摘要
基于相关反馈的图像检索算法,加权系数的调整预先确定,缺乏灵活性。为了获得满意的检索结果,需要大量的反馈计算且算法效率低。针对相关反馈的缺点,提出一种基于粒子编码的加权系数自适应调整算法,并且给出了粒子编码的过程与适应度函数的计算过程。选择Corel标准图片库进行实验,基于粒子编码的算法比其他相关反馈算法检索精度大大提高。
Weighted coefficient of image retrieval algorithm based on relevance feedback are determined in advance,which is lack of flexibility.In order to obtain satisfactory retrieval results,this algorithm requires a large amount of feedback calculation and the algorithm efficiency is low.Aiming at the faults of relevance feedback,the adaptive adjustment algorithm of weighting coefficients based on particle encoding is presented.The particle encoding process and fitness function calculation process is worked out.The result of experiment using the Corel standard library,shows that particle coding algorithm greatly improves the retrieval accuracy than other relevance feedback algorithms.
出处
《科技通报》
北大核心
2013年第2期50-52,共3页
Bulletin of Science and Technology
基金
山东省职业教育与成人教育研究所项目(2010zcj216)
关键词
相关反馈
粒子群
检索精度
自适应权值调整
relevance feedback
particle swarm
retrieval accuracy
adaptive weight adjustment
