融合方向测度和灰度共生矩阵的纹理特征提取算法研究
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摘要
为了解决提取图像纹理特征时所遇到的纹理方向抑制问题,提出一种融合方向测度和灰度共生矩阵的纹理特征提取算法。该算法通过灰度共生矩阵,提取图像的Haralick特征,其中包括对比度、相关性、能量、逆差矩等,然后利用方向测度引入权值因子,并将其与所提取的Haralick特征相融合,最后对融合后的各个分量进行高斯归一化处理,获取最终的纹理特征集。实验结果表明,与采用灰度共生矩阵方法相比,该算法可以有效的避免图像纹理方向的抑制,所提取的纹理特征具有更强的图像识别能力,对Brodatz标准纹理库分类的正确率也有一定的提高。
To solve the texture direction suppression problem occurring on texture feature extraction of image,a new feature extraction algorithm fused with direction measure and GLCM was proposed. The algorithm extracts Haralick textural features based on GLCM,which include contract,correlation,angular second moment and homogeneity. Moreover,weight factors are introduced based on the direction measure. Then,the ultimate textural feature which is normalized by gauss method is extracted by fusing Haralick textural features and weight factors together. The experimental results show that the proposed algorithm can avoid the suppression problem of texture direction effectively and also can easily identify the textural image. The accuracy of classification for Brodatz has a certain improved compared with the GLCM method.
To solve the texture direction suppression problem occurring on texture feature extraction of image,a new feature extraction algorithm fused with direction measure and GLCM was proposed. The algorithm extracts Haralick textural features based on GLCM,which include contract,correlation,angular second moment and homogeneity. Moreover,weight factors are introduced based on the direction measure. Then,the ultimate textural feature which is normalized by gauss method is extracted by fusing Haralick textural features and weight factors together. The experimental results show that the proposed algorithm can avoid the suppression problem of texture direction effectively and also can easily identify the textural image. The accuracy of classification for Brodatz has a certain improved compared with the GLCM method.
引文
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2 刘健,程英蕾,孙纪达.基于GLCM特征的改进FCM的SAR图像分割方法.计算机工程与设计,2012;33(9):3502—3506Liu Jian,Cheng Yinglei,Sun Jida.Modified FCM SAR image segmentation method based on GLCM feature.Computer Engineering and Design,2012;33(9):3502—3506
3 田儆,余雪丽,钱杰.基于GLCM和CGA的人脸表情识别方法研究.微型机与应用,2010;29(18):32—36Tian Jing,Yu Xue Li,Qian Jie.Study of face expression recognition based on GLCM and CGA.Microcomputer&Its Applications,2010;29 (18):32—36
4 童敏.地震纹理属性提取方法研究及影响因素分析.北京:中国地质大学,2013Tong Min.The research of seismic texture extraction method and analysis of influencing factors.Beijing:China University of Geoscience,2013
5 雷英成,曹俊兴.地震图像的振幅共生矩阵分析及其应用.石油天然气学报,2011;33(6):64—68Lei Yingcheng,Cao Junxing.The amplitude co-occurrence matrix analysis of seismic images and its application.Journal of Oil and Gas Technology,2011;33(6):64—68
6 王国德,张培林,任国全,等.融合LBP和GLCM的纹理特征提取方法.计算机工程,2012;38(11):199—201Wang Guode,Zhang Peilin,Ren Guoquan,et al.Texture feature extraction method fused with LBP and GLCM.Computer Engineering,2012;38(11):199—201
7 陈美龙,戴声奎.基于GLCM算法的图像纹理特征分析.通信技术,2012;(2):108—111Chen Meilong,Dai Shengkui.Analysis on image texture based on gray-level co-occurrence matrix.Communications Technology,2012;(2):108—111
8 阳魁,黄新生,徐婉莹.结合灰度共生矩阵的多分辨率图像融合策略.计算机应用研究,2012;29(3):1181—1185Yang Kui,Huang Xinsheng,Xu Wanying.Fusion strategy of multiresolution image combined with gray level co-occurrence matrix.Application Research of Computers,2012;29(3):1181—1185
9 于晓晗,袁保宗.方向测度及其在纹理识别中的应用.自动化学报,1990;16(4):347—351Yu Xiaohan,Yuan Baozong.Direction measure and its application to texture classification.Acta Automatica Sinica,1990;16(4):347 —351
10 Haralick R M,Shanmugam K,Dinstein I H.Textural features for image classification.Systems,Man and Cybernetics,IEEE Transactions on,1973;(6):610—621
11 Baraldi A,Parmiggiani F.An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters.Geoscience and Remote Sensing,IEEE Transactions on,1995;33(2):293—304
2 刘健,程英蕾,孙纪达.基于GLCM特征的改进FCM的SAR图像分割方法.计算机工程与设计,2012;33(9):3502—3506Liu Jian,Cheng Yinglei,Sun Jida.Modified FCM SAR image segmentation method based on GLCM feature.Computer Engineering and Design,2012;33(9):3502—3506
3 田儆,余雪丽,钱杰.基于GLCM和CGA的人脸表情识别方法研究.微型机与应用,2010;29(18):32—36Tian Jing,Yu Xue Li,Qian Jie.Study of face expression recognition based on GLCM and CGA.Microcomputer&Its Applications,2010;29 (18):32—36
4 童敏.地震纹理属性提取方法研究及影响因素分析.北京:中国地质大学,2013Tong Min.The research of seismic texture extraction method and analysis of influencing factors.Beijing:China University of Geoscience,2013
5 雷英成,曹俊兴.地震图像的振幅共生矩阵分析及其应用.石油天然气学报,2011;33(6):64—68Lei Yingcheng,Cao Junxing.The amplitude co-occurrence matrix analysis of seismic images and its application.Journal of Oil and Gas Technology,2011;33(6):64—68
6 王国德,张培林,任国全,等.融合LBP和GLCM的纹理特征提取方法.计算机工程,2012;38(11):199—201Wang Guode,Zhang Peilin,Ren Guoquan,et al.Texture feature extraction method fused with LBP and GLCM.Computer Engineering,2012;38(11):199—201
7 陈美龙,戴声奎.基于GLCM算法的图像纹理特征分析.通信技术,2012;(2):108—111Chen Meilong,Dai Shengkui.Analysis on image texture based on gray-level co-occurrence matrix.Communications Technology,2012;(2):108—111
8 阳魁,黄新生,徐婉莹.结合灰度共生矩阵的多分辨率图像融合策略.计算机应用研究,2012;29(3):1181—1185Yang Kui,Huang Xinsheng,Xu Wanying.Fusion strategy of multiresolution image combined with gray level co-occurrence matrix.Application Research of Computers,2012;29(3):1181—1185
9 于晓晗,袁保宗.方向测度及其在纹理识别中的应用.自动化学报,1990;16(4):347—351Yu Xiaohan,Yuan Baozong.Direction measure and its application to texture classification.Acta Automatica Sinica,1990;16(4):347 —351
10 Haralick R M,Shanmugam K,Dinstein I H.Textural features for image classification.Systems,Man and Cybernetics,IEEE Transactions on,1973;(6):610—621
11 Baraldi A,Parmiggiani F.An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters.Geoscience and Remote Sensing,IEEE Transactions on,1995;33(2):293—304
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