南京大学学报：自然科学版2011，Vol.47Issue(4)：438-445,8.
一种基于概率粗糙集模型的图像语义检索方法
An image semantics retrieval method based on probability rough set model
摘要
Abstract
In view of the problem that the present image data contains too much information,not easy to retrieve and people is used to searching the image semantic concept in the process of image retrieval,this paper introduces the probabilistic rough set model and image semantic annotation technology into the image information retrieval and puts out a kind of image information retrieval model based on Nave Bayesian and probability rough set model.Firstly,the images are crisp annotated and weighted fuzzy annotated by Nave Bayesian after building crisp annotation space for the image library information.Secondly,the conditional probability and fuzzy conditional probability are computed for each pair of annotations by combining the posterior probability of Nave Bayesian with the probabilistic rough set model,after that the support set and supported set of each annotation are computed,the upper and lower approximation of each annotation are calculated for the support set and supported set,and the image semantic similarity calculation method is built by the upper and lower approximation,then the semantic similarity between query characteristics and the characteristics of image library is calculated,and the retrieval results are output by ordering according to similarity.Finally,taking the images in Corel image library for an example,the paper give a simple simulation experiment which shows the algorithm is feasible and effective in practice.关键词
概率粗糙集/图像语义/自动标注/朴素贝叶斯Key words
probability rough set/image semantic/automatic annotation/Nave Bayesian分类
信息技术与安全科学引用本文复制引用
徐久成,李晓艳,孙林..一种基于概率粗糙集模型的图像语义检索方法[J].南京大学学报：自然科学版,2011,47(4):438-445,8.基金项目
国家自然科学基金 （）
河南省省教育厅自然科学基金 （）
