| 引用本文: | 韩芳芳,段发阶,张宝峰,段晓杰.单线阵CCD系统的表面凹坑缺陷检测方法[J].哈尔滨工业大学学报,2012,44(4):116.DOI:10.11918/j.issn.0367-6234.2012.04.023 |
| HAN Fang fang,DUAN Fa jie,ZHANG Bao feng,DUAN Xiao jie.Study and modeling for surface pit defect detection based on linear array CCD system[J].Journal of Harbin Institute of Technology,2012,44(4):116.DOI:10.11918/j.issn.0367-6234.2012.04.023 |
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| 摘要: |
| 为解决表面凹坑缺陷与其他平面表面缺陷同时在线检测的问题,提出一种基于单线阵CCD系统进行表面凹坑缺陷检测的方法．根据光辐射照射模型和相机成像模型,建立了基于单线阵CCD的凹坑检测数学模型,由模型推导出图像像素灰度与凹坑深度的关系,利用特定光源和光照角度的关系,进行表面凹坑缺陷的检测．结果表明,由于凹坑边缘部位深度的渐变引起CCD输出电压信号的渐变,凹坑图像呈现边缘像素灰度渐变现象,且随光源光照角度的降低,凹坑图像特征更加突出．边缘灰度渐变的图像特征成为凹坑缺陷与其他平面缺陷相区别的重要特征,有利于凹坑缺陷的检测与识别． |
| 关键词: 机器视觉 表面缺陷检测 凹坑检测 线阵CCD系统 汇聚线光源 |
| DOI：10.11918/j.issn.0367-6234.2012.04.023 |
| 分类号:O439 |
| 基金项目:国家“十一五”科技支撑计划项目(2006BAK02B01) |
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| Study and modeling for surface pit defect detection based on linear array CCD system |
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HAN Fangfang1,2, DUAN Fajie1, ZHANG Baofeng2, DUAN Xiaojie1
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1.State Key Lab of Precision Measuring Technology and Instruments, Tianjin University, 300072 Tianjin, China;2.School of Electrical Engineering, Tianjin University of Technology, 300382 Tianjin, China
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| Abstract: |
| To solve the problem of simultaneous detection of pit defect and other planar defects, a pit defect detection method based on single linear CCD system is developed. On the basis of light radiation, light illumination and camera imaging model, the mathematic model for pit detection based on single linear CCD system is deduced. The mathematic model indicates the relationship of image pixel gray level and pit depth. By making use of the structure of special light source and illumination angle, the surface pit defect can be detected. The experimental results show that the gradual change of pit edge depth causes the gradual change of CCD output voltage signal, and then causes the gradual change of pit image edge gray level. The lower the illumination angle, the more obvious the image feature. The image feature of edge pixel gray level gradual change becomes the most important feature for the distinction of pit defect and other planar defects, which contributes to the pit defect detection and recognition. |
| Key words: machine vision surface defect detection pit detection linear CCD system convergent liner light source |
