AN INVESTIGATION OF THE TEXTURAL CHARACTERISTICS ASSOCIATED WITH GRAY-LEVEL COOCCURRENCE MATRIX STATISTICAL PARAMETERS
AN INVESTIGATION OF THE TEXTURAL CHARACTERISTICS ASSOCIATED WITH GRAY-LEVEL COOCCURRENCE MATRIX STATISTICAL PARAMETERS
复制标题
DOI：
10.1109/36.377929
复制
发表时间：
1995-03-01
影响因子：
8.2
通讯作者：
PARMIGGIANI, F
中科院分区：
文献类型：
--
作者：
BARALDI, A;PARMIGGIANI, F
本研究旨在探究六个灰度共生矩阵（GLCM）参数的统计学意义。这一目标主要通过自洽的理论评估来实现，以便不受测试图像的影响。这六个统计参数分别是能量、对比度、方差、相关性、熵和逆差矩，它们被认为是哈拉里克等人最初提出的14个参数中最相关的。支持理论思考的函数分析基于分割纹理值特征空间中的自然聚类。结果表明，在六个GLCM统计参数中，可以识别出五组不同的集合，每组都具有特定的纹理意义。第一组包含能量和熵，而其余四个参数可被视为属于四个不同的集合。能量和对比度这两个参数被认为是区分不同纹理模式最有效的。提出了一个新的GLCM统计参数——递归性，以替代与对比度存在一定程度相关性的能量。研究表明，在某些情况下，用灰度级差直方图（GLDH）的计算来替代GLCM的计算可能是合理的，以便在纹理测量精度、计算机存储和计算时间之间取得更好的平衡。
The aim of this study was to investigate the statistical meaning of six GLCM (Gray Level Cooccurrence Matrix) parameters, This objective was mainly pursued by means of a self-consistent, theoretical assessment in order to remain independent from test image.The six statistical parameters are energy, contrast, variance, correlation, entropy and inverse difference moment, which are considered the most relevant among the 14 originally proposed by Haralick et al.The functional analysis supporting theoretical considerations was based on natural clustering in the feature space of segment texture values.The results show that among the six GLCM statistical parameters, five different sets can be identified, each set featuring a specific textural meaning. The first set contains energy and entropy, while the four remaining parameters can be regarded as belonging to four different sets. Two parameters, energy and contrast, are considered to be the most efficient for discriminating different textural patterns.A new GLCM statistical parameter, recursivity, is presented in order to replace energy which presents some degree of correlation with contrast.It is demonstrated that in some cases it may be reasonable to replace the computation of GLCM viith that of GLDH (Gray Level Difference Histogram), in order to benefit by a better compromise between texture measurement accuracy, computer storage and computation time.