摘要
探讨如何将LSI技术应用于图像检索中 ,以实现基于语义的图像检索的技术途径 .给出了一种新的图像索引方法 ,它使用灰色模型GM (1,1)对图像的像素值进行模型化处理 ,并且使用模型参数的概率分布来描述图像 .在此基础上 ,详细讨论了将隐含语义索引技术应用于图像检索中的具体方法 ,并给出了相应的算法 .最后 。
Latent Semantic Indexing (LSI) is a new and promising technique for information retrieval, which has been successfully used for document process and retrieval domains. Within the limits of our knowledge of publish work, only a few papers are concerned with the LSI technique for content based image retrieval. In this paper, the approach to semantic image retrieval using the LSI technique is investigated. A novel image indexing method is introduced, which uses the grey model GM(1,1) and Hilbert space filling curve to model the pixels in an image, and uses the distribution of the GM(1,1) parameters as the image representation. The method to LSI based image retrieval is discussed in detail, and the corresponding algorithms are given. The experimental results are reported and the future work is presented.
出处
《华中科技大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2002年第2期105-107,共3页
Journal of Huazhong University of Science and Technology(Natural Science Edition)
基金
湖北省教育厅重点研究项目 (99A10 8)
