Meiping Song, Dongqing Cui, Chunyan Yu, Jubai An, Chein-I. Chang, Meping Song
{"title":"基于多尺度金字塔和改进区域生长的光伏图像裂纹检测算法","authors":"Meiping Song, Dongqing Cui, Chunyan Yu, Jubai An, Chein-I. Chang, Meping Song","doi":"10.1109/ICIVC.2018.8492810","DOIUrl":null,"url":null,"abstract":"Aiming at detecting cracks in photovoltaic images, a crack detection algorithm of photovoltaic images based on multi-scale pyramid and improved region growing is implemented in this paper. Firstly, in order to suppress noise from the crack area, the image is subjected to a filtering process. Then, the multi-scale pyramid is used to extract the fracture characteristics of photovoltaic images on different scales. There are obvious noise disturbances in the extracted cracks that do not conform to the characteristics of the cracks, which can be removed through an optimization process. Finally, this paper focuses on an improved directional region growing algorithm to complement the detected cracks. For comparison, the wavelet modulus maximum method is tested too. The results show that the proposed method has a better performance on noise suppression, suspect crack removing, and crack integrality.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Crack Detection Algorithm for Photovoltaic Image Based on Multi-Scale Pyramid and Improved Region Growing\",\"authors\":\"Meiping Song, Dongqing Cui, Chunyan Yu, Jubai An, Chein-I. Chang, Meping Song\",\"doi\":\"10.1109/ICIVC.2018.8492810\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Aiming at detecting cracks in photovoltaic images, a crack detection algorithm of photovoltaic images based on multi-scale pyramid and improved region growing is implemented in this paper. Firstly, in order to suppress noise from the crack area, the image is subjected to a filtering process. Then, the multi-scale pyramid is used to extract the fracture characteristics of photovoltaic images on different scales. There are obvious noise disturbances in the extracted cracks that do not conform to the characteristics of the cracks, which can be removed through an optimization process. Finally, this paper focuses on an improved directional region growing algorithm to complement the detected cracks. For comparison, the wavelet modulus maximum method is tested too. The results show that the proposed method has a better performance on noise suppression, suspect crack removing, and crack integrality.\",\"PeriodicalId\":173981,\"journal\":{\"name\":\"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIVC.2018.8492810\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIVC.2018.8492810","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Crack Detection Algorithm for Photovoltaic Image Based on Multi-Scale Pyramid and Improved Region Growing
Aiming at detecting cracks in photovoltaic images, a crack detection algorithm of photovoltaic images based on multi-scale pyramid and improved region growing is implemented in this paper. Firstly, in order to suppress noise from the crack area, the image is subjected to a filtering process. Then, the multi-scale pyramid is used to extract the fracture characteristics of photovoltaic images on different scales. There are obvious noise disturbances in the extracted cracks that do not conform to the characteristics of the cracks, which can be removed through an optimization process. Finally, this paper focuses on an improved directional region growing algorithm to complement the detected cracks. For comparison, the wavelet modulus maximum method is tested too. The results show that the proposed method has a better performance on noise suppression, suspect crack removing, and crack integrality.