Smith, L. and Smith, M.
Automatic machine vision calibration using statistical and neural network methods.
Image and Vision Computing, 23 (10).
Available from: http://eprints.uwe.ac.uk/5967
Full text not available from this repository
Publisher's URL: http://dx.doi.org/10.1016/j.imavis.2005.03.009
|Additional Information:||This work resulted from a more in-depth analysis of an image distortion problem in connection with research into calibration of a vision based metrology system developed by the author for Quantronix. The work went well beyond previous techniques since it does not assume that lens distortion is axis-symmetrical. It is relevant to metrology applications, but can also be applied in any field involving image capture, with a wide angle lens. The paper was listed among the journal's 25 most read articles. The metrology system is now being marketed and installed worldwide. (C Skeen, Quantronix Incorporated, Farmington Utah.)|
|Uncontrolled Keywords:||automatic calibration; radial lens distortion, linear regression, artificial neural network|
|Faculty/Department:||Faculty of Environment and Technology|
R. Upload account
|Deposited On:||22 Jan 2010 15:11|
|Last Modified:||02 Dec 2016 13:13|
Request a change to this item