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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