Automated inspection of engineering ceramic grinding surface damage based on image recognition
Automated inspection of engineering ceramic grinding surface damage based on image recognition
复制标题
基于图像识别的工程陶瓷磨削表面损伤自动检测
DOI：
10.1007/s00170-012-4338-2
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发表时间：
2012-07
影响因子：
3.4
通讯作者：
Liang, Xiaohu
中科院分区：
文献类型：
--
作者：
Chen, Shangong;Lin, Bin;Han, Xuesong;Liang, Xiaohu
由于工程陶瓷磨削工件通常存在断裂、裂纹等加工损伤，传统的检测方法无法准确反映工件的真实表面。因此，本文介绍了一种基于图像处理技术、模式识别和机器视觉的工程陶瓷加工表面损伤自动检测系统。首先，工程陶瓷加工表面是否含有磨削织构对表面损伤的准确识别影响很大，因此巧妙地采用傅里叶变换去除磨削织构。其次，通过图像降噪、对比度增强和图像分割，得到图像预处理的最优组合。然后，通过综合提取表面特征参数，根据形状特征和纹理特征构建基于C4.5算法的决策树分类器。最后，本文实现了工程陶瓷磨削表面损伤的自动提取与分类，破损识别准确率达到93%以上。实验结果表明，该方法对工程陶瓷表面的缺陷检测是有效的，也可为工程陶瓷工件的后功能层次划分提供一定的分析依据。
As the engineering ceramic ground workpieces usually contain machining damage such as breaks and cracks, the traditional test methods cannot accurately reflect the real surface. Therefore, this paper describes an automatic damage detection system of the engineering ceramic machined surface using image processing techniques, pattern recognition, and machine vision. First, it has great influence on the exact identification of surface damage if engineering ceramic machined surfaces contain grinding texture, so Fourier transform is skillfully adopted to remove grinding texture. Second, through image noise reduction, contrast enhancement, and image segmentation, an optimal combination of image preprocessing is obtained. Then, by comprehensive extraction of surface feature parameters, decision tree classifier based on the C4.5 algorithm is built according to shape features and texture features. Finally, the paper achieves automatic extraction and classification of engineering ceramic grinding surface damage, and the recognition accuracy of breakage reaches over 93 %. Experimental results show that this method is effective in defect detection of the engineering ceramic surface, and it also can provide some analytical basis for the post-function hierarchy partition of engineering ceramic workpieces.
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影响因子：
6.3
作者：
Hong-Dar Lin
通讯作者：
Hong-Dar Lin
DOI：
10.1016/j.ijmachtools.2007.10.013
发表时间：
2008-05-01
影响因子：
14
作者：
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通讯作者：
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影响因子：
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作者：
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DOI：
10.1109/ias.1999.805975
发表时间：
1999-10
期刊：
Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370)
影响因子：
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作者：
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通讯作者：
Chi-Ho Chan;G. Pang
DOI：
10.1007/s00170-010-3141-1
发表时间：
2011-01
期刊：
The International Journal of Advanced Manufacturing Technology
影响因子：
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作者：
Ssu-Han Chen;D. Perng
通讯作者：
Ssu-Han Chen;D. Perng