1863 results about "Image splicing" patented technology

The invention discloses a real-time panoramic image stitching method of aerial videos shot by an unmanned plane. The method comprises the steps of: utilizing a video acquisition card to acquire images which are transmitted to a base station in real time by an unmanned plane through microwave channels, carrying out key frame selection on an image sequence, and carrying out image enhancement on key frames; in the image splicing process, firstly carrying out characteristic detection and interframe matching on image frames by adopting an SURF (speeded up robust features) detection method with good robustness; then reducing the series-multiplication accumulative errors of images in a frame-to-mosaic image transformation mode, determining images which are not adjacent in time sequence but adjacent in space on a flight path according to the GPS (global positioning system) position information of the unmanned plane, optimizing the frame-to-mosaic transformation relation, determining image overlapping areas, thereby realizing image fusion and the panoramic image construction and realizing real-time effect of carrying out flying and stitching simultaneously; and in image transformation, based on adjacent frame information in a vision field and adjacent frame information in airspace, optimizing image transformation to obtain the accurate panoramic images. The stitching method has good real-time performance, is fast and accurate and meets the requirements of application occasions in multiple fields.

The invention provides a binocular camera-based panoramic image splicing method. According to the method, a binocular camera is arranged at a certain point of view in the space, the binocular camera completes photographing for once and obtains two fisheye images; a traditional algorithm is improved according to the defect of insufficient distortion correction capacity of a latitude-longitude correction method in a horizontal direction; corrected images are projected into the same coordinate system through using a spherical surface orthographic projection method, so that the fast correction of the fisheye images can be realized; feature points in an overlapping area of the two projected images are extracted based on an SIFT feature point detection method; the search strategy of a K-D tree is adopted to search Euclidean nearest neighbor distances of the feature points, so that feature point matching can be performed; an RANSAC (random sample consensus) algorithm is used to perform de-noising on the feature points and eliminate mismatching points, so that image splicing can be completed; and a linear fusion method is adopted to fuse spliced images, and therefore, color and scene change bluntness in an image transition area can be avoided.

A 360 degree panoramic aerial view generation method used for assisting vehicle driving is disclosed. The method is characterized by: firstly, erecting four wide-angled cameras around a vehicle and guaranteeing that the cameras can cover all the field areas surrounding the vehicle; secondly, calibrating a camera parameter and carrying out distortion rectification on the collected image; then, carrying out areal perspective transformation on the rectified image so as to obtain the aerial view with a downward view effect; finally, establishing a image splicing lookup table so that a system can rapidly complete splicing of a panoramic picture through a lookup table method. The method is simple is easy to perform. A hardware equipment requirement is low. The system realizes the splicing of four pictures through the lookup table mode, which is rapid and has less amount of calculation. The operation parameter which is calibrated once by using the method can be served as a constant, be stored and be used in real time hardware system work so that system processing time can be substantially reduced and the real-time performance requirement of the system can be satisfied.

The invention discloses a high-precision dynamic map data processing system and method based on road side sensors. The high-precision dynamic map data processing system comprises a map data acquisition terminal and a high-precision map generation service terminal. The map data acquisition terminal provides a bulk of diversified map road original data for the high-precision map generation service terminal; the high-precision map generation service terminal comprises a map data processing module and a map generation visual module; the map data processing module is used for extracting road features from the map road original data and carrying out hierarchical design on all the road features, splicing information of the same road, completing road feature data fusion on the road feature aspect first, finally completing image splicing on the image aspect, and generating a road downward projection drawing in dependence on the splicing result; and the map generation visual module is used for marking road information on the downward projection drawing, the marked road information and the downward projection drawing commonly form map data of a high-precision map, visual editing is carried out on the map data, and a high-precision dynamic map is generated. According to the invention, the generation cost of the high-precision map can be reduced, and the high-precision dynamic map can be updated quickly.

The invention discloses an image registration and multi-resolution fusion-based panoramic image splicing method. An adaptive threshold of sequence images is subjected to binary processing and image contour information is extracted by utilizing a pixel neighborhood relationship; a similar region of an image contour structure is quickly estimated through a similarity measurement method for Hu momentinvariant features; and SIFT feature point extraction is performed in a similar region part of two original images. Moreover, feature point initial matching is performed by using a bidirectional K-nearest classification algorithm; mismatched points are screened by an RANSAC algorithm; and an affine transformation matrix among the images is estimated. In addition, in an image fusion aspect, brightness equalization and local color mapping processing is adopted. Then, through an improved Laplacian pyramid multi-resolution fusion algorithm, spliced images are fused to realize seamless splicing. According to the method, the image splicing time is shortened, the image splicing efficiency is improved, the similar region can be quickly located, the mismatch in splicing is effectively improved, and the image registration precision is improved.

A system for capturing images of a target, such as a test tube, that is presented in front of an optical imager and rotated 360 degrees. The imager of the system captures a series of images which are then stitched together to form a panoramic image of the target. The panoramic image may then be processed to decode any barcode code information placed on the target, capture other information placed on the target, or obtain information about the target or the contents thereof.

The invention discloses a fast image splicing method based on an improved SURF algorithm. An existing corner extraction method and an existing corner feature description method are improved, mismatching of extracted corners is eliminated, and multiple images can be spliced fast. At first, an improved FAST algorithm is adopted for increasing the extracted corners, the operation speed of the FAST algorithm for extracting the corners is high, and after the improvement is carried out, the stability is good; secondly, the combination of SURF description and LBP description is adopted for describing the corner feature, and in this way, the speed for matching the corners can also be increased; then an RANSAC method is adopted for eliminating mismatching, accuracy is improved, and a more accurate transformation matrix is obtained, so that fast splicing is carried out; finally, according to obtained matching point pairs, parameters for transforming images to be spliced into reference images are calculated, and a slow-in and slow-out method is adopted for finishing image splicing.

The invention discloses a splicing device for a real-time high speed high definition panoramic video and a method thereof. The method comprises the steps: S10, obtaining spliced multipath real-time video sequences; S20, judging whether video images at the same moment in any two paths of video sequences meet the image splicing condition; S30, calculating an image splicing parameter; S40, selecting a projection face and mapping the video images in the multipath real-time video sequences to the same mapping face according to the splicing parameter, then determining the panoramic projection face; S50, establishing a mapping table of pixel points on the video images and coordinate points of the overall projection face; S60, conducting exposure and fusion processing on pixel values of all the coordinate points on the panoramic projection face and outputting the panoramic video images according to the pixel values. The splicing device for the real-time high speed high definition panoramic video and the method of the splicing device can greatly improve splicing efficiency of the images, ensure output quality of the images, and meet the requirement for real-time high speed high definition panoramic video.

The invention discloses a rapid image splicing method based on wide-angle lenses. The method includes the steps that firstly, distortion correction is conducted on images acquired through the wide-angle lenses; secondly, cylindrical surface mapping is conducted on the images on which distortion correction is conducted, and a two-dimensional discrete coordinate mapping table is generated for each wide-angle lens; thirdly, the two-dimensional discrete coordinate mapping table of each wide-angle lens is loaded, and distortion correction and cylindrical surface mapping are sequentially conducted on the distortion images acquired through the wide-angle lenses according to the tables; fourthly, translation parameters between adjacent visual angle images on which cylindrical surface mapping is conducted are acquired, and the adjacent visual angle images are registered; fifthly, the registered adjacent visual angle images are fused, wherein Laplacian pyramids are established for registered adjacent visual angle image sequences respectively, linear fusion is conducted on a high-frequency pyramid image overlaying region and a low-frequency pyramid image overlaying region, and then a fused image of the adjacent visual angle images is obtained. The method has the advantages of being high in splicing speed and real-time performance.

The invention discloses a method of an unmanned plane image real-time splicing. The method comprises the following steps: (1) obtaining image data downloaded by an unmanned plane in real time and obtaining global position system (GPS) information of the unmanned plane, attitude information, height information, speed information, camera parameter information synchronously downloaded with the image data in the real time; (2) carrying out processing and transformation on the obtained images according to the information of the first step and obtaining the pre-processed images; (3) carrying out overall dynamic image amendment for to-be-spliced images and spliced images; (4) judging image overlapped areas according to the flying direction of the unmanned plane, obtaining templates, and carrying out image matching and image fusion; (5) achieving splicing for the frame image, and then entering the first step to carry out image splicing of the next frame. The method can quickly obtain the flying direction trend of the image of the unmanned plane, shortens matching searching ranges, enables the matching time to be shorter than that of a span practice that adjacent images are downloaded by the unmanned plane, and real-time performance of the image splicing of the unmanned plane is guaranteed.

The invention discloses a parallel and matching precision constrained splicing method for consecutive frames of multi-feature-point unmanned aerial vehicle reconnaissance images, and belongs to the technical field of unmanned aerial vehicle image processing. According to the method, the data sizes of four stages, namely, the feature extraction sage, the feature matching stage, the matrix transformation stage and the image synthesis stage, of image splicing are deeply analyzed, and the serial or parallel dependence relations between the stages are deeply analyzed. The data processing mode which conforms to the large-data-size image processing features of an unmanned aerial vehicle and meets the requirement for processing the features of the unmanned aerial vehicle is designed according to types of data and relations between the data. Meanwhile, a multi-core resource and multi-thread calculation method of a computer is applied to the data processing process so that the use ratio of computing resources can be increased and the operation speed can be increased. The method is high in pertinence, the capacity for splicing and processing the large-data-size remote sensing images of the unmanned aerial vehicle can be remarkably improved, and real-time generation of image splicing intelligence of the unmanned aerial vehicle is ensured.

The invention discloses a bridge crack detection method. Due to the fact that manual marking has certain subjectivity, the pavement crack detection precision depends on experience knowledge of experts, and experience lacks objectivity in quantitative analysis. The method comprises the following steps: 1, collecting images of a detected bridge floor one by one to obtain a bridge floor image set; 2,splicing images; 3, detecting crack; 4, extracting crack parameter. According to the invention, the image acquisition and processing technology replaces human eyes to complete automatic nondestructive detection of the bridge crack, and has very important practical significance for research of the bridge crack detection technology in a complex terrain environment. On one hand, the construction safety is enhanced, and on the other hand, the operation maneuverability and flexibility are improved. According to the invention, fidelity splicing of multiple groups of bridge deck images is realized,the image splicing precision and efficiency are improved, a working foundation is laid for subsequent bridge crack image detection, and a technical reference is provided for image splicing detection in other fields.

The invention relates to the multi-video seamless splicing technology. Calibration of a relative position relation between multiple videos is needed. The invention proposes a multi-video seamless splicing method and a splicing panoramic camera apparatus taking a fish-eye panoramic camera as a reference. The apparatus comprises a fish-eye panoramic camera and a camera array formed by a plurality of common cameras. The fish-eye panoramic camera photographs a panoramic image in a 180 DEG view. The camera array photographs common videos which are used for the multi-video splicing. According to the method, all the cameras in the camera array are in registration with the panoramic image, a relative position relation between the camera array and the panoramic camera is established, and the seamless splicing of the multiple videos are conduced according to the relative position relation. The method and the apparatus have the advantages such as low demand for overlapping field of vision, and good robust performance of registration, and solve a problem of poor image splicing effect caused by low image registration precision in a conventional spliced panoramic camera composed of multiple common cameras.

The invention discloses a fast image splicing method, which is characterized by comprising the following steps of: (1) acquiring a single-breadth field image; (2) extracting characteristic information in an image to be spliced; (3) performing two-dimensional wavelet transform on the image to be spliced to obtain high-frequency coefficients reflecting the profile of change in a horizontal direction and a vertical direction of the image, and realizing overlapped position alignment in combination with a phase correlation method; and (4) adopting a weighted mean method to fuse overlapped areas of the image to finish the splicing. In the method, low-energy coefficients reflecting the gradual change of illumination are removed by performing the two-dimensional wavelet transform on the image and then the high-frequency coefficients reflecting the profile of the change in the horizontal direction and the vertical direction of the image are obtained, which can effectively reduce calculation complexity; and simultaneously, the fast and accurate overlapped position alignment is realized in combination with the phase correlation method and the fusion of the image is realized by adopting the weighted mean method so as to realize the fast and accurate splicing of PCB images of various specifications and various colors.

Embodiments of the invention provide a panoramic selfie taking method and a mobile terminal, which are applied to mobile terminals comprising cameras and flexible screens. The method comprises: receiving a panoramic selfie taking command input by a mobile terminal user; controlling a flexible screen to axially rotate, and controlling a camera to continuously acquire each frame image; detecting whether preset shooting finish conditions are met; when the preset shooting finish conditions are met, finishing the rotation of the flexible screen and the image acquisition of the camera; and based on the acquired each frame image, performing image splicing, thereby generating a panoramic selfie. According to the panoramic selfie taking method provided by the embodiments of the invention, the mobile terminal only needs to rotate for a relatively smaller angle, and then can acquire one panoramic selfie.

Embodiments of the invention are directed toward methods for an effective blind, passive, splicing/tampering detection. The methods of the various embodiments of the invention use a natural image model to detect image splicing/tampering with a model that is based on statistical features extracted from a given test image and multiple 2-D arrays generated by applying the block discrete cosine transform (BDCT) with several different block-sizes to the test images. Experimental results have demonstrated that the new splicing detection scheme outperforms state-of-the-art methods by a significant margin when applied to the Columbia Image Splicing Detection Evaluation Dataset.

The invention relates to an imaging screen configuring method of a splicing type display screen. The method comprises the steps that (a) configuration parameters comprising the resolution ratios of a plurality of physical splicing units are obtained; (b) a plurality of imaging splicing units corresponding to the physical splicing units respectively are generated according to the obtained configuration parameters, wherein the imaging splicing units with different shape sizes are generated correspondingly through different resolution ratios; (c) the multiple imaging splicing units are arrayed in one splicing zone responding to user operation, and the multiple imaging splicing units which are arrayed in the splicing zone are subjected to wiring; and (d) according to the positions, the shape sizes and wiring of the multiple imaging splicing units in the splicing zone, the video display coordinate and wiring relationship of the multiple physical splicing units is obtained, and accordingly display screen configuration information is generated. According to the method, the splicing units are represented in an imaging mode, the imaging splicing units with different shape sizes are generated correspondingly through different resolution ratios, and accordingly screen configuring operation is visual, quick and convenient.

The invention provides a panoramic auxiliary driving system and method for a large truck. Image collecting and calibrating are respectively conducted through a first camera, a second camera, a third camera, a fourth camera, a fifth camera and a sixth camera, inner parameters and outer parameters of all the cameras are acquired, the collected images are corrected through the inner parameters and the outer parameters, and a mapping model of the collected images and the corrected images is constructed; the collected images are subjected to affine transformation, perspective transformation and zooming transformation to obtain overlook images; the overlook images are subjected to image matching through a speed up robust feature registration algorithm to obtain local feature points; image splicing fusion is conducted according to the local feature points; a panoramic image after splicing is subjected to image processing to obtain a preprocessed panoramic image; a main control processing module conducts barrier detection on the preprocessed panoramic image according to the running state of a vehicle; the main control processing module automatically switches to a one-way camera image or amulti-way camera image according to the state of the vehicle, and early-warning is achieved according to the barrier detection result.

The invention discloses an automatic panorama parking aerial view image splicing method, system and vehicle. According to the method, firstly a pre-designed calibration cloth and a splicing template are utilized, the image skeleton technology is utilized to automatically acquire a cross line center point of camera overlapping regions of adjacent calibration aerial view images, the center point is utilized to splice the calibration aerial view images, and weight adjustment on brightness of a camera overlapping region of one aerial view image is carried out through utilizing a distance between a pixel and a splicing slit according to brightness values of sub images of the camera overlapping regions of the adjacent calibration aerial view images. The splicing method is advantaged in that the method can be automatically realized, splicing precision is relatively high, brightness transformation of the panorama splicing images is natural, the splicing slit is not obvious, the manual splicing time can be shortened, and panorama splicing image quality is improved.