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

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.

[1]  Stephen T. Barnard,et al.  Interpreting Perspective Image , 1983, Artif. Intell..

[2]  Matthew N. Dailey,et al.  Robust Radial Distortion from a Single Image , 2010, ISVC.

[3]  Luis Gómez,et al.  Zoom Dependent Lens Distortion Mathematical Models , 2012, Journal of Mathematical Imaging and Vision.

[4]  Christian Bräuer-Burchardt,et al.  Distance Dependent Lens Distortion Variation in 3D Measuring Systems Using Fringe Projection , 2006, BMVC.

[5]  J. Rafael Sendra,et al.  Accurate Depth Dependent Lens Distortion Models: An Application to Planar View Scenarios , 2010, Journal of Mathematical Imaging and Vision.

[6]  C. Fraser,et al.  Variation of distortion within the photographic field , 1992 .

[7]  Sing Bing Kang,et al.  Radial Distortion Snakes , 2001, MVA.

[8]  O. D. Faugeras,et al.  Camera Self-Calibration: Theory and Experiments , 1992, ECCV.

[9]  P.V.C. Hough,et al.  Machine Analysis of Bubble Chamber Pictures , 1959 .

[10]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[11]  P. Nagabhushan,et al.  A simple and robust line detection algorithm based on small eigenvalue analysis , 2004, Pattern Recognit. Lett..

[12]  J. Chris McGlone,et al.  Manual of photogrammetry , 2004 .

[13]  Matthew N. Dailey,et al.  Automatic Radial Distortion Estimation from a Single Image , 2012, Journal of Mathematical Imaging and Vision.

[14]  Duane C. Brown,et al.  Close-Range Camera Calibration , 1971 .

[15]  Aiqi Wang,et al.  A Simple Method of Radial Distortion Correction with Centre of Distortion Estimation , 2009, Journal of Mathematical Imaging and Vision.

[16]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[17]  Chang-Sung Jeong,et al.  A straight line detection using principal component analysis , 2006, Pattern Recognit. Lett..

[18]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[19]  Andrew Zisserman,et al.  Multiple view geometry in computer visiond , 2001 .

[20]  Andrew W. Fitzgibbon,et al.  Simultaneous linear estimation of multiple view geometry and lens distortion , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[21]  J. Rafael Sendra,et al.  An Algebraic Approach to Lens Distortion by Line Rectification , 2009, Journal of Mathematical Imaging and Vision.

[22]  D Gonzalez-Aguilera,et al.  An Automatic Approach for Radial Lens Distortion Correction From a Single Image , 2011, IEEE Sensors Journal.

[23]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[24]  Olivier Faugeras,et al.  Three-Dimensional Computer Vision , 1993 .

[25]  Olivier Faugeras,et al.  Structure from motion using the reconstruction and reprojection technique on noisy and incorrect point matches , 1987 .

[26]  Peter F. Sturm,et al.  Generic self-calibration of central cameras , 2010, Comput. Vis. Image Underst..

[27]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  Olivier D. Faugeras,et al.  Automatic calibration and removal of distortion from scenes of structured environments , 1995, Optics & Photonics.

[29]  Kuo-Liang Chung,et al.  New orientation-based elimination approach for accurate line-detection , 2010, Pattern Recognit. Lett..

[30]  Eric Hayman,et al.  Correcting Radial Distortion by Circle Fitting , 2005, BMVC.

[31]  J. Rafael Sendra,et al.  Algebraic Lens Distortion Model Estimation , 2010, Image Process. Line.