摘要
利用激光扫描技术形成了待检测材面的轮廓信息,把激光位移传感器输出的轮廓距离信息转换成图像的象素值而形成轮廓图像。根据裂缝和孔洞缺陷的形状特征,在统计的基础上提取了裂缝和孔洞缺陷的四个识别特征,并在此基础上开发了用于裂缝和孔洞缺陷识别的八条规则。结果表明,所开发的基于激光扫描成像技术基础上的锯材裂缝和孔洞缺陷的视觉识别系统不仅可以正确表征裂缝和孔洞等厚度缺陷信息,而且该系统能够精确地定位和分类上述缺陷。
We have developed a laser scanning system to detect the splits and the holes based on their thickness, which correlates spatially with the profile information. The displacements measured by the laser sensor were converted to pixel values to generate the displacement profile image. Both the splits and the holes manifested well in the image. A dedicated image-processing program written in Visual Basic has been developed. The defects regions were accurately located by the image processing. To identify the defects, eight recognition rules based on four features have been utilized. Furthermore, a method based on the pixel model was proposed to compute the area of the defect. The results indicated that the defects could be identified correctly, and the areas could be computed accurately by using the pixels model.
出处
《木材加工机械》
2008年第5期7-11,21,共6页
Wood Processing Machinery
基金
广东省自然科学基金项目(4400-E07116)
教育部留学回国人员科研启动基金项目。
关键词
木材缺陷
锯材
图像处理
机器视觉
defects： sawn lumber： image processing, machine vision
