中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Non-concentric Circular Texture Removal for Workpiece Defect Detection

文献类型:会议论文

作者Qin SJ(秦书嘉)1,3; Guo, Di3; Chen, Heping3
出版日期2019
会议日期August 8-11, 2019
会议地点Shenyang, China
关键词Defect detection Non-concentric circle Small dataset
页码576-584
英文摘要Since workpiece defect detection is a typical problem in computer vision with small datasets, generally its solutions cannot exploit the advantages of high accuracy, generalization ability, and neural network structures from the deep learning paradigm. Thus, traditional image processing techniques are still widely applied in such requirements. Aiming at three types of defects (crack, pitting and scratch) on a workpiece with non-concentric circular textures that severely interfere in the defect recognition stage, this paper proposes a sliding window filter for the texture detection. Experiments compare the proposed method with the polar coordinate mapping method and the T-smooth texture removal algorithm. Results show that the proposed method reveals the three types of defects better than the other two methods.
产权排序1
会议录Intelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings
会议录出版者Springer Verlag
会议录出版地Berlin
语种英语
ISSN号0302-9743
ISBN号978-3-030-27537-2
源URL[http://ir.sia.cn/handle/173321/25501]  
专题沈阳自动化研究所_机器人学研究室
通讯作者Qin SJ(秦书嘉)
作者单位1.Shenyang Institute of Automation, CAS, Shenyang 110000, China
2.The University of Hong Kong, Pok Fu Lam, Hong Kong
3.Shenzhen Academy of Robotics, Shenzhen 518000, China
推荐引用方式
GB/T 7714
Qin SJ,Guo, Di,Chen, Heping. Non-concentric Circular Texture Removal for Workpiece Defect Detection[C]. 见:. Shenyang, China. August 8-11, 2019.

入库方式: OAI收割

来源:沈阳自动化研究所

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