Automatic machine vision calibration using statistical and neural network methods

Smith, L. and Smith, M. (2005) Automatic machine vision calibration using statistical and neural network methods. Image and Vision Computing, 23 (10). pp. 887-899. ISSN 0262-8856

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Publisher's URL: http://dx.doi.org/10.1016/j.imavis.2005.03.009


Item Type:Article
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
ID Code:5967
Deposited By: R. Upload account
Deposited On:22 Jan 2010 15:11
Last Modified:10 Feb 2014 16:44

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