【作者】 戚大伟； 牟洪波；

【Author】 Qi Dawei Mu Hongbo (College of Science,Northeast Forestry University,Harbin150040,China)

【机构】 东北林业大学理学院；

【摘要】 采用X射线作为检测手段,对木材进行无损检测,通过检测透过木材的射线强度来断定检测木材是否存在缺陷.对得到的木材缺陷进行图像处理,将木材缺陷图像转化为灰度图像,再把灰度图像转换为二值图像.根据经验选择相应的阈值,提取出清晰的木材缺陷边缘,把木材缺陷部位从背景中分离出来,完成木材缺陷图像分割.对Hu提出的区域不变矩进行扩展,得到一组新的描述形状特征的参数,这些参数具有平移、缩放和旋转不变性,并且具有较低的计算复杂性.将这些特征参数预处理后输入BP神经网络,对木材缺陷进行检测,检测准确率达到86%以上,试验结果表明此方法的可行性,为实现木材缺陷的自动检测提供了新的途径.更多还原

【Abstract】 X-ray was adopted as a measure method for wood nondestructive testing.Wood defects were identified by testing X-ray transmitted intensity through the wood.The detected defects were conducted by image processing.Wood defect images were first converted into grayscale images,and then into binary images.With the threshold values determined by some known experience,the wood defects were separated from the background and the clear wood defects edge was extracted.A group of parameters describing shape features were obtained by extending Hu invariant moments.Those parameters not only have translation invariance,scaling invariance and rotation invariance,but also have lower computational complexity.The feature parameters were input into BP(back propagation) neural network after preprocessing,and then the wood defects were recognized.The experi-mental results show that the recognition ratio is above 86%,indicating that this method is successful for detection and classification of wood defects.This study offers a new method for automatic detection of wood defects.更多还原