Camera calibration is a key technology in computer vision

in which camera self-calibration technology is to compute the camera's intrinsic parameters from a series of images.Compared to traditional camera calibration methods

the process of self-calibration is simpler and more convenient for application.The self-calibration technology using Kruppa equation not only requires computing the fundamental matrix

but also computing the epipoles of images which are variable with the different images and will result in unstable computation results.GA algorithm is used to complete the self-calibration processing by estimating the new and simple Kruppa equations defined by Hartley.At last

the self-calibration problem is converted into the minimization of the cost function

so that the epipoles instability is eliminated and the calibration effect is improved.Experimental results show that the proposed method is simple and effective

and can become an versatile tool for camera calibration.