[1]焦蓬蓬 郭依正 刘丽娟 卫星.灰度共生矩阵纹理特征提取的Matlab实现[J].计算机技术与发展,2012,(11):169-171.
　JIAO Peng-peng,GUO Yi-zheng,LIU Li-juan,et al.Implementation of Gray Level Co-occurrence Matrix Texture Feature Extraction Using Matlab[J].,2012,(11):169-171.
点击复制

灰度共生矩阵纹理特征提取的Matlab实现()
分享到：

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年11期
页码:
169-171
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
Implementation of Gray Level Co-occurrence Matrix Texture Feature Extraction Using Matlab
文章编号:
1673-629X（2012）11-0169-03
作者:
焦蓬蓬 郭依正 刘丽娟 卫星
南京师范大学泰州学院
Author(s):
JIAO Peng-peng;  GUO Yi-zheng;  LIU Li-juan;  WEI Xing
Taizhou College of Nanjing Normal University
关键词:
灰度共生矩阵; 纹理特征; Matlab
Keywords:
gray level co-occurrence matrix;  texture feature;  Matlab
分类号:
TP391.9
文献标志码:
A
摘要:
图像的特征提取是图像的识别和分类、基于内容的图像检索、图像数据挖掘等研究内容的基础性工作，其中图像的纹理特征对描述图像内容具有重要意义，纹理特征提取已成为目前图像领域研究的热点。文中深入研究了基于灰度共生矩阵（GLCM）的纹理特征提取方法，给出了基于Matlab的简便实现代码，分析了共生矩阵各个构造参数对构造共生矩阵的影响。分析结果对优化灰度共生矩阵的构造、实现基于灰度共生矩阵（GLCM）的特定图像的纹理特征提取等都具有重要参考意义
Abstract:
The texture feature extraction of image is a foundational work for image recognition and classification, content-based image re trieval ,image data mining, etc. The texture feature of image is significant for description of image content. And it is a hot topic in the research of image now. The method of texture feature extraction based on gray level co-occurrence matrix （GLCM） was studied. Analyzed the effect of each parameter on constructing the co-occurrence matrix and implemented the feature extraction using Matlab. The analytical results provide valuable reference for creating GLCM better and extracting texture features of specific kinds of images

相似文献/References:

[1]李晶 姚明海.基于支持向量机的语义图像分类研究[J].计算机技术与发展,2010,(02):75.
　LI Jing,YAO Ming-hai.Research of Semantic Image Classification Based on Support Vector Machine[J].,2010,(11):75.
[2]王森 陈炬桦.基于神经网络和综合特征的车牌定位算法[J].计算机技术与发展,2008,(02):38.
　WANG Sen,CHEN Ju-hua.Algorithm of Car Plate Location Based on Neural Network and Integrated Features[J].,2008,(11):38.
[3]赵福君 李景文 陈大克 刘卉卉.数学形态学的纹理图像分割方法[J].计算机技术与发展,2008,(05):112.
　ZHAO Fu-jun,LI Jing-wen,CHEN Da-ke,et al.Image Segmentation Method about Mathematical Morphology Based on Textural Features[J].,2008,(11):112.
[4]肖秦琨,刘米娜,高嵩.基于颜色和纹理特征的遥感图像检索[J].计算机技术与发展,2013,(04):107.
　XIAO Qin-kun,LIU Mi-na,GAO Song.Remote Sensing Image Retrieval Based on Color and Texture[J].,2013,(11):107.
[5]王萍,张媛,李聪,等. 基于灰度共生矩阵的特征构建及超折射滤除[J].计算机技术与发展,2014,24(08):1.
　WANG Ping,ZHANG Yuan,LI Cong,et al. Feature Construction and AP Clutter Filtering Based on Gray Lever Co-occurrence Matrix[J].,2014,24(11):1.
[6]王职军[],梁光明[],刘任任[],等. 共生矩阵纹理特征的DSP优化实现[J].计算机技术与发展,2014,24(11):13.
　WANG Zhi-jun[],LIANG Guang-ming[],LIU Ren-ren[],et al. DSP Optimized Implementation of Co-occurrence Matrix Texture Feature[J].,2014,24(11):13.
[7]王树梅,张文斌. 小波变换在数字图像边缘探测中的应用[J].计算机技术与发展,2015,25(06):16.
　WANG Shu-mei,ZHANG Wen-bin. Application of Wavelet Transform in Edge Detection for Digital Image[J].,2015,25(11):16.
[8]黎粤华,单磊,田仲富,等. 基于多特征融合的视频烟雾检测[J].计算机技术与发展,2016,26(01):129.
　LI Yue-hua,SHAN Lei,TIAN Zhong-fu,et al. Video Smoke Detection Based on Multi Feature Fusion Technology[J].,2016,26(11):129.
[9]刘少林,朱文球,孙文静,等.基于联合直方图的自适应粒子滤波跟踪算法[J].计算机技术与发展,2018,28(06):106.[doi:10.3969/ j. issn.1673-629X.2018.06.024]
　LIU Shao-lin,ZHU Wen-qiu,SUN Wen-jing,et al.An Adaptive Particle Filtering and Tracking Algorithm Based on Joint Histogram[J].,2018,28(11):106.[doi:10.3969/ j. issn.1673-629X.2018.06.024]
[10]宋辉,刘奉华.基于数据预分析的虹膜识别方法[J].计算机技术与发展,2018,28(08):58.[doi:10.3969/ j. issn.1673-629X.2018.08.012]
　SONG Hui,LIU Feng-hua.An Iris Recognition Method Based on Data Pre-analysis[J].,2018,28(11):58.[doi:10.3969/ j. issn.1673-629X.2018.08.012]
[11]崔红霞,黄科涵.基于混合纹理的计算机自动分类方法[J].计算机技术与发展,2018,28(02):158.[doi:10．3969/j．issn．1673－629X．2018．02．034]
　CUI Hong-xia,HUANG Ke-han.Computer Automatic Classification Method Based on Mixed Texture[J].,2018,28(11):158.[doi:10．3969/j．issn．1673－629X．2018．02．034]

备注/Memo

备注/Memo:
国家“十一五”计划课题（FIB070335-B8-04）焦蓬蓬（1981-），女，硕士，讲师，研究方向为数字信号处理
更新日期/Last Update: 1900-01-01