期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2014
卷号：11
期号：1
页码：31-33
DOI：10.14445/22312803/IJCTT-V11P107
出版社：Seventh Sense Research Group
摘要：A novel method for automatic annotation of images is used with keywords from a generic vocabulary of concepts or objects combined with annotationbased retrieval of images. This can be done by using spatial hidden Markov model, in which states represent concepts. The parameters of this model are estimated from a set of manually annotated training images. An image in a large test collection is then automatically annotated with the a posteriori probability of the concepts. This annotation supports contentbased search of the imagecollection through keywords. The keyword relevance can be constructed using Aggregate Markov Chain (AMC). A stochastic distance between images based on their annotation and the keyword relevance are captured in the AMC is then introduced. Investigation has been made in the Geometric interpretations of the proposed distance and its relation to a clustering in the keyword space.
