Special Section on Advances of Precision Optical Measurements and Instrumentation for Geometrical and Mechanical Quantities

Surface roughness extraction based on Markov random field model in wavelet feature domain

[+] Author Affiliations
Lei Yang

Hefei University of Technology, School of Instrument Science and Opto-electronics Engineering, 193 Tunxi Road, Hefei, 230009 China

Li-qiao Lei

Hefei University of Technology, School of Instrument Science and Opto-electronics Engineering, 193 Tunxi Road, Hefei, 230009 China

Opt. Eng. 53(12), 122414 (Sep 09, 2014). doi:10.1117/1.OE.53.12.122414
History: Received March 30, 2014; Revised August 20, 2014; Accepted August 21, 2014
Text Size: A A A

Abstract.  Based on the computer texture analysis method, a new noncontact surface roughness measurement technique is proposed. The method is inspired by the nonredundant directional selectivity and highly discriminative nature of the wavelet representation and the capability of the Markov random field (MRF) model to capture statistical regularities. Surface roughness information contained in the texture features may be extracted based on an MRF stochastic model of textures in the wavelet feature domain. The model captures significant intrascale and interscale statistical dependencies between wavelet coefficients. To investigate the relationship between the texture features and surface roughness Ra, a simple research setup, which consists of a charge-coupled diode camera without a lens and a diode laser, was established, and the laser speckle texture patterns are acquired from some standard grinding surfaces. The research results have illustrated that surface roughness Ra has a good monotonic relationship with the texture features of the laser speckle pattern. If this measuring system is calibrated with the surface standard samples roughness beforehand, the surface roughness actual value Ra can be deduced in the case of the same material surfaces ground at the same manufacture conditions.

Figures in this Article
© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Lei Yang and Li-qiao Lei
"Surface roughness extraction based on Markov random field model in wavelet feature domain", Opt. Eng. 53(12), 122414 (Sep 09, 2014). ; http://dx.doi.org/10.1117/1.OE.53.12.122414


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.