图像检索中一种新的相关反馈机制

A Novel Relevance Feedback Technique for Interactive Content-Based Image Retrieval

1.引言近年来,随着图像数据的大量增加,对图像进行智能化、基于内容的处理愈来愈引起人们的极大兴趣.除了使用手工输入的关键字外(基于文本的方法),其于内容的图像检索(Content-Based Image Retrleval,CBIR)系统也使用图像的视觉特征来建立图像索引,所使用的图像低层特征包括:颜色、纹理和形状等.

Content-based image retrieval systems require the development of relevance feedback mechanism to facilitate the human-computer interaction. In this paper,we propose a grey approach to relevance feedback,where the GRA is used to describe the feature distributions of the images judged relevant by the user and dynamically updates both the similarity measure and the query in order to accurately represent the user's particular information needs. Experimental results show that the proposed approach captures the user's information needs more precisely,and improves the effectiveness of image retrieval considerably.