{"title":"基于SIFT描述符的木材图像检索","authors":"Shaoli Huang, C. Cai, Yang Zhang","doi":"10.1109/CISE.2009.5365099","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new representation and matching scheme for wood image retrieval using Scale Invariant Feature Transformation (SIFT). We extract SIFT feature points in scale space and perform matching based on the texture information around the feature points using SIFT feature operator. This scheme can be appended to most existing wood image retrieval systems and improve their retrieval accuracy and efficiency. Experimental results demonstrate that the performance of this scheme is efficient and stable enough for wood image retrieval technique.","PeriodicalId":135441,"journal":{"name":"2009 International Conference on Computational Intelligence and Software Engineering","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Wood Image Retrieval Using SIFT Descriptor\",\"authors\":\"Shaoli Huang, C. Cai, Yang Zhang\",\"doi\":\"10.1109/CISE.2009.5365099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new representation and matching scheme for wood image retrieval using Scale Invariant Feature Transformation (SIFT). We extract SIFT feature points in scale space and perform matching based on the texture information around the feature points using SIFT feature operator. This scheme can be appended to most existing wood image retrieval systems and improve their retrieval accuracy and efficiency. Experimental results demonstrate that the performance of this scheme is efficient and stable enough for wood image retrieval technique.\",\"PeriodicalId\":135441,\"journal\":{\"name\":\"2009 International Conference on Computational Intelligence and Software Engineering\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Computational Intelligence and Software Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISE.2009.5365099\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Computational Intelligence and Software Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISE.2009.5365099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, we propose a new representation and matching scheme for wood image retrieval using Scale Invariant Feature Transformation (SIFT). We extract SIFT feature points in scale space and perform matching based on the texture information around the feature points using SIFT feature operator. This scheme can be appended to most existing wood image retrieval systems and improve their retrieval accuracy and efficiency. Experimental results demonstrate that the performance of this scheme is efficient and stable enough for wood image retrieval technique.