Camera Calibration Based on Optimized RBF-DDA Neural Networks

Abstract

This paper presents an algorithm of dynamic decay adjustment RBF neural networks which can adaptively get the number of the hidden layer nodes,the center values of Gaussian function and the width of RBF.The neural networks overcome the difficulty of fixing parameters in the former neural networks.The experimental results show that this algorithm is effective.Then it is applied into camera calibration.It doesn’t require an accurate mathematical model and compensates for the nonlinear distortion of camera,which makes the outcome more accurate.The experimental results show that this neural network calibration can obtain high accuracy and it is used in the robot curve tracking successfully.