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基于贝叶斯网络模型的纹理分析及分类

Bayesian Network Based Texture Analysis and Classification

  • 摘要: 用贝叶斯网络对纹理图像建模,并基于此模型给出了一种纹理分类的方法.把纹理图像在一个窗口内各个像素的灰度值看作贝叶斯网络的一次实现,通过训练得到各类纹理所对应贝叶斯网络的结构和参数,用纹理图像像素点在网络中的条件概率分布作为特征进行纹理分类.实验结果证明了该方法的有效性.

     

    Abstract: A novel Bayesian network(BN) texture model is proposed.Based on the model,a texture classification method is given.Pixel values in an image window are taken as a realization of a BN,and the structure and parameters of BN for each texture class are then studied.The conditional distribution probability of the pixels is used as the feature for texture classification.Experimental results show that the proposed model is effective for texture analysis and classification.

     

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