Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Objective speckle pattern-based surface roughness measurement using matrix factorization

Not Accessible

Your library or personal account may give you access

Abstract

A method for the measurement of profile parameters of both isotropic and anisotropic surfaces is presented using the objective laser speckle imaging technique. The surface parameters are characterized in terms of a singular value decomposition method-based metric derived from the initial key contributing singular values of the speckle pattern. A simulation study is performed with random Gaussian anisotropic surfaces generated as a function of the correlation lengths in both $x$ and $y$ directions. In the experimental demonstration, the proposed method is verified with metallic samples having distinct surface roughness processed through widely used machining operations viz., vertical milling, and grinding. A brief discussion about the extent to which the minimum number of singular values that are sufficient to evaluate the profile parameters in the context of experimental results is provided. The method supports the measurement of profile parameters of higher magnitude in the realm of non-contact topographic measurement techniques. The experimental results substantiate the practical applicability of the proposed method.

© 2022 Optica Publishing Group

Full Article  |  PDF Article
More Like This
Grinding surface roughness measurement based on the co-occurrence matrix of speckle pattern texture

Rong-Sheng Lu, Gui-Yun Tian, Duke Gledhill, and Steve Ward
Appl. Opt. 45(35) 8839-8847 (2006)

Surface roughness measurement using dichromatic speckle pattern: an experimental study

Hitoshi Fujii and John W. Y. Lit
Appl. Opt. 17(17) 2690-2694 (1978)

Surface roughness measurements by means of polychromatic speckle patterns

C. T. Stansberg
Appl. Opt. 18(23) 4051-4060 (1979)

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (13)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (1)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (12)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.