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基于GLCM算法的图像纹理特征分析 被引量:34

Analysis on Image Texture based on Gray-level Co-occurrence Matrix
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摘要 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。 In-depth study on gray level co-occurrence matrix(GLCM) is done,the meaning of the fourteen texture features based on gray level co-occurrence matrix is explained,and the redundancy existing between the texture features is pointed out.The analysis,calculation and extraction of texture image gray-level co-occurrence matrix indicate that gray-level co-occurrence matrix could be used to describe the image characteristics consistent with texture features,while certain redundancy exists between fourteen texture features of the image.In practice,several significant features are selected for the image texture classification based on the differences of the image texture features.Texture analysis and experimental results are of great guiding importance for the practical application of image texture features.
出处 《通信技术》 2012年第2期108-111,共4页 Communications Technology
基金 华侨大学自然科学基金(批准号:09BS102) 华侨大学基本科研业务费专项基金(No.JB-ZR1145) 厦门市科技计划项目(No.3502Z20103026)
关键词 灰度共生矩阵 纹理特征 图像分类 gray-level co-occurrence matrix texture feature image classification
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