Method for self-adaptation geometric correction of projector picture

Abstract

The invention discloses a method for self-adaptation geometric correction of a projector picture. The method for self-adaptation geometric correction of the projector picture comprises the steps of (1) shooting a projection plane image without a projection picture, (2) projecting a target original image to be corrected on a projection plane to obtain a current projection picture, (3) shooting a projection plane image of the current projection picture, (4) collecting point cloud sample data of the projection plane, (5) obtaining a homography matrix from a camera plane to the projection plane, (6) identifying a frame number which corresponds to the current projection picture, searching for an original projection image corresponding to the current projection picture, (7) obtaining the corresponding relation, between the projection plane image of the currently existing projection picture and the original projection image of the currently existing projection picture about two-dimensional position coordinates with the matching characteristics, obtaining a homography matrix from the projector plane to the camera plane, obtaining a homography matrix from the projector plane to the projection plane, (8) carrying out scale variation processing on a target original image, to be corrected, of a next frame to generate a variation projection image, and (9) projecting the variation projection image on the projection plane to obtain a new current projection picture.

Description

Technical field [0001] The invention relates to a method for adaptive geometric correction of a projector picture, belonging to the technical field of projector picture correction. Background technique [0002] The adaptive geometric correction of the projector image is to automatically correct the projector image according to a specific type of surface information. Bimber proposed to map a two-dimensional P2C texture to the original image in 2005. This texture is also called a communication texture. It contains the coordinates of each pixel in the image and gives it a specific floating-point color value. Calculate the three-dimensional information of the projection surface by detecting the pixel-level displacement of its texture after projection. This purely image content-based embedding method often relies excessively on the information of the image itself, and does not accurately match the three-dimensional information of the projection surface. It is easy to affect the accur...

AI Technical Summary

Problems solved by technology

Later, a method of light and dark differential projection was developed according to the specificity of human vision. Due to the compensation of the human eye for light and dark patterns, the existence of coding cannot be felt, but the camera can capture these light and dark coding information with the help of a certain sampling frequency. , the specific method is to perform differential superposition on the projected image according to the coding to generate two images, one image is positive superposition coding, and the other is negative superposition coding, project these two frames at a specific frequency, and then carry out synchronous calibration of the camera, This method has high requirements on the synchronization of the frame rate of the camera and the frequency of the projector. It is difficult for general hardware to achieve such accuracy, and when the human eye observes the projected screen when it is moving, it can detect the difference between the two images.

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