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. Secondjy, "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OpenCV的具有丰富计算机视觉和图像处理算法及功能的织物疵点检测方法。首先，OpenCV图像处理功能实现了织物图像预处理。由于图像的模糊缺陷，我们使用形态学的打开和关闭操作来分割图像。其次，“使用种子填充算法连接断线以保持缺陷边缘平滑。最后，边缘检测功能是完成精确的定位缺陷。在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，高效。代码集成，准确的缺陷定位，可用于开发实时织物缺陷检测系统。
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