An evaluation method for the segmentation of ferrograph image based on grey relational analysis

被引：0

作者：

Wang, Jingqiu ^{[1
]}

Xia, Min ^{[1
]}

Wang, Xiaolei ^{[1
]}

机构：

[1] Nanjing Univ Aeronaut & Astronaut, Coll Mech & Elect Engn, Jiangsu Key Lab Precis & Micromfg Technol, Nanjing, Jiangsu, Peoples R China

来源：

2014 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE, ELECTRONICS AND ELECTRICAL ENGINEERING (ISEEE), VOLS 1-3 | 2014年

关键词：

ferrograph image; grey relational analysis; image segmentation; segmentation evaluation; WEAR PARTICLES; CLASSIFICATION;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The segmentation of ferrograph image is one of the important steps of the intelligent ferrography analysis, which will influences the results of the subsequent wear particle recognition and fault diagnosis. In order to improve the accuracy of particle segmentation, a new evaluation method on the segmentation quality of ferrograph image is put forward based on grey relational analysis. This method evaluates the qualities of segmentation results of wear particles using the color ratio parameters in RGB and CIELAB color space. The experimental results show that this method can automatically evaluate segmentation quality with high precision.

引用

页码：701 / 705

页数：5

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