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
收藏
页码：1756 / 1760
页数：5
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