1366 results about "Angular point" patented technology

A targeted heterogeneous medium in the form of an underground layered formation is gridded into a layered structured grid or a layered semi-unstructured grid. The structured grid can be of the irregular corner-point-geometry grid type or the simple Cartesian grid type. The semi-unstructured grid is areally unstructured, formed by arbitrarily connected control-volumes derived from the dual grid of a suitable triangulation; but the connectivity pattern does not change from layer to layer. Problems with determining fluid movement and other state changes in the formation are solved by exploiting the layered structure of the medium. The techniques are particularly suited for large-scale simulation by parallel processing on a supercomputer with multiple central processing units (CPU's).

The invention discloses a fruit and vegetable detection method based on deep learning. The method comprises the following steps that: S1: firstly, preprocessing data, and carrying out manual calibration on an original picture in advance to obtain a segmentation tag, wherein the calibration means the coordinates of the left upper angular point and the right lower angular point of a target frame in the original picture, and the tag is used for judging whether a target in each calibration frame is a fruit and vegetable and determining the category of the fruit and vegetable; S2: secondly, training the data, taking the original picture and the picture tag as a training set of a deep learning neural network, and combining with a RPN (Region Proposal Network) and a Fast R-CNN to train the data to obtain a final fruit and vegetable detection model; and S3: finally, testing test data, calling a final fruit and vegetable detection model and a test program, carrying out fruit and vegetable detection on a test picture, and analyzing a final fruit and vegetable detection model effect through the observation of a test result.

A method for image recognition of a material object that utilizes graphical modeling of the corner points of a vertex which includes projecting a point on a digital display to an inward depth, a one half pixel distance in the plane of the display, with a conic to a digital display, and a square block containing one half size child blocks that are scaled to depth, projecting the corner points of a vertex and replacing the bisecting points of edge features detected in a digital display scaled at an increasing rate of congruency to the dimensions of an object. The method may further include producing a digital image of the material object, providing a central processing unit, providing memory associated with a central processing unit; providing a display associated with a central processing unit; loading the digital image into the memory; defining the edges of features within the digital image; and a finding fight crucial points from registrations projected on to an edge feature display.

The invention discloses a light stream based vehicle motion state estimating method which is applicable to estimating motion of vehicles running of flat bituminous pavement at low speed in the road traffic environment. The light stream based vehicle motion state estimating method includes mounting a high-precision overlook monocular video camera at the center of a rear axle of a vehicle, and acquiring video camera parameters by means of calibration algorithm; preprocessing acquired image sequence by histogram equalization so as to highlight angular point characteristics of the bituminous pavement, and reducing adverse affection caused by pavement conditions and light variation; detecting the angular point characteristics of the pavement in real time by adopting efficient Harris angular point detection algorithm; performing angular point matching tracking of a front frame and a rear frame according to the Lucas-Kanade light stream algorithm, further optimizing matched angular points by RANSAC (random sample consensus) algorithm and acquiring more accurate light stream information; and finally, restructuring real-time motion parameters of the vehicle such as longitudinal velocity, transverse velocity and side slip angle under a vehicle carrier coordinate system, and accordingly, realizing high-precision vehicle ground motion state estimation.

An apparatus and method for estimating a location of a mobile body and generating a map of a mobile body environment using an upper image of the mobile body environment, and a computer readable recording medium storing a computer program for controlling the apparatus. The apparatus includes: a landmark generating unit observing corner points from the upper image obtained by photographing in an upper vertical direction in the mobile body environment and respectively generating landmarks from the observed corner points; and a location and map operation unit estimating the location of the mobile body and generating the map of the mobile body environment from the landmarks.

The invention discloses a method for recognizing video fire smoke image based on optical flow, which is characterized in that: optical flow of corners and points in smoke motion regions is extracted by a computer based on the video image obtained by a surveillance camera; whether the smoke is fire smoke is judged based on the set threshold by calculating the average and variance of the array consisting all corner and point optical flow speed in the foreground image and the average and variance of the array consisting optical flow speed directions; if a fire smoke is identified, the computer sends orders which controls the alarm to send alarm signals and controls the interlocked fire extinguisher to start the fire extinguishing function quickly; if a fire smoke is not identified, the first step is returned to. The method provided by the invention can not only accurately reflect the motion characteristics of smoke, reducing light interference and impact of similar pixels on the results, but also reduce computation and improve practicality. The method can greatly reduce false alarm rate and quickly and accurately realize fire smoke detection function.

The invention discloses a parameter calibration method. The method comprises steps of acquiring a calibration template image which is obtained by photographing of a calibration template image; performing corner detection for the calibration template image so as to extract an image corner; calculating radial distortion parameters in accordance with the extracted image corner; performing radial distortion correction in accordance with the calculated radial distortion parameters so as to reconstruct a distortion correction image; and according to a perspective projection relation of the calibration template and the reconstructed distortion correction image, calculating internal parameters and external parameters so as to achieve parameter calibration, wherein internal parameters and external parameters comprise internal parameter matrixes, rotating vectors and translation vectors. The invention also provides a parameter calibration device. The method and the device can be applied to parameter calibration of imaging devices such as video cameras or cameras under the condition of high distortion, the operation is simple and the precision is high.

The invention relates to an image characteristic matching method. The image characteristic matching method includes the steps of pre-processing an obtained CCD (charge coupled device) image; extracting characteristic points of the pre-processed CCD image by a SURF operator and conducting matching image by the quasi epipolar line limit condition and minimum Euclidean distance condition to obtain the identical point information; establishing affine deformation relation between the CCD images according to the obtained identical point information; extracting the characteristic points of a reference image by Harris corner extracting operator, projecting the characteristics points to a searching image by the affine transformation to obtain points to be matched; in neighbourhood around the points to be matched, counting the correlation coefficient between the characteristic points and the points in the neighbourhood and taking extreme points as the identical points; and using the comprehensive results of twice matching as the final identical point information. According to the method of the invention, can match surface images of deep-space stars obtained in a deep-space environment is utilized for imaging matching to obtain high-precision identical point information of CCD images, so that the characteristic matching is realized.

The invention discloses a complex table and a method for identifying handwritten numbers in the complex table. A complex template table is preprocessed by line detection and angular point detection to realize classified row and column ordering and obtain structural description of cells of the template table; after an electronic handwritten table is obtained, inclination of the electronic handwritten table is corrected, and the electronic handwritten table matches the template table to obtain cell position description thereof; each cell is processed by removing the edge and reserving characters in the cell as completely as possible; number images are extracted from the cells, and a trained classifier of a data set is used to identify the number images; and the handwritten characters are post-processed, and an identification result is filled into the template table. The method of the invention is easy to realize, and better in identification effect, and provides a good solution to automatic identification and table filling later.

According to an angular point positioning method and apparatus which are provided by the present invention, firstly, an interest area on a target image is subjected to edge detection to acquire a plurality of edge pixel points, then the plurality of edge pixel points are partitioned into two fit areas according to preset rules, coordinates of each edge pixel point in each fit area is subjected to linear fitting to obtain two fitting straight lines and finally, angular point coordinates can be obtained by calculating a point of intersection of two fitting straight lines, and thus, in the image matching process, the required angular point position can be accurately positioned without manually presetting an offset and not only the manual operation is reduced, but also accuacy of angular point positioning and image matching is greatly promoted, so that system accuracy of a mechanism is promoted.

The invention, which belongs to the computer vision field, provides a flexible-target-based close-range large-field-of-view calibrate method of a high-speed camera and relates to a close-range large-field-of-view binocular-visual-sense camera calibration method in a wind tunnel. According to the method, a flexible target is used for fill an overall calibration view field for calibration; the internal region of the target is formed by a planar chessboard mesh and distances between angular points of the chessboard mesh are known; the external region of the target is formed by cross target rods perpendicular to each other and a plurality of coding marking points with known distances are distributed on the target rods uniformly. During calibration, regional and constraint calibration is carried out on a high-speed camera by using different constraint information provided by different regions of the target. When the internal region of the target is calibrated, calibration is carried out by using a homography matrix; and the external region is calibrated by using distance constraints of the coding marking points. According to the invention, the cost is lowered and the operation portability is realized. During calibration, distortion of different regions is considered by using the regional and constraint camera calibration method, so that the calibration precision is improved.

The invention discloses a method for reconstructing an outer outline polygon of a building based on multivariate data. The method comprises the following steps of: respectively dividing DSM (Design Standards Manual) data and image data so as to obtain a mask image of an interest region of the building and an image dividing object; combining the mask image with the image dividing object so as to obtain a complete building object; carrying out boundary tracing on the building object so as to obtain curves of the building; using points corresponding to local maximum curvature values of the curves as angular points; connecting the angular points in sequence so as to obtain the outline polygon of the building; dividing the building object into regions by using a hierarchical clustering method and calculating the main direction of the building; establishing a linear model of the polygon of the building and correcting and regularizing the linear model of the outline of the building with the combination of the main direction of the building and gradient information of the image data; calculating an intersection point of every two adjacent straight line sections by using the linear model of each line section of the polygon; and by taking the intersection points as the angular points, connecting the angular points in sequence so as to form the final polygon of the building. According to the method, the DSM data is organically combined with the image data, the data are complementary to each other in the whole process, so that the problem of reconstructing the polygon of the outline of the building is solved well, and the method has very strong robustness in the two-dimensional outline modeling aspect of the building.

The present invention relates to a circular masking-out area rate determination-based adhesive particle image concave point segmentation method. The method comprises the following steps of 1) carrying out the image pre-processing to obtain a binary image of a particle image; 2) carrying out the concave point rough detection to obtain an angular point image of the particle image; 3) carrying out the concave point accurate detection, and utilizing an area rate method to obtain all concave points capable of being used for the particle segmentation in a regional contour; 4) carrying out the concave point pairing, wherein the selected concave point pairs are used as the segmentation points of an adhesive particle image; 5) constructing a segmentation line of the particles, obtaining the contour coordinates of individual particles, and combining the coordinates of two segmentation points to obtain the complete particle contour. According to the present invention, by combining an angular point detection method and a method based on concave point analysis, an operand problem brought by purely utilizing the concave point search based on area is avoided; by setting few parameters, a lot of sample training is not needed; at the same time, the segmentation paths can be replanned, thereby being able to adapt to the different shape and size change of the images.

The invention relates to a computer vision based automatic labelling positioning method. The method comprises the following steps: acquiring an image of a labelling sample product through an image acquiring module; preprocessing the product image through an image recognizing module; determining an interesting area based on a position to be labelled; performing corner-point detection in the interesting area in order to recognize pixel coordinates of corner points of a label; finally and accurately positioning pixel coordinates of a center point of the label; calibrating a camera; transforming the pixel coordinates of the center point of a paper carton image into world coordinates through a data processing module in a computer processing controller based on the obtained camera parameters; returning the obtained spatial position of the center point of the label as known information to a manipulator; determining a moving route based on the input position information through the manipulator; and finding out a position point to be labelled so as to realize automatic labelling operation. The method can be continuously carried out for a long time at high speed, high accuracy and high resolution ratio; the recognizing rate is high; and the measurement result is accurate.

A mosaicking method for large breadth cultural heritage image is provided, which relates to the technical field of image matching and image mosaicking. The invention comprises the following processing procedures: 1) aiming at the features of cultural heritage image, adopt an angle point detection method to extract the angle point of image, which can be taken as image feature for the matching of images; 2) calculate gradient of straight line connected between the matching points of nearby images, and; adopt a clustering method to pre-select the correlation points between images by utilizing the similarity of gradient; 3) adopt a best route method to generate a smaller mosaicking route with little pixel value, so as to evade the area with big pixel difference and remove the ghost image; 4) use a brightness component in HIS color space and blend the brightness via weighted function formula according to the mosaicking route. Compared with other mosaicking method, the method provided in the invention is able to greatly improve the speed for image mosaicking, eliminate the brightness difference of image, remove the ghost image in mosaicking and realize ideal mosaicking result.

The invention provides a camera array calibration algorithm capable of calibrating a 3D camera and obtaining relatively precise extrinsic parameters between the 3D camera and a visible light camera. The algorithm comprises the following steps: firstly, internally calibrating the visible light camera and the 3D camera to obtain intrinsic parameters of the cameras; secondly, adopting the intrinsic parameters of and a depth map provided by the 3D camera to restore the spatial locations of corner points of calibration boards, adopting minimum corner point projection error to obtain the optimum extrinsic parameters from the 3D camera to the required visible light camera, thereby completing the calibration of the whole camera array.

A motion estimation method based on the angle-point matching and the optical flow method under violent light change, relating to the computer vision technology field, comprises the following steps of: first, carrying out angle-point detection to a present frame; next, carrying out normalized angle-point matching of the present frame and a last frame rotation-invariantly; then, dividing the matched frame into blocks and calculating the affine transformation parameter in each block, carrying out block global motion vector estimating of the present frame according to the affine transformation parameter and performing motion compensation of the last frame using the vector estimation; again, carrying out block linear illumination compensation of the last frame after the motion compensation; finally, estimating the global motion vector of the next frame via the optical flow computation of the linear illumination compensated image and the present image frame. With overcoming the advantages of the invalidation of the optical flow method caused by bad conditions, violent light change and great rotation, etc, the invention obtains higher accuracy.

The invention discloses a method for identifying a freehand sketch. The method comprises the steps of acquiring a current processing track inputted by a user, and carrying out preprocessing on the current processing track; detecting valid angular points according to a preprocessing result; segmenting the preprocessing result by utilizing the valid angular points, carrying out curve fitting on each section of track, and identifying a geometric shape of the current track according to all fitting results; storing the processing result of the current processing track as at least one geometry. The invention also discloses a method for editing the freehand sketch as well as a device for identifying and editing the freehand sketch.

The invention provides a detection method for rectangular pin component visual positioning, and relates to the field of visual positioning and detection of rectangular pin components. The method aims to solve the problems that a traditional rectangular pin component detection method is low in positioning precision, pins break in images and deviation and deviation angles are detected separately. The method is characterized in that a measured component image is obtained by means of a chip mounter visual system, an image after binary pre-processing is obtained through threshold segmentation, a communication area of the component pins is marked, the shape of the component pins is judged, pixel-level Harris angular point coordinates of the pin image are extracted, sub-pixels of Harris angular points are solved and classified, the deviation angles of components are calculated, the pin image is matched with a standard image, and the deviation of the component is calculated. The method is mainly used for pin detection, deviation angle detection and deviation detection of the rectangular pin components.