A computer vision system for automatic steel surface inspection

Yung Chun Liu, Yu Lu Hsu, Yung Nien Sun, Song Jan Tsai, Chiu Yi Ho, Chung Mei Chen

研究成果: Conference contribution

24 引文 斯高帕斯(Scopus)

摘要

Automatic inspection on line plays an important role in industrial quality management nowadays. This paper proposes a new computer vision system for automatic steel surface inspection. The system analyzes the images sequentially acquired from steel bar to detect different kinds of defects on the steel surface. Several image processing strategies are used to detect and outline the defects. The detected defects are then classified into different defect types by using a hierarchical neural network classifier. Some manual detection results by field experts are used to verify the correctness of the proposed detection. In defect classification, the results show that the relevance vector machine (RVM) has better accuracy than the back propagation neural network (BPN). The proposed algorithm was found capable of detecting defects on steel surface rapidly and precisely.

原文English
主出版物標題Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
頁面1667-1670
頁數4
DOIs
出版狀態Published - 2010
事件5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010 - Taichung, Taiwan
持續時間: 2010 六月 152010 六月 17

出版系列

名字Proceedings of the 2010 5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010

Other

Other5th IEEE Conference on Industrial Electronics and Applications, ICIEA 2010
國家Taiwan
城市Taichung
期間10-06-1510-06-17

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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