Surface roughness classification using pattern recognition theory

Wei Min Shi; Siak-Piang Lim; Kim Seng Lee

doi:10.1117/12.203125

1 June 1995 Surface roughness classification using pattern recognition theory

Wei Min Shi, Siak-Piang Lim, Kim Seng Lee

Author Affiliations +

Optical Engineering, Vol. 34, Issue 6, (June 1995). https://doi.org/10.1117/12.203125

Abstract

Pattern recognition theory is introduced to perform rough surface classification. The light intensity distribution scattered from a rough surface is defined as the pattern vector of the rough surface. Using the Karhunen-Loeve transformation, the pattern vector is transformed into a feature vector for classification. To achieve a maximum separability, a modified method is proposed. The feasibility and effectiveness of the proposed method is demonstrated by computer simulation results.

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Wei Min Shi, Siak-Piang Lim, and Kim Seng Lee "Surface roughness classification using pattern recognition theory," Optical Engineering 34(6), (1 June 1995). https://doi.org/10.1117/12.203125

Published: 1 June 1995

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