Haiyong Chen, Xiaofang Zhang, Jiali Liu, Huifang Zhao, Peng Yang
{"title":"Robust Visual Detection for Vague Scratches defect in inhomogeneous surface","authors":"Haiyong Chen, Xiaofang Zhang, Jiali Liu, Huifang Zhao, Peng Yang","doi":"10.23919/IConAC.2018.8749054","DOIUrl":null,"url":null,"abstract":"Scratch inspection has become a challenging problem in the detection of multicrystalline solar cells surface quality because the scratches in inhomogeneous textured surfaces are usually shallow and weak. Thus, this paper presents a novel framework for detecting vague scratches in the complex inhomogeneous surface texture of multicrystalline solar cell. Firstly, an enhanced texture energy measure is used for highlighting candidate scratch defcects information, and simultaneously suppressing inhomogeneous surface texture information. Then, a robust structural-texture decomposition method with an adaptive parameter is employed to capture the meaningful structure information from the enhanced image. Futheremore, an optimal threshold from a Otsu's threshold segmentation method is used to distinguish defect from the background. Finally, some experimental results have shown the proposed method can effectively detecte vague scratches in multicrystalline solar cell surface.","PeriodicalId":121030,"journal":{"name":"2018 24th International Conference on Automation and Computing (ICAC)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 24th International Conference on Automation and Computing (ICAC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/IConAC.2018.8749054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Scratch inspection has become a challenging problem in the detection of multicrystalline solar cells surface quality because the scratches in inhomogeneous textured surfaces are usually shallow and weak. Thus, this paper presents a novel framework for detecting vague scratches in the complex inhomogeneous surface texture of multicrystalline solar cell. Firstly, an enhanced texture energy measure is used for highlighting candidate scratch defcects information, and simultaneously suppressing inhomogeneous surface texture information. Then, a robust structural-texture decomposition method with an adaptive parameter is employed to capture the meaningful structure information from the enhanced image. Futheremore, an optimal threshold from a Otsu's threshold segmentation method is used to distinguish defect from the background. Finally, some experimental results have shown the proposed method can effectively detecte vague scratches in multicrystalline solar cell surface.