Images with geometrical distortions

which are taken by cameras

must be corrected before being analyzed. According to the normal distortion correction method for distorted images which obtains distortion coefficients by setting up a distortion model

but as the calculation is complicated and numerical error becomes a big problem

a distortion correction method based on neural networks is put forward in this paper. First of all

the sample coordinates which serve as input parameters of neural networks are extracted from a distorted template image by image processing technique. Then the neural networks are trained by samples. The trained neural networks can learn any distortion relationship between the normal image and the distorted image. Experiments are done by the new method in this paper

and the correcting results are given and analyzed. The experimental results show the neural networks distortion correction technique is satisfactory and it is used in the vision system of the welding robot.