Fabric defect segmentation using multichannel blob detectors
Fabric defect segmentation using multichannel blob detectors
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DOI：
10.1117/1.1327837
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发表时间：
2000-12
影响因子：
1.3
通讯作者：
Ajay Kumar;G. Pang
中科院分区：
文献类型：
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作者：
Ajay Kumar;G. Pang
研究了织构材料的自动缺陷检测问题。提出了一种基于多通道滤波的新算法。通过使用由多个真实的Gabor函数组成的滤波器组对所获取的图像进行滤波来提取纹理特征，所述滤波器组具有多个窄的空间频率和方向通道。对于每个图像，我们提出了使用图像融合多路复用的信息从16个不同的渠道在四个方向获得。阈值的自适应程度和材料杂质的灵敏度的相关影响进行了讨论。该算法实现了大量的计算节省了以前的方法，并使高质量的实时缺陷检测。在真实的织物疵点上对该算法进行了测试，实验结果证实了该方法的有效性。© 2000年照片-光学仪器工程师协会。（S0091-3286（00）01912-7）
The problem of automated defect detection in textured mate- rials is investigated. A new algorithm based on multichannel filtering is presented. The texture features are extracted by filtering the acquired image using a filter bank consisting of a number of real Gabor functions, with multiple narrow spatial frequency and orientation channels. For each image, we propose the use of image fusion to multiplex the infor- mation from sixteen different channels obtained in four orientations. Adaptive degrees of thresholding and the associated effect on sensitivity to material impurities are discussed. This algorithm realizes large com- putational savings over the previous approaches and enables high- quality real-time defect detection. The performance of this algorithm has been tested thoroughly on real fabric defects, and experimental results have confirmed the usefulness of the approach. © 2000 Society of Photo- Optical Instrumentation Engineers. (S0091-3286(00)01912-7)