Camera distortion correcting method based on square target model and perspective projection

Abstract

The invention relates to a camera distortion correcting method based on a square target model and perspective projection. According to the method, firstly, a space coordinate system with the center of a camera as an original point is built, the plane equation of a grid point target plane on a camera coordinate system is calculated by the adoption of the square target model according to the coordinates of a target spot in the center of an image; a grid corresponding to the original image is generated on the plane, grid points are projected on an imaging plane, and ideal grid points are formed; according to the one-to-one correspondence relation between the grid points of the original image and the ideal grid points, interpolation is carried out in the image in a blocking mode, and each pixel on the original image is corrected to be at the ideal position. Compared with the prior art, a distortion model is not used, the computing process is simple, and the image distortion caused by errors of camera components and assembly is well overcome.

Description

technical field [0001] The invention relates to a method for correcting geometric distortion of an industrial fixed-focus camera image, in particular to a method for correcting camera distortion based on a square target model and perspective projection. Background technique [0002] Due to the physical nonlinear characteristics of the camera lens, it is inevitable to cause distortion of the shape of the object on the image during the imaging process. This geometric distortion not only affects the visual effect of the collected images, but if it is directly applied to industrial close-range measurement, it will reduce the measurement accuracy of the camera and adversely affect the results. There are still various errors in the camera's component processing and lens assembly process, which will also aggravate the geometric distortion of the image. Ordinary industrial cameras are low in cost and easy to use, but there are disadvantages such as large distortion and serious geom...

AI Technical Summary

Problems solved by technology

The disadvantage of the geometric distortion model is that the three distortion parameters are coupled with each other, and the model is complex, which brings a large computational workload and cannot overcome the distortion caused by assembly errors.

This method of image correction can solve the distortion caused by components or assembly errors. It only uses the principle of perspective projection and does not consider the physical source of distortion. The method has high accuracy, but the calibration process and principle are more complicated, and the accuracy also depends on the calibration object. production quality of

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