基于视觉显著图的彩色图像检索

摘要

为提高图像检索效率,提出一种基于视觉显著图的彩色图像检索方法.利用视觉显著图去除原图中与检索任务无关的背景信息,保留用户感兴趣的图像区域信息,采用小波域的BDIP-BVLC方法提取图像特征,并引入二次查询度量策略进行距离度量.实验结果表明,与基于显著性加权的检索方法相比,该方法的平均查准率较高.%Aiming at the problem of attribute reduction, this paper proposes a new multi-objective particle swarm optimization algorithm which aims at the least reduction of attributes sets and maximum of the dependency of the attributes. It searches best particle based on non-dominated sorting and weighting method. Combining the new motion equation with ε-neighborhood perturbation, the algorithm has strong global and local searching ability. Experimental results with UCI data sets show that the proposed algorithm is more effective than the compared algorithms.