节点文献
一种由低层视觉特征获取高层语义的图像检索方法
An Image Retrieval Method of Getting the High-level Semantics from the Low-level Features
【摘要】 提出了一种在获取图像低层视觉特征(颜色)的基础上,利用语义网络对图像进行语义自动分类,从而建立起低层视觉特征和高层语义特征之间的联系的算法。最后,为了提高检索效率,引进相关反馈技术,实验证明这种方法是行之有效的。
【Abstract】 This paper presents results of a project that seeks to transform the low level features to high level of meaning. It extracts the low level features called as the representative colors from the images, and presents a new approach called word net to establish the link from the low- level feature vectors to the semantics. In order to improve the retrieval efficiency, the relevance feedback is also applied into the system. Experiments show the method is promising.
【关键词】 主颜色;
语义网络;
图像语义;
相关反馈;
【Key words】 Representative color; Word net; Image semantics; Relevance feedback;
【Key words】 Representative color; Word net; Image semantics; Relevance feedback;
【基金】 国防科工委基金资助项目
- 【文献出处】 计算机工程 ,Computer Engineering , 编辑部邮箱 ,2005年01期
- 【分类号】TP391.3
- 【被引频次】17
- 【下载频次】349