【摘要】 为了识别死节、活节、虫眼三种木材表面缺陷,采用Gabor变换和模糊C均值聚类进行缺陷分割;采用数学形态学运算对分割图像进行了后处理;获取了木材缺陷区域的12维频率能量参数和2维几何形状参数;用支持向量机进行木材表面缺陷类型的识别。采用Gabor变换和模糊C均值聚类方法对死节、活节、虫眼三种木材表面缺陷的分割精度都达到94%以上,支持向量机对缺陷类型分类正确率达到93%以上,这说明本文的方法对木材表面缺陷的分割与识别是可行的。更多还原

【Abstract】 In order to recognize the wood surface defects of dead knot,live knot,and worm hole,Gabor transtorm and fuzzy C-means clustering algorithm were used to segment wood image defects.Mathematical morphology was used in post-processing operation of segmented wood images,12 frequency-enengy parameters and 2 shape parameters of defect targets were calculated.Support vector machines were used in the recognition of wood surface defect types.The segmentation accuracy to defects reached up to 94%,and the recognition accuracy to defect types of Support vector machines reached up to 93%.The result shows that it is feasible to segment and identify wood surface defects.更多还原