SURFACE-ROUGHNESS CLASSIFICATION USING PATTERN-RECOGNITION THEORY

被引：6

作者：

SHI, WM ^{[1
]}

LIM, SP ^{[1
]}

LEE, KS ^{[1
]}

机构：

[1] NATL UNIV SINGAPORE,DEPT MECH & PROD ENGN,SINGAPORE 0512,SINGAPORE

来源：

OPTICAL ENGINEERING | 1995年 / 34卷 / 06期

关键词：

SURFACE ROUGHNESS; PATTERN RECOGNITION;

D O I：

10.1117/12.203125

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

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.

引用

页码：1756 / 1760

页数：5

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