Lens distortion correction method based on cross-ratio invariability and compressed sensing

Dingfei Jin; Yue Yang; Yiping Luo; Sisi Liu

doi:10.1117/1.OE.57.5.054103

10 May 2018 Lens distortion correction method based on cross-ratio invariability and compressed sensing

Dingfei Jin, Yue Yang, Yiping Luo, Sisi Liu

Author Affiliations +

Optical Engineering, Vol. 57, Issue 5, 054103 (May 2018). https://doi.org/10.1117/1.OE.57.5.054103

Abstract

Optical lens distortions will seriously affect the measurement accuracy of the vision system. An independent lens distortion correction method based on cross-ratio invariability and compressed sensing is, thus, proposed to improve the measurement accuracy of the system. A virtual distortion correction template is designed according to the characteristics of the lens distortion. The ideal projection coordinate in the imaging plane of the camera and the distortion correction value of the characteristic points in the virtual correction template can be calculated based on the four-point cross-ratio invariance principle. The ideal projection coordinate of the other pixels in the image can then be reconstructed based on compressed sensing theory and, thus, correcting the distortion of all pixels. The experimental results show that for the same vision measurement system, when the independent distortion correction algorithm is used, its measurement accuracy is significantly improved, and the maximum error is only 0.069 mm. This method can correct the distortion effectively, thus improving the precision of the system.

Citation Download Citation

Dingfei Jin, Yue Yang, Yiping Luo, and Sisi Liu "Lens distortion correction method based on cross-ratio invariability and compressed sensing," Optical Engineering 57(5), 054103 (10 May 2018). https://doi.org/10.1117/1.OE.57.5.054103

Received: 9 January 2018; Accepted: 16 April 2018; Published: 10 May 2018

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available