A vision system with automatic learning capability for industrial parts inspection

J. Lin, Wen-Hsiang Tsai , Jeunn Shenn Lee, Chai Hsiung Chen

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

A vision system for automated parts inspection is proposed. The system is equipped with learning capabilities such that it automatically selects from a set of sample parts a minimum, but effective inspection region within the camera's field of view for parts discrimination. A binary template is formed within the inspection region which is then used for parts inspection by template matching. The inspection speed is enhanced by keeping the inspection region small and by making the matching task uncomplicated. A simple learning algorithm based on statistical pattern recognition theory is employed, which only requires the system to be taught by a training set of good and defective parts without specific defect identification or location. The system is applicable to most 2-D industrial parts inspection.

原文English
主出版物標題Proceedings - 1984 IEEE International Conference on Robotics and Automation, ICRA 1984
發行者Institute of Electrical and Electronics Engineers Inc.
頁面417-425
頁數9
ISBN(列印)081860526X
DOIs
出版狀態Published - 1 1月 1984
事件1st IEEE International Conference on Robotics and Automation, ICRA 1984 - Atlanta, United States
持續時間: 13 3月 198415 3月 1984

出版系列

名字Proceedings - IEEE International Conference on Robotics and Automation
ISSN(列印)1050-4729

Conference

Conference1st IEEE International Conference on Robotics and Automation, ICRA 1984
國家/地區United States
城市Atlanta
期間13/03/8415/03/84

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