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机械加工零件表面纹理缺陷检测
引用本文:黎明,马聪,杨小芹.机械加工零件表面纹理缺陷检测[J].中国图象图形学报,2004,9(3):318-322.
作者姓名:黎明  马聪  杨小芹
作者单位:南昌航空工业学院测试与控制工程系 南昌330034 (黎明,马聪),南昌航空工业学院测试与控制工程系 南昌330034(杨小芹)
基金项目:江西省跨世纪学科带头人培养计划项目(第三批),江西省测控研究中心开放基金(200104003)
摘    要:在一些对机械加工零件表面的加工精度和表面质量要求较高的自动化工业中,对机械加工零件表面纹理缺陷进行可靠的、有效的检测和分析可以大大地提高生产加工的自动化水平。为了能够对机械加工零件表面进行可靠、有效的检测,根据机械加工零件表面的纹理特点,设计了一种新的图像频域滤波器,用于增强缺陷纹理图像和抑制背景纹理对缺陷纹理检测的干扰,再通过图像分割的方法的实现了缺陷纹理和背景纹理的分割。实验结果显示,这种方法检测速度较快,尤其适用于机械精加工零件表面纹理缺陷的准实时检测。

关 键 词:图像滤波  缺陷检测  图像分割  机械加工零件  表面纹理
文章编号:1006-8961(2004)03-0318-05

Detection of Texture Defects for Machined Surface
LI Ming,MA Cong,YANG Xiao qin,LI Ming,MA Cong,YANG Xiao qin and LI Ming,MA Cong,YANG Xiao qin.Detection of Texture Defects for Machined Surface[J].Journal of Image and Graphics,2004,9(3):318-322.
Authors:LI Ming  MA Cong  YANG Xiao qin  LI Ming  MA Cong  YANG Xiao qin and LI Ming  MA Cong  YANG Xiao qin
Abstract:Surface inspection for quality control is the most important part of today's highly competitive industrial production. There are a great number of manufacturing processes where inspection for surface finishing or surface defects is attempted: steel strip, hot steel slabs, plastic plates, painted surfaces, wooden surfaces, profiles and etc. But the surface inspection is usually a bottleneck in many production processes. Reliable and effective detection of machined surface defects is of great importance in automatic industry that needs high surface aesthetics and machined precision, it can obviously enhance the entire efficiency for the automatic manufacturing. A novel image filter has been developed in this paper, it transforms the original image via FFT and then filters out those Fourier areas which Fourier energy concentrates on. These Fourier areas correspond to the background texture on machined directions. The method can enhance the texture defects and reduce the effect of background texture by analyzing the texture features of machined surfaces. Then the texture defects can be easily detected through the segmentation of defects and background. The experimental results have shown that the method can obtain precise results and high detection speed.
Keywords:Image filter  Defects detection  Image segmentation
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