基于SVM改进的图像反馈检索方法研究

宋冬慧; 马晓楠; 王冲

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基于SVM改进的图像反馈检索方法研究

更新时间：2026-09-04

- 基于SVM改进的图像反馈检索方法研究
- Research on Image Feedback Retrieval Method Based on Improving SVM
- 微电子学与计算机 2018年35卷第4期页码：79-83
- 作者机构：
  
  桂林电子科技大学机构计算机与信息安全学院,广西,桂林,541004
- 作者简介：
- 基金信息：
  
  广西可信软件重点实验室项目 PF14071X广西教改工程项目 C66JWA13SX07
- DOI：
  中图分类号：
- 纸质出版：2018
- 稿件说明：
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宋冬慧, 马晓楠, 王冲. 基于SVM改进的图像反馈检索方法研究[J]. 微电子学与计算机, 2018, 35(4): 79-83, 88.

SONG Dong-hui, MA Xiao-nan, WANG Chong. Research on Image Feedback Retrieval Method Based on Improving SVM[J]. 2018, 35(4): 79-83.
宋冬慧, 马晓楠, 王冲. 基于SVM改进的图像反馈检索方法研究[J]. 微电子学与计算机, 2018, 35(4): 79-83, 88. DOI：

SONG Dong-hui, MA Xiao-nan, WANG Chong. Research on Image Feedback Retrieval Method Based on Improving SVM[J]. 2018, 35(4): 79-83. DOI：

摘要

基于内容的图像检索系统在用SVM算法进行反馈时

为了提高图像检索的精度

减少用户的反馈次数

提出了KRSVM算法.该算法通过运用颜色矩、颜色直方图和Hu矩提取图像的颜色和形状特征

并用K-means算法对特征进行多次聚类

同时使用SVM算法对其图像样本进行训练时

引入了多个SVM核函数和Relief算法

对核函数和图像特征进行权重分配.相比较传统的SVM算法和K-SVM算法

本算法在一定程度上提高了图像检索的准确度和用户满意度.

Abstract

The feedback of the content-based image retrieval system with the SVM algorithm

In order to improve the accuracy of image retrieval and reduce the number of user feedback

we proposed a novel algorithm called KRSVM

extracting features of the image about color shape and shape by using color moments

color histograms and Hu moments

and they are clustered with the multiple clusters of the K-means algorithm

at the same time

the SVM algorithm trains the image samples using a number of SVM kernel functions and Relief algorithm

they are for the weight distribution of the kernel functions and the image features. Compared with the traditional SVM algorithm and K-SVM algorithm

this algorithm is more better in terms of accuracy and requirements to some extent.

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references

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