{"title":"基于LSH改进的剪纸图像检索技术","authors":"Xintong Liu, Huaxiong Zhang","doi":"10.2991/ICMEIT-19.2019.37","DOIUrl":null,"url":null,"abstract":"Characteristics of paper-cutting, paper-cutting gallery construction, etc. are analyzed aiming at existing problems of folk traditional paper-cutting art multimedia interactive platform. It is proposed that rotation invariant LBP (Local Binary Pattern) is combined with LSH algorithm to present a large-scale paper-cutting image fast retrieval method. Firstly, the background image is eliminated with OTSU, then the paper-cutting image rotation LBP feature. In addition, highdimensional data is mapped to low dimensional space, and a hash index was constructed by local sensitive hash algorithm to find the approximate KNN. Experimental result in the dataset shows that the improved algorithm has high accuracy on paper-cutting image retrieval, and it is significantly higher than traditional algorithm on retrieval speed.","PeriodicalId":223458,"journal":{"name":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Paper-cutting Image Retrieval Technology based on LSH Improvement\",\"authors\":\"Xintong Liu, Huaxiong Zhang\",\"doi\":\"10.2991/ICMEIT-19.2019.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Characteristics of paper-cutting, paper-cutting gallery construction, etc. are analyzed aiming at existing problems of folk traditional paper-cutting art multimedia interactive platform. It is proposed that rotation invariant LBP (Local Binary Pattern) is combined with LSH algorithm to present a large-scale paper-cutting image fast retrieval method. Firstly, the background image is eliminated with OTSU, then the paper-cutting image rotation LBP feature. In addition, highdimensional data is mapped to low dimensional space, and a hash index was constructed by local sensitive hash algorithm to find the approximate KNN. Experimental result in the dataset shows that the improved algorithm has high accuracy on paper-cutting image retrieval, and it is significantly higher than traditional algorithm on retrieval speed.\",\"PeriodicalId\":223458,\"journal\":{\"name\":\"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2991/ICMEIT-19.2019.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/ICMEIT-19.2019.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Paper-cutting Image Retrieval Technology based on LSH Improvement
Characteristics of paper-cutting, paper-cutting gallery construction, etc. are analyzed aiming at existing problems of folk traditional paper-cutting art multimedia interactive platform. It is proposed that rotation invariant LBP (Local Binary Pattern) is combined with LSH algorithm to present a large-scale paper-cutting image fast retrieval method. Firstly, the background image is eliminated with OTSU, then the paper-cutting image rotation LBP feature. In addition, highdimensional data is mapped to low dimensional space, and a hash index was constructed by local sensitive hash algorithm to find the approximate KNN. Experimental result in the dataset shows that the improved algorithm has high accuracy on paper-cutting image retrieval, and it is significantly higher than traditional algorithm on retrieval speed.