基于贝叶斯决策的图像检索相关反馈方法研究

为了有效解决基于内容图像检索中“语义鸿沟”问题，利用贝叶斯决策理论估计图像检索中相关图像集与不相关图像集合的分类面，通过移动查询点的策略，指导新一轮的查询，将查询点移向好的范例点而远离坏的范例点。试验证明该方法是一种有效的基于统计分析的反馈方法。

An Image Retrieval Relevance Feedback Algorithm Based on Bayesian Decision Theory

As an effective solution to the ＂Semantic gap＂ problem in content based image re- trieval , a new relevance feedback approach is proposed. The Bayesian decision theory is used to estimate the boundary between relevant and non-relevant images. Then a new query is computed whose neighborhood is likely to fall in a region of the feature space containing relevant images. It is a kind of query shifting method. Experimental results show that the method is an effective relevance feedback method.