Line detection in images showing significant lens distortion and application to distortion correction

• A new Hough space which includes the distortion parameter is proposed.
• Lines are automatically detected in images with significant radial lens distortion.
• Distortion is corrected using the information provided by the distorted lines.

Lines are one of the basic primitives used by the perceptual system to analyze and interpret a scene. Therefore, line detection is a very important issue for the robustness and flexibility of Computer Vision systems. However, in the case of images showing a significant lens distortion, standard line detection methods fail because lines are not straight. In this paper we present a new technique to deal with this problem: we propose to extend the usual Hough representation by introducing a new parameter which corresponds to the lens distortion, in such a way that the search space is a three-dimensional space, which includes orientation, distance to the origin and also distortion. Using the collection of distorted lines which have been recovered, we are able to estimate the lens distortion, remove it and create a new distortion-free image by using a two-parameter lens distortion model. We present some experiments in a variety of images which show the ability of the proposed approach to extract lines in images showing a significant lens distortion.