戴声奎
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基于GLCM 算法的图像纹理特征分析
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Journal:通信技术

Key Words:灰度共生矩阵;纹理特征;图像分类

Abstract:】深入研究灰度共生矩阵(GLCM,Gray Level Co-occurrence Matrix)算法,说明基于灰度共生 矩阵的14 个纹理特征具体意义,指出纹理特征之间存在冗余性。通过对纹理图像的灰度共生矩阵的计算分 析和纹理特征提取实验,表明灰度共生矩阵能够反应图像的特点,与纹理特征描述图像的特点相对应,同 时,图像的14 个纹理特征之间存在一定程度的冗余,实际中可以根据图像纹理特征的差异,选择几个显著 的纹理特征对图像进行分类。纹理特征分析和实验结果对图像纹理特征的应用具有普遍的指导意义。

Note:2013考核

Page Number:108-111

Translation or Not:no

Date of Publication:2011-12-02

First Author:DSK

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Associate professor
Supervisor of Master's Candidates

Gender:Male

Date of Birth:1971-03-25

Education Level:博士研究生

Degree:Doctoral Degree in Engineering

Date of Employment:2007-10-17

Business Address:华侨大学机电实验大楼A618

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Status:在岗

Discipline:Computer Applications Technology
Pattern Recognition and Intelligent Systems
Signal and Information Processing

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