计算机工程Issue(6)：188-194,200,8.DOI:10.3969/j.issn.1000-3428.2015.06.034
基于混合引力搜索的自适应特征提取算法
Adaptive Feature Extraction Algorithm Based on Hybrid Gravity Search
摘要
Abstract
A new algorithm with adaptive feature extraction and feature selection simultaneously is proposed to improve the performance of Content-based Image Retrieval( CBIR) . Semantic gap between low-level visual features and high-level semantic information is reduced by synchronization in feature extraction and feature selection. A parameterized wavelet is used to improve accuracy of image details. Mother wavelet function of color histogram feature is optimized and interval parameters are quantified using multiple gravity search algorithm. Experimenal results on 1 000 images searched by Corel show that compared with the most relevant algorithm, fusion algorithm of Gravitational Search Algorithm and Support Vector Machine(GSA-SVM),fusion algorithm of Fuzzy Color Histogram and Fuzzy String Matching(FCH-FSM),the retrieval accuracy is higher,and the and average time consumption is less.关键词
图像检索/特征提取/离散小波变换/引力搜索算法/模糊颜色直方图Key words
image retrieval/feature extraction/Discrete Wavelet Transform(DWT)/Gravitational Search Algorithm(GSA)/Fuzzy Color Histogram( FCH)分类
信息技术与安全科学引用本文复制引用
易唐唐,黄立宏..基于混合引力搜索的自适应特征提取算法[J].计算机工程,2015,(6):188-194,200,8.基金项目
国家科技支撑计划基金资助项目(2012BAH08B00) （2012BAH08B00）
湖南省教育厅科学研究基金资助青年项目(12B066)。 （12B066）
