J4

• 计算机科学 • 上一篇    下一篇

基于DCT和SVD的图像检索算法

许相莉, 张利彪, 于哲舟, 周春光   

  1. 吉林大学 计算机科学与技术学院, 长春 130012
  • 收稿日期:2008-04-24 修回日期:1900-01-01 出版日期:2008-11-26 发布日期:2008-11-26
  • 通讯作者: 周春光

Image Retrieval Algorithm Based on DCT and SVD

XU Xiangli, ZHANG Libiao, YU Zhezhou, ZHOU Chunguang   

  1. College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2008-04-24 Revised:1900-01-01 Online:2008-11-26 Published:2008-11-26
  • Contact: ZHOU Chunguang

摘要: 提出一种在子块分割和区域划分的基础上, 利用离散余弦变换和奇异值分解对图像进行特征提取的检索算法. 首先对图像进行子块分割, 利用离散余弦变换提取重要系数作为子块颜色特征, 进而对图像进行区域划分, 将每个区域中的子块颜色特征分量组成矩阵进行奇异值分解, 得到该区域的检索特征向量, 从而完成图像检索. 实验结果表明, 该算法取得了较好的查全率和查准率, 具有较好的检索效果.

关键词: 离散余弦变换, 奇异值分解, 图像检索

Abstract: A feature extraction and retrieval algorithm based on childblock partition and area division using discrete cosine transformation and singular value decomposition is proposed. First the image is divided into childblocks, discrete cosine transformation is used to extract important coefficients as color feature of the childblock, and then the image is divided into areas, some matrixes are constructed of the discrete cosine transformation coefficients in this area, which are submitted to singular value decomposition to gain the retrieval feature vector to accomplish image retrieval. Experiments show that the proposed algorithm gains good recall and precision, and has a good retrieval effect.

Key words: discrete cosine transformation, singular value decomposition, image retrieval

中图分类号: 

  • TP391