Extraction of color image texture feature based on gray-level co-occurrence matrix
HOU Qunqun1, WANG Fei1,2, YAN Li1
1. College of Resources and Environment, Northwest A & F University, Yangling 712100, China;
2. Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China
Texture plays a very important role in image retrieval and classification, and texture feature extraction has been a research hotspot. Most present existing texture extraction algorithms can be only used to calculate texture features of gray image. Texture extraction algorithm for color image is very few. Referring to the analytical method of gray level co-occurrence matrix (GLCM),the authors analyzed the influence law of parameters (direction,distance,grayscale,window size)on GLCM texture features of color image. A color image texture feature extraction method(color GLCM,CGLCM)based on GLCM was realized. Through analyzing the influence law of these parameters on four texture features(ASM(angular second moment),Entropy,Contrast,Correlation),a proper parameter value range was given and the CGLCM method was optimized. The results of comparing CGLCM method with GLCM method show that the four texture features calculated with CGLCM method have better robustness and identification capability. These results can provide reference for image retrieval and classification based on texture information.
侯群群, 王飞, 严丽. 基于灰度共生矩阵的彩色遥感图像纹理特征提取[J]. 国土资源遥感, 2013, 25(4): 26-32.
HOU Qunqun, WANG Fei, YAN Li. Extraction of color image texture feature based on gray-level co-occurrence matrix. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(4): 26-32.
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