首页> 外文会议>IEEE International Conference on Automation and Computing >A self-reference scheme based on structure-texture decomposition for crack defect detection with electroluminescence images
【24h】

A self-reference scheme based on structure-texture decomposition for crack defect detection with electroluminescence images

机译:一种基于结构纹理分解的自律方案,用于电致发光图像裂缝缺陷检测

获取原文

摘要

Surface defect detection based on machine vision has drawn much attention today. Traditional methods aim at uniform repetitive texture, thus can rarely handle inhomogeneous texture surfaces like solar cells'. Therefore, a self-reference scheme based on the decomposition of structural-texture is introduced here to observe solar cell's surface cracks under electroluminescence (EL) images. Firstly, the structure-texture decomposition of the original image is carried out, and the L0 gradient minimization and the relative total variational operation are carried out on the structural component and the textural component respectively. It turns out that the small amplitude gradient information in the structural map is removed and the crack details are preserved in the textural map. Then, the discrete wavelet transform is used to process the structural component and the textural component, and a self-reference image is obtained by combination. Through finding an appropriate radius in the spectrogram of self-reference image and setting the frequency domain inside the selected circular area to zero, we can finally acquire the precise location of the defect. The proposed method has been proved of high efficiency from a large set of tests of a real production line.
机译:基于机器视觉的表面缺陷检测今天绘制了很多关注。传统方法瞄准均匀的重复质地,因此可以很少能够处理太阳能电池等不均匀纹理表面。因此,介绍了基于结构纹理分解的自参考方案,以观察到电致发光(EL)图像下的太阳能电池的表面裂缝。首先,执行原始图像的结构纹理分解,而L 0 梯度最小化和相对总分析操作分别在结构部件和纹理部件上进行。事实证明,在纹理地图中被移除了结构图中的小幅度梯度信息,并且在纹理地图中保留了裂纹细节。然后,使用离散小波变换来处理结构部件和纹理组件,并且通过组合获得自参考图像。通过在自参考图像的频谱图中找到适当的半径并将所选圆形区域内的频域设定为零,我们最终可以获得缺陷的精确位置。已经从真正生产线的大量测试中证明了所提出的方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号