04681nas a2200493 a 4500 20260817170922.0 161121s2012 th uu m rtt 0| a1eng d .b12174531 AIT Diss. no.CS-12-05 Bukhari, Faisal Automatic radial distortion estimation from a single image Pathum Thani, Thailand : Asian Institute of Technology, 2012 1 online resource (73 p.) : ill. Dissertation ; no. CS-12-05 A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science, School of Engineering and Technology Thesis (Ph.D.) - Asian Institute of Technology, 2012 Many computer vision algorithms rely on the assumptions of the pinhole camera model, butlens distortion with off-the-shelf cameras is usually significant enough to violate this as-sumption. Many methods for radial distortion estimation have been proposed, but they allhave limitations. Robust automatic radial distortion estimation from a single natural imagewould be extremely useful for many applications, particularly those in human-made envi-ronments containing abundant lines. For example, it could be used in place of an extensivecalibration procedure to get a mobile robot or quadrotor experiment up and running quicklyin an indoor environment.In this dissertation we propose a new and fully automatic method for radial distortion esti-mation based on the plumb-line approach.First, the method works from a single image and does not require a special calibration pattern.It is based on Fitzgibbon{u2019}s division model.Second, we devise a new algorithm for robust estimation of circular arcs.Third, we design and implement a new algorithm for robust estimation of lens distortionparameters based on the estimated circular arcs.Fourth, we perform an extensive empirical study of the method on synthetic images. Wedevelop our own data set for synthetic images under different levels of lambda and distortioncenter.Fifth, we perform a comparative statistical analysis of how different circle fitting methodscontribute to accurate distortion parameter estimation.Sixth, we provide qualitative results on a wide variety of challenging real images. Theexperiments demonstrate the method{u2019}s ability to accurately identify distortion parametersand remove distortion from images. Seventh, we perform a direct comparison of our methodwith that of Alvarez et al. (Alvarez, Gomez, & Sendra, 2009), the only researchers who haveprovided a publicly accessible implementation of their method, on synthetic images.Finally, we provide the source code based on OpenCV (Bradski, 2000) online1for re-searchers interested in evaluating or extending our procedure. Computer vision Image processing Dailey, Mathew N., Chairperson Afzulpurkar, Nitin V., Examination Committee Duboz, Raphael, Examination Committee Higher Education Commission (HEC), Pakistan, Scholarship Donor Asian Institute of Technology Fellowship, Scholarship Donor Asian Institute of Technology. Dissertation ; no. CS-12-05 Full-Text http://203.159.5.9/ait-thesis/detail.php?q=B00292 .b12174531 mnait m 240405 0 161121 m a m 0 000:001:PDF:b1217453:002824:0:0:0:0:0:0 Abstract-AIT Diss. no.CS-12-05 n mnait mnait mnarc mnarc mnarc 20 40 Barcode : 30050120389795 CREATED : 2016-11-21 RECORD # : i13060788 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050120389787 CREATED : 2016-11-21 RECORD # : i1306079x LPATRON : 1015151 LCHKIN : 2019-02-04 # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 1 TOT RENEW : 4 Barcode : 30050120405922 CREATED : 2017-05-04 RECORD # : i13073680 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050120978183 CREATED : 2020-09-17 RECORD # : i13297247 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 Barcode : 30050120978175 CREATED : 2020-09-17 RECORD # : i13297259 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 10225 10225 0 0 0 0 MAIN MAIN mnait 2026-08-17 50.00 0 AIT Diss. no.CS-12-05 30050120389795 2026-08-17 17:09:22 1 2026-08-17 20 0 0 0 0 MAIN MAIN mnait 2026-08-17 50.00 0 AIT Diss. no.CS-12-05 30050120389787 2026-08-17 17:09:22 2 2026-08-17 20 0 0 0 0 MAIN MAIN mnarc 2026-08-17 50.00 0 AIT Diss. no.CS-12-05 30050120405922 2026-08-17 17:09:22 1 2026-08-17 40 0 0 0 0 MAIN MAIN mnarc 2026-08-17 50.00 0 AIT Diss. no.CS-12-05 30050120978183 2026-08-17 17:09:22 3 2026-08-17 20 0 0 0 0 MAIN MAIN mnarc 2026-08-17 50.00 0 AIT Diss. no.CS-12-05 30050120978175 2026-08-17 17:09:22 4 2026-08-17 20