An online calibration method for extrinsic parameters of a monocular camera

Abstract

The invention discloses an on-line calibration system for an external parameter of a monocular camera. The system comprises a straight line detection module, a lane extraction module, a fast-perspective-removal (FPR) module, an optimal value iterative module, and an external parameter output module. The straight line detection module obtains an effective straight line position of an inputted infrared image; the lane extraction module carries out effective straight line searching and determination at a possibly occurring lane position; the FPR module carried out perspective transformation removing on a lane based on an imaging principle; the optimal value iterative module carries out loop iteration to enable a fitness function to be optimized, thereby obtaining an angle with the smallest error relative to a practical value; and the external parameter output module is used for outputting the angle obtained by optimal iteration. No calibration object is needed; the influence on the calibration precision by any external factor can be reduced; dependence on the straight line information of the lane is only needed during the calculation process; the flexibility is high; and on-line calibration on the camera can be realized. Moreover, no control by an external device and no strict experiment condition are needed during the calculation process. The system and method are simple and convenient to realize.

Description

technical field [0001] The invention belongs to the technical field of camera calibration, and relates to an on-line calibration system and method for external parameters of a monocular camera. Background technique [0002] In the process of image measurement and machine vision applications, in order to determine the relationship between the three-dimensional geometric position of a point on the surface of a space object and its corresponding point in the image, a geometric model of camera imaging must be established, and these geometric model parameters are camera parameters. Under most conditions, these parameters must be obtained through experiments and calculations, and this process of solving parameters is called camera calibration (or camera calibration). Whether in image measurement or machine vision applications, the calibration of camera parameters is a very critical link. The accuracy of the calibration results and the stability of the method directly affect the ac...

AI Technical Summary

Problems solved by technology

The three-dimensional calibration object can be calibrated by a single image, and the calibration accuracy is high, but the processing and maintenance of high-precision three-dimensional calibration objects are difficult

However, since it is based on absolute conic curves or surfaces, its method is less robust

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