{"title":"Gabor空间中的复矩几何图像基元及其在纹理分割中的应用","authors":"J. Bigün, J. D. Buf","doi":"10.1109/CVPR.1992.223118","DOIUrl":null,"url":null,"abstract":"An approach to image feature extraction is proposed. Complex moments of the Gabor power spectrum are used to detect linear, rectangular, hexagonal/triangular, and other structures with very fine to very coarse resolutions. When the method is applied to texture segmentation, good results are obtained.<<ETX>>","PeriodicalId":325476,"journal":{"name":"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Geometric image primitives by complex moments in Gabor space and the application to texture segmentation\",\"authors\":\"J. Bigün, J. D. Buf\",\"doi\":\"10.1109/CVPR.1992.223118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An approach to image feature extraction is proposed. Complex moments of the Gabor power spectrum are used to detect linear, rectangular, hexagonal/triangular, and other structures with very fine to very coarse resolutions. When the method is applied to texture segmentation, good results are obtained.<<ETX>>\",\"PeriodicalId\":325476,\"journal\":{\"name\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CVPR.1992.223118\",\"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 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.1992.223118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Geometric image primitives by complex moments in Gabor space and the application to texture segmentation
An approach to image feature extraction is proposed. Complex moments of the Gabor power spectrum are used to detect linear, rectangular, hexagonal/triangular, and other structures with very fine to very coarse resolutions. When the method is applied to texture segmentation, good results are obtained.<>