首页 | 本学科首页   官方微博 | 高级检索  
     

一种基于小波纹理特征的目标检测方法
引用本文:宋新,罗军,王鲁平,沈振康.一种基于小波纹理特征的目标检测方法[J].红外技术,2006,28(9):545-548.
作者姓名:宋新  罗军  王鲁平  沈振康
作者单位:国防科技大学电子科学与工程学院ATR重点实验室,湖南,长沙,410073
摘    要:给出了一种利用小波分块分解和灰度共生矩阵特征来提取目标的方法。首先对图像进行分块小波变换,然后求分块灰度共生矩阵并且计算小波共生矩阵特征向量,选取纹理特征最大的作为种子区域;最后利用均值聚类的方法进行目标标记。实验结果证明,能够检测红外和可见光图像中各种类型的目标。

关 键 词:小波变换  灰度共生矩阵  图像纹理  均值聚类
文章编号:1001-8891(2006)09-0545-05
收稿时间:2006-03-07
修稿时间:2006-03-07

A Target Detection Approach Based on Wavelet Texture Characterization
SONG Xin,LUO Jun,WANG Lu-ping,SHEN Zhen-kang.A Target Detection Approach Based on Wavelet Texture Characterization[J].Infrared Technology,2006,28(9):545-548.
Authors:SONG Xin  LUO Jun  WANG Lu-ping  SHEN Zhen-kang
Affiliation:National University of Defense Technology College ATR key lab, Changsha Hunan 410073, China
Abstract:An approach of detecting targets based on wavelet transform and gray level co-occurrence matrix was presented. Wavelet transform is used to decompose an image into blocks; the gray level co-occurrence matrix and each block wavelet co-occurrence feature value are evaluated. A block with max texture value is selected as a seed block and mean clustering method is used to mark blocks. Experiments show this method can detect various targets in IR and visible images.
Keywords:Wavelet transform  GLCM  image texture  mean clustering
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号