Many computer vision algorithms assume a pinhole camera model, but commercial and off-the-shelf cameras usually exhibit enough lens distortion to violate this model. There are many methods that have been proposed to estimate radial lens distortions, each of which has specific limitations. A novel method is therefore proposed in this thesis to estimate and correct for image radial distortion. The solution is based upon an algebraic expansion of the homographic relationship between a planar pattern and its distorted projection into a single image, which is solved using the Direct Linear Transformation. The proposed method requires ten point correspondences, is fully automatic and estimates both the first two parameters of the radial lens distortion division model, and the center of distortion. Experimental results show the method to be general and practical, and more accurate than other recent one- and twoparameter point correspondence-based and plumb line-based approaches.