{"title":"压缩图像的存储和检索","authors":"F. Idris, S. Panchanathan","doi":"10.1109/ICCE.1995.517928","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new technique for the storage and retrieval of compressed images. Here, the images are compressed using vector quantization and the codebook is used to generate a feature vector. This feature vector is used as an index to access the images in the database. This technique combines image compression with image indexing. In addition, it has lower storage and computation requirements compared with other techniques reported in the literature. >","PeriodicalId":306595,"journal":{"name":"Proceedings of International Conference on Consumer Electronics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1995-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"55","resultStr":"{\"title\":\"STORAGE AND RETRIEVAL OF COMPRESSED IMAGES\",\"authors\":\"F. Idris, S. Panchanathan\",\"doi\":\"10.1109/ICCE.1995.517928\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new technique for the storage and retrieval of compressed images. Here, the images are compressed using vector quantization and the codebook is used to generate a feature vector. This feature vector is used as an index to access the images in the database. This technique combines image compression with image indexing. In addition, it has lower storage and computation requirements compared with other techniques reported in the literature. >\",\"PeriodicalId\":306595,\"journal\":{\"name\":\"Proceedings of International Conference on Consumer Electronics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"55\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of International Conference on Consumer Electronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCE.1995.517928\",\"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 International Conference on Consumer Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE.1995.517928","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 technique for the storage and retrieval of compressed images. Here, the images are compressed using vector quantization and the codebook is used to generate a feature vector. This feature vector is used as an index to access the images in the database. This technique combines image compression with image indexing. In addition, it has lower storage and computation requirements compared with other techniques reported in the literature. >
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