Department of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY 12181.
IEEE Trans Pattern Anal Mach Intell. 1982 Jan;4(1):61-8. doi: 10.1109/tpami.1982.4767197.
A new approach to texture classification is described which is based on measurements of the spatial gray-level co-occurrence probability matrix. This approach can make use of assumed stochastic models for texture in imagery and is an approximation to the statistically optimum maximum likelihood classifier. The efficacy of the approach is demonstrated through experimental results obtained with real-world texture data.
一种新的纹理分类方法被描述，该方法基于空间灰度共生概率矩阵的测量。这种方法可以利用图像中纹理的假设随机模型，并且是统计最优最大似然分类器的近似。通过使用真实世界纹理数据获得的实验结果证明了该方法的有效性。
