{"title":"基于三阶相关工具的纹理分类","authors":"C. Coroyer, D. Declercq, P. Duvaut","doi":"10.1109/HOST.1997.613510","DOIUrl":null,"url":null,"abstract":"This study presents a new method for textures classification based on higher order statistics (HOS). We propose the use of third order correlation tools for texture analysis. We compare the performance of three different tools: the bicorrelation in the spatial domain, the bispectrum in the frequency domain and the bicorspectrum which is a spatial/frequency representation in that case. We test classification on representative textures of Brodatz album.","PeriodicalId":305928,"journal":{"name":"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Texture classification using third order correlation tools\",\"authors\":\"C. Coroyer, D. Declercq, P. Duvaut\",\"doi\":\"10.1109/HOST.1997.613510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study presents a new method for textures classification based on higher order statistics (HOS). We propose the use of third order correlation tools for texture analysis. We compare the performance of three different tools: the bicorrelation in the spatial domain, the bispectrum in the frequency domain and the bicorspectrum which is a spatial/frequency representation in that case. We test classification on representative textures of Brodatz album.\",\"PeriodicalId\":305928,\"journal\":{\"name\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-07-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HOST.1997.613510\",\"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 IEEE Signal Processing Workshop on Higher-Order Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HOST.1997.613510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Texture classification using third order correlation tools
This study presents a new method for textures classification based on higher order statistics (HOS). We propose the use of third order correlation tools for texture analysis. We compare the performance of three different tools: the bicorrelation in the spatial domain, the bispectrum in the frequency domain and the bicorspectrum which is a spatial/frequency representation in that case. We test classification on representative textures of Brodatz album.
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