一种改进的粒子群算法和相关反馈的图像检索

计算机科学 ›› 2011, Vol. 38 ›› Issue (10): 278-280.

一种改进的粒子群算法和相关反馈的图像检索

唐朝霞,章慧,徐冬梅

(淮阴工学院计算机工程学院淮安223003);(东南大学计算机科学与工程学院南京211189)

出版日期:2018-11-16 发布日期:2018-11-16

Image Retrieval Based on Improved PSO Algorithm and Relevance Feedback

TANG Zhao-xia,ZHANG Hui,XU Dong-mei

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 由于图像的低层特征与高层语义之间存在着语义鸿沟，以及用户对图像理解的主观性和易变性，使得基于内容的图像检索结果不能很好地满足用户的需求。为解决这个问题，将粒子群算法和相关反馈引入到图像检索过程中，根据用户的反馈信息，引入二自适应调整和Beta自适应变异的粒子群算法动态调整图像的特征权重，从而提高图像的检索精度，以更好地满足用户的需求。

关键词: 相关反馈，粒子群算法，图像检索

Abstract: Because of semantic gap between low-level image features and high-level semantics, and user understanding image subj ectivity and variability, image retrieval results can not satisfy the needs of users. To solve this problem, PSO algorithm and relevance feedback were introduced into the image retrieval process,based on user feedback, W automatic adjustment and Beta adaptive mutation of PSO adjust the weights of the image feature dynamically, to improve search accuracy,better meet the needs of users.

Key words: Relevance feedback(RF) , Particle swarm optimization(PSO) , Image retrieval

唐朝霞,章慧,徐冬梅. 一种改进的粒子群算法和相关反馈的图像检索[J]. 计算机科学, 2011, 38(10): 278-280. https://doi.org/

TANG Zhao-xia,ZHANG Hui,XU Dong-mei. Image Retrieval Based on Improved PSO Algorithm and Relevance Feedback[J]. Computer Science, 2011, 38(10): 278-280. https://doi.org/

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