Film Defects of Lithium Battery Recognition Based on Brightness and One-against-all Support Vector Machine

被引：1
|
作者：
Chen Gong [1 ]
Zhu Xi Fang [1 ]
Xu Qing Quan [1 ]
Xu An Cheng [1 ]
Yang Hui [1 ]
机构：
[1] Changzhou Inst Technol, Changzhou, Peoples R China
来源：
PROGRESS IN MECHATRONICS AND INFORMATION TECHNOLOGY, PTS 1 AND 2 | 2014年 / 462-463卷
关键词：
Lithium battery; Threshold; Support vector machine; Recognition;
D O I：
10.4028/www.scientific.net/AMM.462-463.155
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Lithium battery film on-line defect recognition system is realized based on industrial charge-coupled device(CCD) to improve quality. Otsu algorithm is adopted for threshold instead of traditional method. Area of defect is sorted to get the largest defect and geometry and projective is extracted from image. Film defects of lithium battery recognition is realized based on Brightness Judgment and One-against-all support vector machine(OAA-SVM). Experiment results show that these methods are effective and feasible, the accuracy can reach 90%.
引用
收藏
页码：155 / 158
页数：4
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