SURFACE-ROUGHNESS CLASSIFICATION USING PATTERN-RECOGNITION THEORY

Pattern recognition theory is introduced to perform rough surface clas sification. The light intensity distribution scattered from a rough su rface 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 separabilit y, a modified method is proposed. The feasibility and effectiveness of the proposed method is demonstrated by computer simulation results.