effect and save manpower and resources.

The invention provides a feature extraction and matching method and device for a digital image based on PCA (principal component analysis), belonging to the technical field of image analysis. The method comprises the following steps of: 1) detecting scale space extreme points; 2) locating the extreme points; 3) distributing directions of the extreme points; 4) reducing dimension of PCA and generating image feature descriptors; and 5) judging similarity measurement and feature matching. The device mainly comprises a numerical value preprocessing module, a feature point extraction module and a feature point matching module. Compared with the existing SIFI (Scale Invariant Feature Transform) feature extraction and matching algorithm, the feature extraction and matching method has higher accuracy and matching speed. The method and device provided by the invention can be directly applied to such machine vision fields as digital image retrieval based on contents, digital video retrieval based on contents, digital image fusion and super-resolution image reconstruction.

The present invention provides an improved closed-loop detection algorithm-based mobile robot vision SLAM (Simultaneous Location and Mapping) method. The method includes the following steps that: S1,Kinect is calibrated through a using the Zhang Dingyou calibration method; S2, ORB feature extraction is performed on acquired RGB images, and feature matching is performed by using the FLANN (Fast Library for Approximate Nearest network); S3, mismatches are deleted, the space coordinates of matching points are obtained, and inter-frame pose transformation (R, t) is estimated through adopting thePnP algorithm; S4, structureless iterative optimization is performed on the pose transformation solved by the PnP; and S5, the image frames are preprocessed, the images are described by using the bagof visual words, and an improved similarity score matching method is used to perform image matching so as to obtain closed-loop candidates, and correct closed-loops are selected; and S6, an image optimization method centering cluster adjustment is used to optimize poses and road signs, and more accurate camera poses and road signs are obtained through continuous iterative optimization. With the method of the invention adopted, more accurate pose estimations and better three-dimensional reconstruction effects under indoor environments can be obtained.

The invention relates to a map matching method of floating car data. An optimal matching path is guaranteed and an alternative path set of each global positioning system (GPS) point is minimized at the same time by means of multistandard dynamic planning technology, and therefore the matching efficiency is improved. In addition, aiming at the characteristics of map matching, a traditional shortest path analytical method is improved, and the matching speed is further improved by reducing a mark initialization process and a searching method from multiple points to a single point. Compared with other current methods, the map matching method of the floating car data is better in matching accuracy and matching performance, can achieve real-time map matching processing of low sample frequency floating car data in a city traffic network, and has business popularization and application prospects.

The large part three-dimensional reconstruction method based on the image sequence comprises the following steps that S1, an unmanned aerial vehicle carrying a camera flies around a target part, and ato-be-reconstructed image sequence is obtained; s2, adopting an SIFT algorithm and an SURF algorithm to jointly extract image feature points; s3, estimating camera motion by calculating an essentialmatrix and a basic matrix based on the sparse feature points obtained by the SIFT corner points and the SURF corner points, and registering three-dimensional space points to obtain sparse point cloudof a three-dimensional scene; s4, judging whether the optimized sparse point cloud has a symmetrical repeated structure or not; and S5, taking the sparse point cloud as seed point and reference imageinput, and performing dense reconstruction based on a dense three-dimensional point construction method of multiple views to obtain a low-resolution depth map. The three-dimensional point recovery andcorrection method based on the image sequence has the advantages that the three-dimensional point recovery and correction method based on the image sequence is provided, and construction from the image sequence to the space sparse three-dimensional points is achieved.

The invention provides a three-dimensional reconstruction method for binocular stereo vision. The method comprises the steps of performing image pair collection: obtaining images of a calibration plate and an object; performing camera calibration: performing calibration on a camera based on a Zhengyou Zhang calibration method to obtain initial internal and external parameters of the camera; performing stereo rectification: performing rectification on a distortion parameter through epipolar constraint to obtain a rectified image pair; performing image processing: obtaining a region of interest,and balancing brightness difference between left and right images, thereby searching for matching points; performing stereo matching: implementing a multi-grid intensive stereo matching algorithm toobtain a continuous smooth disparity map; and performing point cloud rebuilding and model rebuilding: obtaining a point cloud chart of the object, performing point cloud optimization, and obtaining acomplete object model through triangulation of a greedy algorithm. The smooth model with no obvious difference with the real object can be obtained; and the method can be used for three-dimensional reconstruction of multiple scenes.

The embodiment of the invention provides a method and device for matching regular expressions. The method comprises the following steps of: firstly, inputting a message to be matched and a DFA (Deterministic Finite Automaton) state table, wherein the DFA state table comprises a state transition table including transition relationships between all state addresses and each state in the matching process of the regular expressions; secondly, judging a data type corresponding to the present state, wherein the data type includes a single-character Char type and a multi-character Str type, and the data corresponding to the Str type are a plurality of continuous characters; if the data type is the Str type, matching a plurality of character values in the current state of the message to be matchedand the matching condition, and when matched, shifting to the next state satisfying the matching condition; if the data type is the Char type, matching a single character value at the current state in the message to be matched and the matching condition, and when matched, shifting to the next state satisfying the matching condition; and when the next state is an accept state, finishing the matching process and outputting a success result of matching. The method for matching regular expressions has high matching speed and high efficiency and the space occupied by the DFA items is small.

The invention relates to a reversing obstacle automatic detection and early warning method based on binocular vision. The method comprises steps that: 1), a binocular camera is calibrated; 2), a pavement area without abundant textures is removed from a binocular video frame image pair; 3), the contour at the right eye image is extracted, and cutting amount of a left eye image is determined; 4), a disparity image based on the left eye image is acquired according to the cut left eye image and the complete right eye image; 5), a splicing position of the right eye image is determined according to the disparity image of the left eye image, and the left and right eye images are spliced; 6), a suspected barrier contour and an external rectangle are extracted from the spliced image of the left and right eye images; and 7), pixel height of the suspected obstacle is calculated, the obstacle is screened, a distance to the obstacle is calculated, obstacle and distance marks are made on the spliced image, and grading early warning is realized. The reversing obstacle automatic detection and early warning method has advantages of simple and practical performance and high accuracy.

The invention provides an image matching system applied to a computer. After the computer executes the image matching system to perform binarization processing on an image to be matched and a template image, outline characteristic points are extracted from the image to be matched and the template image, a geometric figure is obtained according to the fit of the outline characteristic points, the image is matched based on the geometric figure, and the coordinate, direction and other information of a target object in the image to be matched are determined. The invention also provides an image matching method. The image matching system and the image matching method can reduce the computed amount in the image matching process and improve the image matching speed.

The invention discloses a method for automatically detecting the printing defects of a remote controller panel based on an SURF (Speed-Up Robust Feature) algorithm. The method disclosed by the invention comprises the following steps: carrying out histogram equalization on a to-be-detected sample image by making a remote controller template image, respectively acquiring feature points of the template image and the to-be-detected image through the SURF algorithm, matching the feature points by utilizing a partitioned and accelerated nearest neighbour matching method, acquiring a homography matrix according to a matching result, carrying out affine transformation on the to-be-detected image to obtain a correction image by utilizing the homography matrix, processing difference images of the template image and the correction image superposed with a mask, carrying out binaryzation and morphological processing on a difference image result, judging whether a to-be-detected sample is qualified, if the to-be-detected sample has a defect, locating the position of the defect; if the to-be-detected sample does not have a detect, judging that the to-be-detected sample is qualified, and completing detection. The method disclosed by the invention is capable of effectively detecting defects in the to-be-detected sample and accurately locating the positions of the defects.

The invention discloses an address matching method based on semantic recognition. The method uses an address matching engine and a log analysis engine. The address matching engine comprises an administrative division semantic module, a place name class semantic module, a standard address module, a semantic rule module, a Chinese word segmentation module, a semantic recognition module, and a search module. According to the method, matching addresses are quickly and accurately searched through semantic recognition according to user-entered addresses under research, search results are returned to uses in the form of online services, the log analysis engine records, analyzes and searches logs, and the address matching engine is optimized according to the log analysis results.

The invention provides a panorama-based outdoor movement augmented reality method for accurately marking a POI. A panorama is generated on line at the current site where a user is located, and a POI template image which is placed in a server side in advance is matched to the panorama generated on line through a template matching algorithm; meanwhile, the POI template image is roughly positioned in the panorama by calculating the azimuth angle between the current position and the POI in the process, and the searching range of the template matching algorithm is effectively decreased; after recognition is finished, the user can select an interesting area in the generated panorama, personalized augmented reality labels such as words, sounds and a GPS are added to the interesting area, and the interesting area is uploaded to a server to be used as POI information base expansion. According to the panorama-based outdoor movement augmented reality method for accurately marking the POI, the brand-new implementation way is provided for outdoor movement augmented reality, and the user can visually obtain the augmented reality information and deepen the understanding of the surrounding environment by accurately marking POI information on the panorama of the current position where the user is located.

The invention discloses a rapid fingerprint identification method based on image characteristics and minutia characteristics. The method comprises the following steps: firstly, detecting a reference point and determining a direction thereof, and determining the reference direction of the reference point by observing the difference between the fingerprint direction and the radial direction in sector regions with different sizes; carrying out image characteristic extraction, performing feature selection after normalization, and finally, obtaining the characteristic vector of the fingerprint image; establishing a minutia template and transforming the obtained minutiae under a polar coordinate system to establish a fingerprint minutia template; and carrying out the characteristic matching, i.e. as for the input fingerprints to be compared, judging whether the two fingerprints are matched or nor by using the fingerprint image characteristics and the minutia template obtained from the three steps. The invention not only can effectively inhibit the influence generated during the fingerprint image translation and the rotation, but also avoids the dependence to the detected reference point and the direction thereof in the recognition process and can also rapidly and accurately judge whether the fingerprint to be identified is matched with the template fingerprint or not.

The invention belongs to the field of machine vision and relates to a polar correction based sub-pixel level phase three-dimensional matching method. The polar correction based sub-pixel level phase three-dimensional matching method mainly aims at the problem of three-dimensional matching efficiency and accuracy in a three-dimensional measuring system through a binocular structure projection gate phase method. According to the polar correction based sub-pixel level phase three-dimensional matching method, a binocular three-dimensional visual geometric structure is calibrated into a head-up binocular standard geometric structure, phases formed by a matching point in a left camera and a right camera are in the same horizontal line, a dense phase value of a calibrated new phase graph is obtained through bilinear interpolation, a phase area based three-dimensional matching algorithm is provided, an initial matching point is obtained, similarities within a 3*3 area close to the initial matching point are fit into a quadric surface through least square method based surface fitting, a local minimum of the surface is obtained, and coordinates of a right camera matching point with the same phase as a to-be-matched point are obtained. The polar correction based sub-pixel level phase three-dimensional matching method can rapidly and accurately achieve dense three-dimensional matching and satisfies a requirement for industrial applications.

Embodiments of the invention disclose a human face image matching method and apparatus, a terminal and a storage medium. The method comprises the steps of obtaining a target attribute feature of a target human face image; in an image library, determining attribute features of human face images corresponding to the target attribute feature; determining priorities corresponding to the target attribute feature; and according to a sequence of the priorities, matching the target human face image with the corresponding human face images in the image library stage by stage. By adopting the technicalscheme, the human face image matching speed is effectively increased.

The invention provides a system and a method for matching and processing sensitive words on the basis of polymerized word trees. The system comprises a sensitive word library unit, a polymerized word tree algorithm processor, a semantic analysis unit and an industry sector analysis unit. The sensitive words in a sensitive word library are polymerized in a word tree polymerizing manner, so that the word tree structure is formed, the structure of the data in the sensitive word library is ordered, the space of a memory is saved, and the matching efficiency is improved. The method is combined with the application of industrial rules and adopts a manner of filtering by combining semantic analysis and industry environments, so that key words which do not belong to a sensitive word category in certain industrial fields are eliminated, matching errors of the sensitive words are reduced and the matching accuracy is improved.

The invention discloses an image matching method based on polygon generalized Hough transform. The method includes: (1) off-line stage: (1.1) performing edge extraction and polygon fitting of a template image; (1.2) building an R-Table table by employing the local triangle characteristics and the vector relation between the vertex and a reference point of the template image; (2) on-line stage: (2.1) performing edge extraction and polygon fitting of a target image; and (2.2) voting for the target image; the position point with the highest vote is regarded as a matching point corresponding to the reference point of the template image so that the corresponding relation between the vertex of the polygon of the template image and the vertex of the polygon of the target image is determined, and parameters for displacement, rotation and zooming between the template image and the target image are determined. The method is used for real-time positioning of objects in RFID manufacturing equipment and LED manufacturing equipment, and the robustness and the precision are good.

The invention provides a method for eliminating a Brisk (binary robust invariant scale keypoint) error matching point pair by utilizing RANSAC (random sampling consensus). The method comprises the following steps: firstly, preprocessing images to be processed by adopting Gaussian smooth filter, so as to remove the influence of noise on a follow-up algorithm; secondly, carrying out keypoint detection, description and matching on the above two smoothed images by adopting the Brisk, so as to obtain the matching point pair; and finally, further processing the obtained matching point pair by utilizing the RANSAC, so as to eliminate the error matching point pair, so that the matching precision is improved. Compared with the method for detecting, describing and matching the keypoint only by utilizing the Brisk, the method provided by the invention has the advantage that the matching precision is further improved on the basis of keeping the high-speed matching and calculation speed in the original method; and the method provides a foundation for follow-up high-precision tracking.

The invention discloses a low-resolution multi-spectral palm print and palm vein real-time identity recognition method and system. Palm images are collected by the system under the condition of five spectrums, and complementarity of multi-spectrum image information is fully utilized to improve the system recognition rate; meanwhile, palm vein information is collected under the condition of near infrared spectrums so that the system can have the living body detection ability and the counterfeit attack preventing ability of the system can be improved; characteristic extraction speed and other postprocessing speed are improved through the down sampling technology based on bicubic interpolation, and storage space of a characteristic template is saved; characteristic extraction is carried out through a multi-scale multi-directional filter, the influence of lighting changes on characteristic extraction is reduced, and the robustness of the system is improved; a characteristic matrix is coded through a hash table, and system matching speed is further improved; the recognition rate of the system is further improved through the unique fraction-level multi-spectral characteristic fusion method. The system has the advantages of being high in resolution ratio, high in recognition speed, good in stability and expansibility, resistant to counterfeit attack and the like.

The invention discloses an 'internet+' package bottle intelligent recovery system and method. The system comprises an intelligent recovery device, user terminal equipment and a cloud service which are connected through internet communication; the intelligent recovery device comprises a human-computer interactive system, an electromechanical control device, a package bottle transmitting and rotating device, a package bottle identifying device, a package bottle compressing and crushing device, and a machine cabinet. A user selects to start throwing a bottle through the human-computer interactive system or the user terminal equipment; the intelligent recovery device has the functions of identifying the bar code, the weight, the image and the material of the package bottle. If the intelligent recovery device fails to identify, the package bottle is rejected. If the package bottle is identified successfully, the package bottle is compressed and crushed, and is recovered and stored; meanwhile, the user gets rebate. The 'internet+' package bottle intelligent recovery system is convenient to operate and use; the interaction and data sharing of the user, the intelligent recovery device, internet cloud and a user terminal are realized by utilizing the internet; the popularization of an 'internet+' resource recycling development is strongly promoted.

The invention discloses a real-time 3D reconstruction method based on a depth map. The method comprises steps that depth maps and an RGB color map of a shooting scene are obtained through utilizing adepth camera; each frame of the depth maps is processed as follows, the depth information is complemented, pixel points are then converted into a first type of three-dimensional coordinate points, anda normal vector of each pixel point is calculated; the first type of three-dimensional coordinate points corresponding to the depth map are converted into a second type of three-dimensional coordinate points; each of the second type of three-dimensional coordinate points corresponding to the depth map is assigned a voxel block, and a hash table is utilized to index the voxel blocks; an sdf valueof each voxel in the voxel blocks is updated through weighted fusion of the voxel blocks, and the scene surface is extracted; the texture information of the scene surface is obtained, and a surface normal vector of each voxel of the scene surface is calculated. The method is advantaged in that the reconstruction speed and reconstruction quality can be effectively improved, and the method is applicable to large-scale scene reconstruction.

Embodiments of the invention disclose a fingerprint unlocking method and a mobile terminal. The fingerprint unlocking method can comprise the steps of obtaining a fingerprint image input by a user; determining a target fingerprint group corresponding to the fingerprint image, wherein the target fingerprint group comprises a plurality of fingerprint templates; performing matching on the fingerprint templates and the fingerprint image in sequence according to a preset sequence; and when any fingerprint template in the fingerprint templates is successfully matched with the fingerprint image, unlocking the mobile terminal. With the adoption of the embodiments of the method and the mobile terminal, the target fingerprint group is firstly determined before fingerprint matching, so that the matching range can be reduced; and the matching is performed according to the preset sequence, so that the fingerprint matching frequency can be further reduced, the matching speed can be increased, and the fingerprint identification efficiency can be improved.

The invention provides a feature extraction and matching method in visual navigation. According to the method, a feature region is extracted by adopting a two-dimensional maximum entropy threshold segmentation method; an external square region of the feature region is subjected to image normalization processing; each external square region subjected to the image normalization processing is used as a feature region to be matched; a feature vector of a feature point is obtained; each feature point in each feature region in a first image is matched with feature points in each feature region in a second image, and the number of matching points is obtained; and two feature regions with the most matching points are selected as matching regions, wherein matched feature points are used as matching feature points. According to the scheme, the number of the matching points is obtained through feature point matching; the feature regions with the most matching points are obtained by using the number of the matching points as a screening condition; the matching of the feature regions is completed; the practical matching pair is further obtained; and the matching points of navigation images with fine, dense and single textures under the condition of generating affine transformation such as shear transformation is increased.

The invention relates to a video matching method, which comprises the following steps: selecting one frame calculated with an integral image depth map in a video image sequence as a reference frame; acquiring a varying area of a first image of a current frame relative to a first image of the reference frame, and a varying area of a second image of the current frame relative to a second image of the reference frame; and matching and calculating depth maps of the varying area of the first image and the varying area of the second image of the current frame. The invention also relates to a video matching device and a system. The invention utilizes video images, particularly correlation among video image sequences to select the frame matched with the integral image and calculated with the depth map as the reference frame, and newly performs corresponding image matching and depth map calculation only for the varying area of the current frame by detecting the varying area of the image of the current frame relative to the image of the reference frame, therefore, the invention shortens the matching time of the image of the current frame remarkably so as to improve the matching speed of the video and achieve the quick matching of the video.

The invention discloses a moving target anti-fusion shielding tracking algorithm which specifically comprises the following steps of: firstly, judging whether the current moving target is in a fusion shielding state according to the target shielding judgment criterion; classifying all shielding targets according to the target moving information, and separating the active shielding targets and the passive shielding targets; obtaining the real positions of the targets by different template matching algorithms for different types of shielding targets respectively, wherein an overall template matching method based on fast Fourier transform and integral images is adopted for the active shielding targets, and an improved sub-block template matching method is adopted for the passive shielding targets; matching and estimating the moving displacement of the sub-block template by use of a target prospect adaptive block to realize the adaptive update of the template; and finally, realizing the anti-fusion shielding tracking of the target by combining the target overall template matching based on fast Fourier transform and integral images and the adaptive multi-sub-block template matching.