用扫描获取试样腐蚀图像,采用二维离散小波变换对其三级分解,提取各子图像的L1范数、平均能量和熵作为纹理特征,并计算同级纹理特征的各向异性特征.应用多元线性回归分析图像纹理特征的各向异性特征与试样腐蚀参数的相关性.结果表明,点蚀系数与熵的各向异性特征具有很好的相关性,进行回归方程和回归系数的显著性检验,最后确定点蚀系数与图像的1,2级各向异性熵显著相关,相关系数达0.96.建立点蚀系数的预测模型.
First,use a scanner to acquire corrosion images of samples;second,apply two-dimension discrete wavelet transform to decompose the images in three-level,whilst L1 norm,energy and entropy of subimages are extracted as texture features of the images;then the anisotropy of texture feature in the same level is calculated;finally,the correlations between the anisotropy of texture features and corrosion parameters are studied by multivariate linear regression.The result shows that there is a good linear relationship between pitting factor and entropy anisotropy.After taking the significance tests of the regression equation and regression coefficient,it is finally obtained that pitting factor has a good linear relationship with the entropy anisotropy of level 1 and level 2,of which the correlation coefficient is high up to 0.96.So a correlation model can be built to forecast pitting factor.
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