【摘要】 图像低层视觉特征和高层语义间的"语义鸿沟"是图像检索的关键问题。为了进一步提高基于语义的图像检索系统工作效率,以分块权值和视觉词库为基础,结合图像低层特征和高层语义的相关性,提出了一种基于分块权值的语义图像模型,该模型用来反映图像的视觉特性,对图像的高层语义进行有效检测,从而提高语义图像的检索效率。实验结果表明,该方法提高了语义图像检索系统的查全率和查准率。更多还原

【Abstract】 The semantic gap between low-level visual feature and high-level semantic has become a primary problem.For improving the efficiency of semantic-based image retrieval system,this paper based on chunked weight and a visual vocabulary proposed a semantic image model which utilizes the correlation of low-level feature and high-level semantic.The model is used to interpret the image visual characteristic and detecte high-level semantic,which improves the efficiency of the semantic image retrieval.The experimental results show that this method improves the precision and recall of semantic image retrieval system.更多还原