A method for fabric defect detection based on OpenCV with rich computer vision and image processing algorithms and functions is presented. Firstly, OpenCV image processing functions implement fabric image preprocessing. We use morphological opening and closing operations to segment image because of their blur defects. Secondly, "seed filling" algorithm is applied to connect broke lines to keep defect edge smoothing. Finally, the edge detection function is to complete accurate positioning defects. Experimental results under Borland C++ Builder 6.0 show that OpenCV based fabric defect detection methods are simple, high code integration, accurate defects positioning, which can be applied to develop real-time fabric defect detection system.
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机译：提出了一种基于具有丰富电脑视觉和图像处理算法的opencv的织物缺陷检测方法和功能。首先，OpenCV图像处理功能实现织物图像预处理。由于其模糊缺陷，我们使用形态开放和关闭操作来分段图像。其次，施加“种子填充”算法以连接破折线以保持缺陷边缘平滑。最后，边缘检测功能是完成准确的定位缺陷。 Borland C ++ Builder 6.0下的实验结果表明，基于OpenCV的织物缺陷检测方法简单，码集成，准确的缺陷定位，可应用于开发实时织物缺陷检测系统。
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