A Hough Line Detection Based Glass Surface Defects Recognition Algorithm

Zifan Li, Hua Zhou
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引用次数: 1

Abstract

This paper proposes a defect detection algorithm based on defects feature on the glass surface. The process of defects recognition can be divided into five parts. First, median filter is used to eliminate the noise jamming of the glass image. Then laplacian sharping method is applied to enhance the image contrast. After that, the image is segmented by threshold to extract defects. In order to solve the problem of the noise in binary image processing, this paper uses morphological closure operation to remove the tiny connected areas. Finally, scratches are detected by Hough transform. The results of experiment verified that, compared with traditional methods, image processing based on the proposed method has higher detection efficiency and accuracy.
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基于霍夫线检测的玻璃表面缺陷识别算法
提出了一种基于玻璃表面缺陷特征的缺陷检测算法。缺陷识别的过程可分为五个部分。首先,采用中值滤波消除玻璃图像的噪声干扰。然后采用拉普拉斯锐化方法增强图像对比度。然后,对图像进行阈值分割,提取缺陷。为了解决二值图像处理中的噪声问题,本文采用形态学闭合运算去除微小的连通区域。最后利用霍夫变换检测划痕。实验结果证明,与传统方法相比,基于该方法的图像处理具有更高的检测效率和精度。
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