MULTISPECTRAL CAMERA DYNAMIC STEREO CALIBRATION ALGORITHM BASED ON SALIENCY FEATURES

    公开(公告)号:US20220028043A1

    公开(公告)日:2022-01-27

    申请号:US17284394

    申请日:2020-03-05

    Abstract: A multispectral camera dynamic stereo calibration algorithm is based on saliency features. The joint self-calibration method comprises the following steps: step 1: conducting de-distortion and binocular correction on an original image according to internal parameters and original external parameters of an infrared camera and a visible light camera. Step 2: Detecting the saliency of the infrared image and the visible light image respectively based on a histogram contrast method. Step 3: Extracting feature points on the infrared image and the visible light image. Step 4: Matching the feature points extracted in the previous step. Step 5: judging a feature point coverage area. Step 6: correcting the calibration result. The present invention solves the change of a positional relationship between an infrared camera and a visible light camera due to factors such as temperature, humidity and vibration.

    DISPARITY IMAGE FUSION METHOD FOR MULTIBAND STEREO CAMERAS

    公开(公告)号:US20220207776A1

    公开(公告)日:2022-06-30

    申请号:US17604288

    申请日:2020-03-05

    Abstract: A disparity image fusion method for multiband stereo cameras belongs to the field of image processing and computer vision. The method obtains pixel disparity confidence information by using the intermediate output of binocular disparity estimation. The confidence information can be used to judge the disparity credibility of the position and assist disparity fusion. The confidence acquisition process makes full use of the intermediate output of calculation, and can be conveniently embedded into the traditional disparity estimation process, with high calculation efficiency and simple and easy operation. In the disparity image fusion method for multiband stereo cameras proposed by the method, the disparity diagrams participating in the fusion are obtained according to the binocular images of the corresponding bands, which makes full use of the information of each band and simultaneously avoiding introducing uncertainty and errors.

    METHOD FOR FULLY AUTOMATICALLY DETECTING CHESSBOARD CORNER POINTS

    公开(公告)号:US20220148213A1

    公开(公告)日:2022-05-12

    申请号:US17442937

    申请日:2020-03-05

    Abstract: The present invention discloses a method for fully automatically detecting chessboard corner points, and belongs to the field of image processing and computer vision. Full automatic detection of chessboard corner points is completed by setting one or a plurality of marks with colors or certain shapes on a chessboard to mark an initial position, shooting an image and conducting corresponding processing, using a homography matrix H calculated by initial pixel coordinates of a unit grid in a pixel coordinate system and manually set world coordinates in a world coordinate system to expand outwards, and finally spreading to the whole chessboard region. The method has the advantages of simple procedure and easy implementation; the principle of expanding outwards by a homography matrix is used, so that the running speed of the algorithm is fast; and the corner points obtained by a robustness enhancement algorithm is more accurate, so that the situation of inaccurate corner point detection in the condition of complex illumination is avoided.

    ELLIPSE DETECTION ACCELERATION METHOD BASED ON GENERALIZED PASCAL MAPPING

    公开(公告)号:US20220335639A1

    公开(公告)日:2022-10-20

    申请号:US17437234

    申请日:2021-03-05

    Abstract: The present invention relates to the technical field of digital image processing, and provides an ellipse detection acceleration method based on generalized Pascal mapping. The method comprises: step 100, extracting accurate edge points from a real image by means an edge detection method of an ellipse detection method, connecting edge points into arcs, and taking a de-noised arc set as input of an ellipse detection acceleration method; step 200, screening out a valid candidate arc combinations probably belonging to the same ellipse from the arc set input in step 100; step 300, calculating five parameters of a candidate ellipse; repeating step 200 to step 300 until all valid candidate arc combinations in the arc set and corresponding candidate ellipses are found; and step 400, clustering and verifying candidate ellipse sets, obtaining a final detected ellipse set.

    METHOD FOR INFRARED SMALL TARGET DETECTION BASED ON DEPTH MAP IN COMPLEX SCENE

    公开(公告)号:US20220174256A1

    公开(公告)日:2022-06-02

    申请号:US17442967

    申请日:2020-03-05

    Abstract: The present invention discloses a method for infrared small target detection based on a depth map in a complex scene, and belongs to the field of target detection. An infrared image is collected, the image is binarized by using priori knowledge of a to-be-detected target and adopting a pixel value method, the binary image is further limited based on deep priori knowledge, then static and dynamic scoring strategies are formulated to score a candidate connected component in the morphologically processed image, and an infrared small target in a complex scene is detected finally. The method can screen out targets within a specific range, has high reliability; has strong robustness; is simple in program and easy to implement, can be used in sea, land, and air, and has a significant advantage under a complex jungle background.

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